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Secrecy Ensured Socially-Aware Resource Allocation in Device-to-Device Communications Underlaying HetNet
Abstract
Device-to-device (D2D) communication standardiza- tion is underway and considered as one of key technologies in the 5G ecosystem. Eavesdropping is a well-known security risk for D2D communications. Thus, ensuring information security for both cellular users (CUs) and D2D pairs in an underlay network is quite challenging. In this paper, we look into the problem of physical-layer secure transmission jointly with resource allocation in D2D communications. We leverage social-domain and frame a coalitional game approach, enabling multiple D2D pairs to share CU spectral resource. We assume multiple eavesdroppers based practical scenario to maximize system sum-rate, and to ensure information confidentiality for both CUs and D2D pairs. More- over, we prove our proposed algorithm stability, convergence, and computational complexity. The simulation results establish the effectiveness of our proposed approach that not only maximizes the sum-rate (i.e., 10% to 60%) but also improves the secrecy capacity (i.e., 20% to 67%) in comparison to the baseline schemes.
... Later, the researchers explored the importance of game theory and implements in their respective scenarios. In [13]- [16], the authors have implemented the game theory to achieve the high data rate and secrecy rate. They preferred coalitional, non-overlapping coalitional, and extensive game theories. ...
... We also assumed that the communication channel experiences a fading, shadowing, and path loss effects. In such case the channel gain ( ) of ℎ CE to base station ( ), ℎ (of D2D pair ) to { , , , }, ℎ CE to ℎ eavesdropper, and ℎ to ℎ eavesdropper are calculated as follows [13] [17]. ...
Device-to-device (D2D) communication is the most evolving technology in fifth-generation (5G) networks. It allows direct communication of devices in the proximity range with or without base station help. This achieves higher gains and low latency in communication and improves network spectral efficiency. Despite the aforementioned challenges, interference and eavesdropping (by a malicious node) on D2D links/pairs are significant challenges. An eavesdropper can compromise the information exchanged between the D2D devices. To mitigate the issues mentioned above nonorthogonal multiple access (NOMA) technique is quite helpful even in social scenarios. NOMA mitigates the interference issues in D2D communication, which increases the signal to interference noise ratio (SINR). Further, we used a zero-sum game approach to improve the data security and minimize eavesdropper's security risk on the D2D pair. It achieves the goal of the D2D transmitter, i.e., maximize the message security. Simulation results prove the proposed zero-sum game-based system's superiority, considering average network sum rate and average channel secrecy capacity.
... Due to the dynamic topology of multi-tier HetNets, wireless transmission is inherently vulnerable to security breaches [5]. To this end, in order to improve system secrecy, there are some works to investigate the resource allocation regarding physical layer security [6]- [8]. In particular, the authors in [6] maximized the secure capacity of device-to-device (D2D) users to improve system security for D2D-aided HetNets. ...
... To this end, in order to improve system secrecy, there are some works to investigate the resource allocation regarding physical layer security [6]- [8]. In particular, the authors in [6] maximized the secure capacity of device-to-device (D2D) users to improve system security for D2D-aided HetNets. To prolong the lifetime of wireless devices, the authors in [7] integrated simultaneous wireless information and power transfer (SWIPT) with HetNets and maximized the sum of logarithmic secrecy rates under the minimum harvested energy constraints of energy receivers and the maximum transmit power constraint of each femtocell base station (FBS). ...
Resource allocation is very important for achieving interference suppression and protecting the quality of service of users in heterogeneous networks (HetNets). However, the existing works with perfect channel state information (CSI) and ideal hardware ignored the impact of channel uncertainties and hardware impairments on system performance. In this paper, we design a robust secure resource allocation algorithm with imperfect CSI to achieve the energy efficiency (EE) maximization of femtocell users for a two-tier downlink HetNet with multiple passive eavesdroppers, where the residual hardware impairments are considered at the transceivers. The formulated EE problem is non-convex with the consideration of the maximum transmit power constraint of each base station, the cross-tier interference power constraint, as well as the secure rate constraint. By using the worst-case approach and successive convex approximation, the resource allocation problem with the infinite-dimensional constraints is converted into a convex one which is efficiently solved by using convex optimization theory. Simulation results verify that the proposed algorithm has a higher EE and causes less interference power to macrocell users by comparing it with the baseline algorithms.
... Wang et al. [15] proposed a social community-aware resource allocation architecture, where the cellular user prefers to allocate the resources to a close D2D pair in the same community. Ahmed et al. [16], [17] used a coalitional game to solve the secrecy-ensured resource allocation problem by exploiting social trust. Fan et al. [18] utilized users' social information to design a virtual MAC protocol for resource allocation. ...
... When the optimal transmission power is determined, D2D pairs and cellular users calculate the preference values of different individuals in the other set according to their utility function. For ∀ (i, i ) ∈ D d , it is necessary to determine whether each cellular user can be reused according to the constraints in (17), and then the unqualified cellular users should be removed; the removed cellular users will also remove the corresponding D2D pair from their lists because conditions 1)-3) in (17) are valid for both cellular users and D2D pairs. For ease of presentation, we use D2D pair i ∈ D d instead of D2D pair (i, i ) ∈ D d in the following. ...
The explosion of intelligent mobile applications has generated an unprecedented increase in the demand for diverse social content access. Device-to-device (D2D) communication, which enables direct transmission of content, can partly support these needs by reusing cellular spectrum resources. Most existing works focus on mitigating interference in D2D communication only in physical space. However, the effect of user content preference on interference in social space is ignored. In this paper, a satisfied matching-embedded social Internet of Things (IoT) is proposed for content preference-aware resource allocation (SIoT-RA). The social IoT architecture is explored for user social characteristic analysis scenarios to ensure credible data management. Specifically, the user’s content preference characteristics are modeled as the probability of selecting similar content in the social IoT by employing the Dirichlet process. A satisfied matching-based model is proposed and embedded into the architecture as the core algorithm to achieve content preference-aware resource allocation. This design not only helps to reduce interference from the perspective of social space but also realizes maximized and satisfactory resource allocation performance by a matching algorithm that can quantify satisfaction as perceived utility. Extensive simulation results demonstrate the significant performance gains and high cost-effectiveness of the proposed core algorithm of SIoT-RA in terms of the weighted sum data rate and users matching satisfaction.
... Information security for resource allocation in D2D communication for cellular and D2D users is challenging. In [35], the authors propose a security-enhanced social aware resource allocation for D2D communication. Most of the existing works consider imperfect Channel State Information (CSI) that includes estimation errors. ...
In recent years, there has been a trend to integrate networking and computing systems, whose management is getting increasingly complex. Resource allocation is one of the crucial aspects of managing such systems and is affected by this increased complexity. Resource allocation strategies aim to effectively maximize performance, system utilization, and profit by considering virtualization technologies, heterogeneous resources, context awareness, and other features. In such complex scenario, security and dependability are vital concerns that need to be considered in future computing and networking systems in order to provide the future advanced services, such as mission-critical applications. This paper provides a comprehensive survey of existing literature that considers security and dependability for resource allocation in computing and networking systems. The current research works are categorized by considering the allocated type of resources for different technologies, scenarios, issues, attributes, and solutions. The paper presents the research works on resource allocation that includes security and dependability, both singularly and jointly. The future research directions on resource allocation are also discussed. The paper shows how there are only a few works that, even singularly, consider security and dependability in resource allocation in the future computing and networking systems and highlights the importance of jointly considering security and dependability and the need for intelligent, adaptive and robust solutions. This paper aims to help the researchers effectively consider security and dependability in future networking and computing systems.
... These users can affect the overall sumrate of the system, which further reduces its performance. Ahmed et al. [13] presented a secure resource allocation scheme for D2d users in the presence of eavesdroppers and non-trusted D2D users. The authors assumed that the users are non-trusted without specifying any means to identify them. ...
Device-to-device (D2D) is a prominent technology of the fifth-generation's (5G) network that leverages more number of communication links with high efficiency. D2D allows direct communication between mobile devices, improving the system's spectral efficiency and overall datarate. However, D2D users reutilize the cellular users (CLUs) resource in an underlay mode. As a result, multiple users are accessing the CLUs resources, which causes high interference in the system and minimizes its overall performance. The interference effect increases with the increase in the number of non-trusted D2D users in the system. Also, the existing works have not given any means for the identification of non-trusted D2D users in the system. Motivated from the aforementioned issues, in this paper, we proposed a Jenks optimization-based scheme to analyze the non-trusted D2D users over the datarate values in the D2D communication system. The threshold value of each natural break in the Jenks algorithm is calculated using the kernel density estimation algorithm. The proposed scheme maximizes the D2D communication system's performance over the sumrate and computation time parameters.
... To mitigate this issue, we considered imperfect CSI at the transmitter. The channel gain between ℎ CMU to the BS is calculated as follows 33 . ...
Device-to-device (D2D) communication offers a low-cost paradigm where two devices in close proximity can communicate without needing a base station (BS). It significantly improves radio resource allocation, channel gain, communication latency, and energy efficiency and offers cooperative communication to enhance the weak user's network coverage. The cellular mobile users (CMUs) share the spectral resources (e.g., power, channel, and spectrum) with D2D mobile users (DMUs), improving spectral efficiency. However, the reuse of radio resources causes various interferences, such as inter and intra-cell interference, that degrade the performance of overall D2D communication. To overcome the aforementioned issues, this paper presents a fusion of AI and coalition game for secure resource allocation in non-orthogonal multiple access (NOMA)-based cooperative D2D communication. Here, NOMA uses the successive interference cancellation (SIC) technique to reduce the severe impact of interference from the D2D systems. Further, we utilized a coalition game theoretic model that efficiently and securely allocates the resources between CMUs and DMUs. However, in the coalition game, all DMUs participate in obtaining resources from CMUs, which increases the computational overhead of the overall system. For that, we employ artificial intelligence (AI) classifiers that bifurcate the DMUs based on their channel quality parameters, such as reference signal received power (RSRP), received signal strength indicator (RSSI), signal-to-noise ratio (SNR), channel quality indicator (CQI). It only forwards the DMUs that have better channel quality parameters into the coalition game, thus reducing the computational overhead of the overall D2D communication. The performance of the proposed scheme is evaluated using various statistical metrics, e.g., precision score, accuracy, recall, F1 score, overall sum rate, and secrecy capacity, where an accuracy of 99.38% is achieved while selecting DMUs for D2D communication.
... Whereas in practical scenarios, multiple eavesdroppers with unknown CSI are present which are mostly hidden. In Ahmed et al. (2019), author assumes multiple eavesdroppers scenario with imperfect CSI in a HetNet consisting of cellular users (CUs) as well as device users (DUs), and achieves resource allocation of D2D along with PL secure transmission and maximum sum rate of both CUs and DUs using coalitional game method, under the constraints of inter-cell and intra-cell interference. ...
Physical layer security (PLS) has proven to be a potential solution for enhancing the security performance of future 5G networks, which promises to fulfill the demands of increasing user traffic. Preventing eavesdroppers from overhearing and stealing useful information in such high traffic environments is as challenging as eliminating them from the network. The goal of this survey is to present a comprehensive study of the latest PLS works proposed to enhance the security performance in different 5G technologies. The survey starts by first giving a detailed introduction and overview of existing surveys that explicitly or partially discuss PLS in 5G and its emerging technologies. Many researchers have presented a number of PLS schemes, using either a separate technology such as Multiple-input-multiple-output (MIMO), Millimeter Wave (mmWave), Radio frequency (RF), Non-orthogonal multiple access (NOMA), Visible light communication (VLC), etc., or a combination of two or more technologies, for securing each field of future 5G networks such as Heterogeneous networks (HetNets), Device-to-Device (D2D), Internet-of-Things (IoT), Cognitive radio network (CRN), Unmanned Aerial Network (UAV), etc. After summarizing the existing surveys, we present a detailed overview on the PLS research works performed till now in HetNets, with respect to its different underlaying technologies, as well as in other emerging 5G technologies. Then, optimization ontology is presented that discusses different security metrics used for measuring PLS performance. Different from rest of the surveys, our survey includes a comprehensive discussion regarding the proposed PLS techniques based on artificial intelligence and machine learning techniques, especially highlighting the works performed using reinforcement learning and deep learning algorithms, allowing us to understand how artificial intelligence can help to achieve better PLS. Towards the end, we discuss numerous challenges being encountered in practical implementation of PLS techniques, and propose different interesting areas that can be opted as future research direction.
... Ahmed et al. [85] addressed the issue of eavesdropping in D2D communications. A joint physical layer security and resource allocation problem is formulated. ...
The 5G network is an emerging field of the research community. 5G is a multi-disciplinary network that aims to support a wide range of services. 5G network has an objective to support a massive number of connected devices. Game theory has an extensive role in wireless network management. Game theory is an approach to analyzing and modeling the system where multiple actors have a role in decision-making with independent objectives and actions. The game theory is an exciting methodology to control the strategic behavior of players and generate an efficient outcome. Coalition game theory can play a crucial role in ensuring cooperation among a massive number of devices. This article provides insight into the current research trends in 5G using coalition games. The work presented in the survey is divided into three categories, namely resource management, interference management, and miscellaneous. This article also provides the foundation about 5G and coalition games highlight the scope of future research.
... In the aforementioned approaches, improvements are not possible without concern about security risks in D2D communications. To mitigate physical layer secure transmission issues in D2D resource allocation, Ahmed et al. [10] proposed a coalitional game approach for spectral resource allocation and enhance system secrecy capacity in multiple eavesdroppers, imperfect CSI, and intra/inter-cell interference scenarios. Their work improved the secrecy rate of cellular users in OFDMbased HCN. ...
Device-to-device (D2D) communication has become a forefront technology to deal with the escalating demand for wireless network traffic. It allows devices in proximity to transmit data directly without the intervention of the base station for both uplink and downlink procedures. Devices in D2D communication can communicate either in underlay or overlay modes. The overlay D2D communication has a dedicated spectrum, hence reduces the interferences and spectral efficiency. In contrast, the underlay mode improves spectral efficiency with resource reuse. It increases the data rate, power control, and energy efficiency, but can experience co-channel and cross-channel interferences. To mitigate these issues, we propose a Heuristic-based optimal resource allocation scheme for the D2D communication network under imperfect channel state information (CSI). Both cellular and D2D users use the orthogonal frequency division multiple access (OFDMA) scheme for uplink and downlink resources. The proposed scheme significantly improves the average network data rate and optimizes the energy of the cellular network.
... , K N } which player can decide to join or leave based on their preference order. There exists a Nash Equilibrium if ρ p (K t ) > ρ p (K t ) ∀ p ∈ N in such a way that no player can deviate from their strategies to increase their payoff ρ p (K t ) [24]. Therefore, K t is a coalition with maximum payoff ρ p after which the players cannot deviate from their strategy {S υ , S Cu } to be in the Nash Equilibrium. ...
This paper proposes a blockchain and coalition game theory-based secure and reliable optimal data pricing scheme for ride sharing. It mainly focuses on securing data sharing between vehicle owners and customers. It employs beyond 5G as a communication network that facilitates vehicle owners and customers with low latency, high throughput, and high availability for communication. We also formulate a coalition game-theory approach to optimize the payoff of vehicle owners and customers by forming coalitions. The performance of the proposed system beyond 5G is estimated by comparing it with 5G and LTE-A networks. The various performance parameters considered are network latency, throughput, and profit for vehicle owners. The performance results show that the proposed system is efficient and beneficial for both vehicle owners and customers in terms of low latency, high throughput, and profit.
... Additionally, we propose a novel multi-device-to-device (MD2D) delivery mode in our previous work [3] to distract the pressures and boost the download speeds, where multiple potential providers deliver contents to a demander in a collaborative way. Moreover, the interference coordination between potential providers and cellular users is well known as the resource management issue and has been widely investigated [4][5][6], which actually consists of power control and radio resource allocation. The former focuses on the process of adjusting power levels for both cellular users and potential providers. ...
In this paper, we investigate the secure content delivery issue for device-to-device networks based on the trust evaluation mechanism and covert communication model. Specifically, in order to stimulate the lasting and rational cooperation among mobile devices, we propose a trust evaluation mechanism, where the trust degree between two mobile devices can be obtained through historical assessed values. Simultaneously, a covert communication model is introduced to guarantee the undetectability of content delivery, which helps to stop malicious wardens adopting some coming external attacks. In this way, the availability and dependability of content sharing, as well the confidentiality and integrity of transmitted contents cam be guaranteed. Then, combining security-aware metrics, in terms of trust degree and covert rate, with physical layer transmission performances, in terms of achievable rate and successful delivery probability, we propose the definition of secrecy-aware effective rate to serve as a guidance on the joint optimization issue of content delivery mode selection and resource management, which is formulated as a social welfare maximization problem. To solve the complex problem tactfully, it is decoupled into two subproblems, i.e., mode selection which is a many-to-one matching problem, and resource management which is a one-to-one matching problem. By analyzing the interaction between two issues, a novel hierarchical stable matching algorithm is proposed to obtain three-dimension stable matching results. Its properties, such as stability, convergence, optimality, and complexity, are theoretically analyzed and proved. Finally, extensive numerical results are provided to demonstrate the advantages of our proposed algorithms.
Unmanned aerial vehicles (UAVs) have attracted much attention for civil and military uses because of their high mobility and adaptable deployment capabilities in open spaces. They facilitate agile communications and ubiquitous connectivity. UAVs benefit from dominant line-of-sight communication links but are more susceptible to adversary eavesdropping attacks. Since upper-layer cryptography methods may be insufficient, physical-layer security (PLS) is an attractive alternative. PLS capitalizes on the inherent randomness of wireless channels to improve information confidentiality, particularly in UAV systems.
This article provides a comprehensive overview of PLS in the context of UAV systems, examining various communication channels, including ground-to-air (G2A), ground-to-ground (G2G), air-to-ground (A2G), and air-to-air (A2A). First, we give a general review of UAV communications, emphasizing its functions as user equipment, base station (BS), and mobile relay. Following that, we provide an overview of PLS and its forms. The survey organizes the most advanced PLS techniques against passive wireless eavesdropping regarding the channels they are designed to protect. These schemes are further categorized into optimization and secrecy performance analysis. We examine technical aspects within each sub-category and classify core contributions based on approaches and objectives to improve secrecy performance. Moreover, we added summary tables of the identified schemes considering optimization and secrecy performance analysis domains for each category, providing an in-depth understanding of their technical aspects. In addition, we discuss open research issues and identify future research directions to address evolving threats and requirements in UAV communications to improve information confidentiality.
Densification of networks through heterogeneous cells deployment is considered a key technology to satisfy the huge traffic growth in future wireless systems. In addition to achieving the required communication capacity and efficiency, another significant challenge arises from the broadcast nature of wireless channels: vulnerability to wiretapping. Physical-layer security is envisaged as an additional level of security to provide confidentiality of radio communications. Typical characteristics of the wireless channel (noise, interference) can be exploited to keep a message confidential from potential eavesdroppers. In particular, heterogeneous networks (HetNet) have inherent security features: while the legitimate user can benefit of the HetNet architecture, the eavesdropper is strongly affected by the inter-cell interference. This paper presents an overview of HetNets intrinsic security benefits, mainly focusing on users association and resource allocation policies. In particular, allocation of radio resources is a poorly investigated topic when related to information security. However, in systems with a large radio resource reuse like HetNets, co-channel interference can be suitably exploited to resist to the eavesdropper. This paper presents a new framework for radio resources allocation using reinforcement learning (Q-learning) to increase the security level in HetNets. A coordinated scheduling among different cells using the same radio resources is proposed based on the exploitation of the spatial information. The goal is to optimize the security at physical layer. The reinforcement learning approach represents a feasible and efficient solution to the proposed problem.
Device‐to‐device (D2D) communication offers a low‐cost paradigm where two devices in close proximity can communicate without needing a base station (BS). It significantly improves radio resource allocation, channel gain, communication latency, and energy efficiency and offers cooperative communication to enhance the weak user's network coverage. The cellular mobile users (CMUs) share the spectral resources (e.g., power, channel, and spectrum) with D2D mobile users (DMUs), improving spectral efficiency. However, the reuse of radio resources causes various interferences, such as intercell and intracell interference, that degrade the performance of overall D2D communication. To overcome the aforementioned issues, this paper presents a fusion of AI and coalition game for secure resource allocation in non‐orthogonal multiple access (NOMA)‐based cooperative D2D communication. Here, NOMA uses the successive interference cancellation (SIC) technique to reduce the severe impact of interference from the D2D systems. Further, we utilized a coalition game theoretic model that efficiently and securely allocates the resources between CMUs and DMUs. However, in the coalition game, all DMUs participate in obtaining resources from CMUs, which increases the computational overhead of the overall system. For that, we employ artificial intelligence (AI) classifiers that bifurcate the DMUs based on their channel quality parameters, such as reference signal received power (RSRP), received signal strength indicator (RSSI), signal‐to‐noise ratio (SNR), and channel quality indicator (CQI). It only forwards the DMUs that have better channel quality parameters into the coalition game, thus reducing the computational overhead of the overall D2D communication. The performance of the proposed scheme is evaluated using various statistical metrics, for example, precision score, accuracy, recall, F1 score, overall sum rate, and secrecy capacity, where an accuracy of 99.38% is achieved while selecting DMUs for D2D communication.
This paper investigates secure computation offloading in device-collaborative mobile edge computing (MEC) networks, where mobile users (MUs) can process a part of their tasks locally and offload the other part to the MEC server or other idle paired MUs. All the transmission links are exposed to a potential eavesdropper. To prevent information leakage, artificial noise (AN) is employed and the secrecy capacity is considered. For such a system, we formulate a weighted latency-energy-aware cost minimization problem by jointly optimizing the subchannel allocation, the offloading proportions, the MUs' transmit powers, the MUs' and the MEC server's CPU frequencies, and the AN power while guaranteeing the secrecy capacities of all transmission links. Since the variables are multi-dimensional and coupled, the formulated problem is challenging to solve with the traditional optimization method. We first propose a swap-matching-based algorithm to achieve the optimal subchannel allocation. We then propose a two-layer asynchronous advantage actor-critic (A3C) algorithm to optimize the rest of the resource variables. Specifically, in the inner layer, by utilizing the Karush-Kuhn-Tucker conditions, we derive the optimal CPU frequency with semi-closed-form expressions. In the outer layer, we propose an A3C-based algorithm to achieve near-optimal solutions with fast convergence speed based on the obtained optimal CPU frequency. Simulation results demonstrate that our proposed scheme can decrease the latency-energy-aware cost compared with other learning-based algorithms.
Device-to-device (D2D) communication is able to enhance the spectrum efficiency and coverage of wireless networks but its transmission secrecy is vulnerable since D2D terminals are usually resource/power constrained. Various existing endeavors propose physical layer security (PLS) means to protect D2D transmissions, under the default prerequisite that D2D transmissions always improve the secrecy performance. In this paper, we show that this assumption/conclusion is invalid. We investigate a so-called cellular transmission mode assisted by the base station (cellular mode) and compare its secrecy performance with that of the D2D direct transmission (D2D mode). In both modes, subject to the secrecy outage probability constraints, we optimize the transceiver parameters, such as the signal power, secrecy rates and transmission thresholds, to maximize the secrecy throughputs. All of the optimal solutions are obtained by closed-form expressions in both modes. Numerical results show that neither of the two transmission modes is always the better but highly depends on the system parameters, such as the locations of nodes, transmit power and secrecy requirements, and consequently provides the answer that D2D communication is not always beneficial for PLS. This immediately suggests that an adaptive switching transmission mode could achieve an enhanced secrecy performance, which is also validated by simulations.
Social Edge Service (SES) is an emerging mechanism in the Social Internet of Things (SIoT) orchestration for effective user-centric reliable communication and computation. The services are affected by active and/or passive attacks such as replay attacks, message tampering because of sharing the same spectrum, as well as inadequate trust measurement methods among intelligent devices (roadside units, mobile edge devices, servers) during computing and content-sharing. These issues lead to computation and communication overhead of servers and computation nodes. To address this issue, we propose the HybridgrAph-Deep-learning (HAD) approach in two stages for secure communication and computation. First, the Adaptive Trust Weight (ATW) model with relation-based feedback fusion analysis to estimate the fitness-priority of every node based on directed graph theory to detect malicious nodes and reduce computation and communication overhead. Second, a Quotient User-centric Coeval-Learning (QUCL) mechanism to formulate secure channel selection, and Nash equilibrium method for optimizing the communication to share data over edge devices. The simulation results confirm that our proposed approach has achieved effective communication and computation performance, and enhanced Social Edge Services (SES) reliability than state-of-the-art approaches.
Device-to-device (D2D) is a fifth-generation (5G) network's key technology, which allows devices in proximity to communicate one-to-one without a base station (BS). Moreover, it ameliorates channel gain, communication latency, energy efficiency, and spectral efficiency. However, mitigating interference (D2D and cellular mobile users (CMUs)) and eavesdropper effect (at D2D links) is a prime concern in D2D communication. These issues can be resolved with an efficient allocation of radio resources. Cognitive radio (CR) and non-orthogonal multiple access (NOMA) are viable solutions to resolve the aforementioned issues. Motivated by the aforementioned discussion, in this paper, we propose a joint CR and NOMA-based scheme, i.e., SARAS for secure resource allocation in D2D communication. It aims to maximize the overall sum rate and secrecy capacity of D2D users with assured quality of service (QoS) and quality of experience (QoE). CR is used for pairing between strong and weak D2D users (i.e., D2D pair) and NOMA's successive interference cancellation (SIC) technique helps to reduce the interference effect between cellular and D2D users. We used a coalition game for efficient resource utilization, which transfers D2D users from one coalition to another based on the preference order and channel conditions. This landed D2D users in the best coalition having favorable channel conditions. We have executed the proposed SARAS scheme over the MAT-LAB simulation tool, considering a varying number of D2D and CMUs. Simulation results show that the proposed scheme outperforms the traditional OFDMA, random, and nearest approaches concerning parameters such as sum rate and secrecy capacity.
In this paper, we propose a cognitive radio (CR)-based secure resource allocation scheme for device-to-device (D2D) communication networks. It aims to minimize the interference effect with the proper pairing of strong and weak D2D users by sensing the available spectrum of the cellular user (CU's). It maximizes the total sum rate of D2D users with great quality of service and quality of experience. Further, to improve the secrecy capacity of the proposed scheme, we formulate a coalition game. It has a preference order (decides upon the channel conditions) and based on that it moves D2D users from one coalition to another. This landed Finally, it shift D2D users to the superlative coalition having conducive channel conditions. We then evaluate the proposed scheme considering parameters such as total sum rate, sum secrecy capacity, and average secrecy capacity. It is observed from graphs that the proposed scheme outperforms the traditional without CR, first-order algorithm (FOA), and nearest first approaches.
Software-Defined Internet of Vehicles (SD-IoV) is an emerging technology which is being used in modern intelligent transportation systems (ITS). The ultimate goal of SD-IoV is to provide seamless connectivity to the end-users with low latency and high-speed data transfer. However, due to the increase in the density of the connected IoV using an open channel, i.e., the Internet, the foremost challenges of high power consumption and secure data transfer are inevitable in such an environment. An external eavesdropper may intercept the transmitted message to access the legitimate information over the public channel, i.e., the Internet. Most of the solutions reported in the literature to tackle these issues may not be applicable in SD-IoV environment due to high computation and communication costs. Motivated from this, in this paper, the problems of high power consumption and secure data transfer in SD-IoV are formulated using a mixed-integer non-linear programming (MINLP) with associated constraints. To solve the aforementioned problem, we propose a joint power optimization and secrecy ensured scheme known as SecGreen. SecGreen has an efficient-energy harvesting algorithm using simultaneous wireless information and power transfer (SWIPT) to maximize the energy-efficiency.
Device-to-device communication (D2D) is a promising technology of fifth-generation (5G) networks with an aim to maximize spectral efficiency. It permits direct communication between the mobile devices if they are in proximity by ignoring the base station. Despite improving spectral efficiency, it also improves the system data rate, minimizes the communication latency, and reduces the burden on the base station (for data uplink and downlink). The existing communication majorly focused on orthogonal multiple access (OMA), which serves one user at a time for spectrum sharing. To improve the spectral efficiency non-orthogonal multiple access (NOMA) schemes can be employed which serve multiple users at a time for spectrum sharing. NOMA drastically improves the spectrum sharing, but the devices can cause more interference that degrades overall the network performance. But, successive interference cancellation (SIC) of NOMA mitigates the interference issues and improves the system's signal to interference noise ratio (SINR). Further, the sum rate and secrecy capacity of the system can be improved with a matching-based algorithm for optimal power allocation. This improves the overall sum rate, which further improves the system's secrecy capacity against the number of eavesdroppers. Finally, the performance, i.e., overall sum rate and average secrecy capacity of the proposed system is evaluated by considering varying numbers of cellular users, D2D groups, and eavesdroppers.
Integration of Device-to-Device communication in 5G Heterogeneous networks (HetNets) promises to increase resource utilization and spectrum efficiency (SE). However, the broadcast nature of wireless communication makes it vulnerable to an eavesdropper, who can steal useful information from the transmission channel. Hence, ensuring secure communication for both cellular users (CUs) and D2D pairs is the need of the time. In this paper, we study the optimization problem of resource allocation in 5G and beyond wireless networks to maximize the secrecy rate of both CUs and D2D links from the physical layer security perspective. We consider multiple eavesdroppers overhearing the CUs and D2D pairs. Two optimization problems are formulated: one considering separate channels for CUs and D2D user (DU), and second, considering the shared channel between CU and DU. The nature of the formulated problems is mixed-integer non-linear programming (MINLP) problem and to solve it, we propose an ϵ-optimal based successive linearization algorithm. This algorithm decomposes our original problem into finite sub-problem branches and solves each separately. Simulation results show that the proposed technique can significantly improve the secrecy rate, throughput, and energy efficiency of the network especially in the case of separate channels for CUs and DUs.
The distributed and heterogeneous framework in 5G heterogeneous networks (HetNet) makes it vulnerable to attacks of different kinds. Nodes for improving the network security are therefore important to eliminate such critical threats. Without cooperation or with limited cooperation, these nodes are substantially restricted in their protecting capacity due to specific characteristics such as heterogeneity, hierarchy and wide range in 5G HetNet. In this paper, we propose a federated learning empowered end-edge-cloud cooperation based framework for enhancing 5G HetNet security. In this framework, the nodes equipped with attack detection mechanisms are distributed in the end, edge and cloud of the 5G HetNet. We then design cooperative training schemes to realise the full potential of these nodes in detecting attacks. Illustrative results demonstrate the superior performance of our proposed scheme compared to three different benchmark schemes.
As the Internet of Things (IoT) is maturing and acquires its social flavor, the Social IoT enables smart devices to build inter-thing social networks without human intervention. As a new form of smart devices, unmanned aerial vehicles (UAVs) are finding their way into IoT applications. The integrated Social Internet of Flying Things (SIoFT) can provide the socialaware UAV-assisted services. However, the broadcast nature of air-to-ground (A2G) channels makes them vulnerable to being eavesdropped by terrestrial malicious users due to their strong line-of-sight (LoS) links. In this paper, we investigate to ensure the security of A2G communications when the location information of multiple potential eavesdroppers cannot be perfectly estimated. Following the “no pain no gain” principle, the terrestrial users who reuse the UAV cellular spectrum will act as friendly jammers to realize “win-win” situation. Hence, joint trajectory design, power control, and channel allocation optimization problem is formulated to maximize the average secrecy rate of UAVs in worst case. In the first stage, we utilize the block coordinate descent method and successive convex optimization method to solve the trajectory design and power control problems in an iterative manner. In the second stage, we convert the user pairing problem into a popular matching problem with externalities. Two distributed algorithms are proposed to maintain the popular matching under dynamics. Moreover, we conduct detailed analysis of the popularity, convergence, and computational complexity. Simulation results demonstrate the superiority of our proposed method in terms of different performance metrics.
Security is a critical element to the existing Internet of Things (IoT) deployment, where any user may actively or passively attack the content sharing of others reusing the same channel. As most smart devices are carried by human, we may leverage their owners' social trust to avoid being intercepted by untrusted users, which conforms to the Social Internet of Things (SIoT) paradigm. In this paper, we propose a secure content sharing (SCS) scheme to strike the trade-off between security and quality of experience (QoE) by exploring the social trust. Firstly, to dynamically extract the social trust, the random walk strategy is employed for prediction based on the proposed “User-Content-Social Group" graph which models users' preference over time. Given the social trust value, we propose a hierarchical game model to decouple the optimization problem into two sub-problems: user pairing and channel selection. More specifically, the user pairing sub-problem is formulated as a matching sub-game with peer effect, and the embedded rotation-swap matching algorithm can accommodate the dynamics caused by mutual interference. The second sub-problem can be formulated as a secure channel selection sub-game with the directed hypergraph being game space, which is proved to be an exact potential game. Then, we design an uncoupled-user concurrent learning algorithm (UUCL) to search for the optimal pure Nash equilibrium, and thereby the global optimum of this sub-game is achieved. Finally, simulation results generated on realistic social dataset verify that our proposed scheme can notably enhance the security without sacrificing users' QoE.
In this paper, we concentrate on the robust multiobjective optimization (MOO) for the tradeoff between energy efficiency (EE) and spectral efficiency (SE) in device-to-device (D2D) communications underlaying heterogeneous networks (HetNets). Different from traditional resource optimization, we focus on finding robust Pareto optimal solutions for spectrum allocation and power coordination in D2D communications underlaying HetNets with the consideration of interference channel uncertainties. The problem is formulated as an uncertain MOO problem to maximize EE and SE of cellular users (CUs) simultaneously while guaranteeing the minimum rate requirements of both CUs and D2D pairs.With the aid of "-constraint method and strict robustness, we propose a general framework to transform the uncertain MOO problem into a deterministic single-objective optimization problem. As exponential computational complexity is required to solve this highly non-convex problem, the power coordination and the spectrum allocation problems are solved separately, and an effective two-stage iterative algorithm is developed. Finally, simulation results validate that our proposed robust scheme converges fast and significantly outperforms the non-robust scheme in terms of the effective EE-SE tradeoff and the quality of service satisfying probability of D2D pairs.
Device-to-Device (D2D) communications underlying the cellular infrastructure is a technology that has been proposed recently as a promising solution to enhance cellular network capabilities. It improves spectrum utilization, overall throughput and energy efficiency while enabling new peer-to-peer and location-based applications and services. However, interference is the major challenge since the same resources are shared by both systems. Therefore, interference management techniques are required to keep the interference under control. In this work, in order to mitigate interference, we consider centralized and distributed power control algorithms in a one-cell random network model. Existing results on D2D underlay networks assume perfect channel state information (CSI). This assumption is usually unrealistic in practice due to the dynamic nature of wireless channels. Thus, it is of great interest to study and evaluate achievable performances under channel uncertainty. Differently from previous works, we are assuming that the CSI may be imperfect and include estimation errors. In the centralized approach, we derive the optimal powers that maximize the coverage probability and the rate of the cellular user while scheduling as many D2D links as possible. These powers are computed at the base station (BS) and then delivered to the users, and hence the name “centralized". For the distributed method, the on-off power control and the truncated channel inversion are proposed. Expressions of coverage probabilities are established in function of D2D links intensity, pathloss exponent and estimation error variance. Results show the important influence of CSI error on achievable performances and thus how crucial it is to consider it while designing networks and evaluating performances.
The ever-increasing demands for local area services underlaying cellular networks benefit from direct device-to-device (D2D) communications, where an efficient scheme for resource allocation is needed to increase the system capacity as the result of interference caused by spectrum sharing. Current works mainly focus on maximizing the overall transmission capacity according to interference constraints of the physical domain. However, D2D users in the social domain form different social communities, and each social community is likely to improve its own group's data transmission cooperatively without considering other communities. Therefore, social relationships among mobile users influence the strategy of the resource allocations for the D2D communications. In this paper, we first introduce social relationships in the continuum space into the resource allocation for D2D communications, which consider the complex social connections in the social domain. Then a social group utility maximization game is formulated to maximize the social group utility of each D2D user, which quantitatively measures the joint performance of social and physical domains. We theoretically investigate the Nash Equilibrium of our proposed game and further propose a distributed algorithm based on the switch operations of the resource allocation vector. Numerical results demonstrate that our proposed solution increases the utility of overall social groups about 45% on average without loss of the fairness compared with other state-of-the-art schemes.
This paper is motivated to examine the security vulnerabilities and threats
imposed by the inherent open nature of wireless communications and to devise
efficient defense mechanisms for improving the wireless network security. We
first summarize the security requirements of wireless networks, including their
authenticity, confidentiality, integrity and availability issues. Next, a
comprehensive overview of security attacks encountered in wireless networks is
presented in view of the network protocol architecture, where the potential
security threats are discussed at each protocol layer. We also provide a survey
of the existing security protocols and algorithms that are adopted in the
existing wireless network standards, such as the Bluetooth, Wi-Fi, WiMAX, and
the long-term evolution (LTE) systems. Then, we discuss the state-of-the-art in
physical-layer security, which is an emerging technique of securing the open
communications environment against eavesdropping attacks at the physical layer.
Several physical-layer security techniques are reviewed and compared, including
information-theoretic security, artificial noise aided security,
security-oriented beamforming, diversity assisted security, and physical-layer
key generation approaches. Additionally, since a jammer emitting radio signals
can readily interfere with the legitimate wireless users, we introduce the
family of various jamming attacks and their counter-measures, including the
constant jammer, intermittent jammer, reactive jammer, adaptive jammer and
intelligent jammer. Finally, some technical challenges which remain unresolved
at the time of writing are summarized and the future trends in wireless
security are discussed.
Device-to-device (D2D) communications underlaying a cellular infrastructure has been proposed as a means of taking advantage of the physical proximity of communicating devices, increasing resource utilization, and improving cellular coverage. Relative to the traditional cellular methods, there is a need to design new peer discovery methods, physical layer procedures, and radio resource management algorithms that help realize the potential advantages of D2D communications. In this article we use the 3GPP Long Term Evolution system as a baseline for D2D design, review some of the key design challenges, and propose solution approaches that allow cellular devices and D2D pairs to share spectrum resources and thereby increase the spectrum and energy efficiency of traditional cellular networks. Simulation results illustrate the viability of the proposed design.
In this tutorial, we provided a comprehensive overview of coalitional game theory, and its usage in wireless and communication networks. For this purpose, we introduced a novel classification of coalitional games by grouping the sparse literature into three distinct classes of games: canonical coalitional games, coalition formation games, and coalitional graph games. For each class, we explained in details the fundamental properties, discussed the main solution concepts, and provided an in-depth analysis of the methodologies and approaches for using these games in both game theory and communication applications. The presented applications have been carefully selected from a broad range of areas spanning a diverse number of research problems. The tutorial also sheds light on future opportunities for using the strong analytical tool of coalitional games in a number of applications. In a nutshell, this article fills a void in existing communications literature, by providing a novel tutorial on applying coalitional game theory in communication networks through comprehensive theory and technical details as well as through practical examples drawn from both game theory and communication application.
In this paper, we consider a two-way relay network where two sources can
communicate only through an untrusted intermediate relay, and investigate the
physical layer security issue of this two-way relay scenario. Specifically, we
treat the intermediate relay as an eavesdropper from which the information
transmitted by the sources needs to be kept secret, despite the fact that its
cooperation in relaying this information is essential. We indicate that a
non-zero secrecy rate is indeed achievable in this two-way relay network even
without external friendly jammers. As for the system with friendly jammers,
after further analysis, we can obtain that the secrecy rate of the sources can
be effectively improved by utilizing proper jamming power from the friendly
jammers. Then, we formulate a Stackelberg game model between the sources and
the friendly jammers as a power control scheme to achieve the optimized secrecy
rate of the sources, in which the sources are treated as the sole buyer and the
friendly jammers are the sellers. In addition, the optimal solutions of the
jamming power and the asking prices are given and a distributed updating
algorithm to obtain the Stakelberg equilibrium is provided for the proposed
game. Finally, the simulations results verify the properties and the efficiency
of the proposed Stackelberg game based scheme.
In this paper, we investigate joint relay and jammer selection in two-way
cooperative networks, consisting of two sources, a number of intermediate
nodes, and one eavesdropper, with the constraints of physical layer security.
Specifically, the proposed algorithms select two or three intermediate nodes to
enhance security against the malicious eavesdropper. The first selected node
operates in the conventional relay mode and assists the sources to deliver
their data to the corresponding destinations using an amplify-and-forward
protocol. The second and third nodes are used in different communication phases
as jammers in order to create intentional interference upon the eavesdropper
node. Firstly, we find that in a topology where the intermediate nodes are
randomly and sparsely distributed, the proposed schemes with cooperative
jamming outperform the conventional non-jamming schemes within a certain
transmitted power regime. We also find that, in the scenario in which the
intermediate nodes gather as a close cluster, the jamming schemes may be less
effective than their non-jamming counterparts. Therefore, we introduce a hybrid
scheme to switch between jamming and non-jamming modes. Simulation results
validate our theoretical analysis and show that the hybrid switching scheme
further improves the secrecy rate.
Device-to-device (D2D) communication is continuously
evolving and engulfing a wide diversity of proximate
services and applications, which is considered as one of the key
technologies in the 5G ecosystem. It is argued that direct communications
paradigm advantages may not be entirely captured
without embracing the concepts of the social-domain. Following
the explosion of social networks and smart mobile devices,
social-interactions among mobile users enable the promotion of
D2D co-operations. In this article, we first present a systematic
overview of the socially-unaware technical challenges and the
prospective applications to consolidate a background on D2D
communications. Next, all the social features utilized in tackling
and improving the technical issues and the applications are
briefed, respectively. Then, we provide a comprehensive survey
on socially-aware D2D communications, where various features
of social-domain are leveraged such as ties, community, trust,
and selfishness to tackle the D2D technical issues and improve
the performance of prospective D2D applications. We categorize
state of the art socially-aware D2D communications into two main
sections. The first section considers technical issues, while the
second section pertains to their applications to provide insightful
information and motivate more in-depth studies in this area.
For each aforementioned section, we overview technical aspects
and classify the core contributions based on approaches used
and the social features utilized. In the discussion section, we
summarize the socially-aware D2D communications and present
lessons learned. Finally, we highlight the open research challenges
in this field and predict future research trends.
With the popularity of proximity-based services, device-to-device (D2D) communication underlaying cellular networks is a promising technology to cope with the growing demands by improving network resource utilization. However, wireless communication’s broadcast nature is vulnerable to eavesdropping, thus, ensuring secrecy communication for both cellular user equipments (CUEs) and D2D pairs in an underlay network is a challenging issue. We investigate the problem of physical-layer secure transmission jointly with resource allocation in D2D communications. Different from existing works, we framed overlapping (partial) coalitional game where each D2D pair can access multiple CUEs’ spectral resources. Moreover, multiple D2D pairs can share single CUE subchannel in multiple eavesdroppers scenario to ensure information security for both CUEs and D2D pairs, and to maximize system sum-rate in socially-aware D2D network. We incorporate mutual interference and propose different transmission modes for secrecy ensured resource allocation based overlapping coalition formation scheme with transferable utility to obtain a final stable partition. We further prove the proposed algorithm stability, convergence and computational complexity. Both analytical and numerical results demonstrate the effectiveness of our proposed scheme, which ensures system-wide security and at the same time improves the performance by maximizing the system sum-rate. IEEE
In this paper, we propose a device to device (D2D) communication scenario underlaying a cellular network where both D2D and cellular users (CUs) are discrete power-rate systems with limited feedback from the receivers. It is assumed that there exists an adversary which wants to eavesdrop on the information transmission from the base station (BS) to CUs. Since D2D communication shares the same spectrum with cellular network, cross interference must be considered. However, when secrecy capacity is considered, the interference caused by D2D communication can help to improve the secrecy communications by confusing the eavesdroppers. Since both systems share the same spectrum, cross interference must be considered. We formulate the proposed resource allocation into an optimization problem whose objective is to maximize the average transmission rate of D2D pair in the presence of the cellular communications under average transmission power constraint. For the cellular network, we require a minimum average achievable secrecy rate in the absence of D2D communication as well as a maximum secrecy outage probability in the presence of D2D communication which should be satisfied. Due to high complexity convex optimization methods, to solve the proposed optimization problem, we apply Particle Swarm Optimization (PSO) which is an evolutionary approach. Moreover, we model and study the error in the feedback channel and the imperfectness of channel distribution information (CDI) using parametric and nonparametric methods. Finally, the impact of different system parameters on the performance of the proposed scheme is investigated through simulations. The performance of the proposed scheme is evaluated using numerical results for different scenarios.
Device-to-device (D2D) communications has gradually become a promising technique to support wireless peerto- peer services and enhance the overall spectrum utilization. In the mean time, the full-duplex communication technique has also attracted significant research interest recently. In this paper, we for the first time employ the D2D communication concept in a full-duplex cellular network. In such a scenario, the user equipments (UEs) are allowed to communicate between each other by reusing the spectrum resources of cellular uplinks and downlinks. However, this D2D underlaying full-duplex cellular scenario poses a new challenge for interference management. The complicated UE-to-UE interference among cellular links and D2D links self-interference at the base station (BS) can critically affect the network performance. Therefore, we investigate the joint resource block (RB) assignment and transmit power allocation problem, in order to optimize the network performance and spectrum utilization. Furthermore, we use graph theory to model the investigated scenario, and propose a novel graph coloring based resource sharing (GCRS) scheme to solve the joint optimization problem effectively with acceptable complexity. The performance of our scheme is evaluated through Monte-Carlo simulations.
Abstract:
Device-to-Device (D2D) communication presents a new paradigm in mobile networking to facilitate data exchange between physically proximate devices. The development of D2D is driven by mobile operators to harvest short range communications for improving network performance and supporting proximity-based services. In this article, we investigate two fundamental and interrelated aspects of D2D communication, security and privacy, which are essential for the adoption and deployment of D2D. We present an extensive review of the stateof- the-art solutions for enhancing security and privacy in D2D communication. By summarizing the challenges, requirements, and features of different proposals, we identify lessons to be learned from existing studies and derive a set of “best practices”. The primary goal of our work is to equip researchers and developers with a better understanding of the underlying problems and the potential solutions for D2D security and privacy. To inspire follow-up research, we identify open problems and highlight future directions with regard to system and communication design. To the best of our knowledge, this is the first comprehensive review to address the fundamental security and privacy issues in D2D communication.
In this letter, the issue of security for device-todevice (D2D) underlaying cellular networks is considered. The cellular communication is overheard by randomly distributed eavesdroppers. By sharing the spectrum between D2D users and cellular users, the interference generated by D2D users is used as a source of jamming to confuse the eavesdroppers. We first derive the connection probability of the D2D links and the secrecy outage probability of the cellular link based on stochastic geometry tools. We then propose a joint guard zone and thresholdbased access control scheme for the D2D users to maximize the achievable secrecy throughput. Moreover, when only the selection threshold is considered, a closed-form expression of the optimal selection threshold is derived. Simulation results show that improved secrecy throughput can be achieved by allowing the transmission of the D2D users.
The implementation of device-to-device (D2D) underlaying or overlaying pre-existing cellular networks has received much attention due to the potential of enhancing the total cell throughput, reducing power consumption and increasing the instantaneous data rate.
In this paper we propose a distributed power allocation scheme for D2D OFDMA communications and, in particular, we consider the two operating modes amenable to a distributed implementation: dedicated and reuse modes. The proposed schemes address the problem of maximizing the users' sum rate subject to power constraints, which is known to be nonconvex and, as such, extremely difficult to be solved exactly. We propose here a fresh approach to this well-known problem, capitalizing on the fact that the power allocation problem can be modeled as a potential game. Exploiting the potential games property of converging under better response dynamics, we propose two fully distributed iterative algorithms, one for each operation mode considered, where each user updates sequentially and autonomously its power allocation.
Numerical results, computed for several different user scenarios, show that the proposed methods, which converge to one of the local maxima of the objective function, exhibit performance close to the maximum achievable optimum and outperform other schemes presented in the literature.
In this paper, we investigate the cooperation issue via spectrum sharing when employing physical layer security concept into the device-to-device (D2D) communications underlaying cellular networks. First, we derive the optimal joint power control solutions of the cellular communication links and D2D pairs in terms of the secrecy capacity under a simple cooperation case and further propose a secrecy-based access control scheme with the best D2D pair selection mechanism. Then, we consider a more general case that multiple D2D pairs can access the same resource block (RB) and one D2D pair is also permitted to access multiple RBs, and provide a novel cooperation mechanism in the investigated network. Furthermore, we formulate the provided cooperation mechanism among cellular communication links and D2D pairs as a coalitional game. Then, based on a newly defined max-coalition order in the constructed game, we further propose a merge-and-split-based coalition formation algorithm for cellular communication links and D2D pairs to achieve efficient and effective cooperation, leading to improved system secrecy rate and social welfare. Simulation results indicate the efficiency of the proposed secrecy-based access control scheme and the proposed merge-and-split-based coalition formation algorithm.
Device-to-device (D2D) communications have recently attracted much attention for the potential capability to improve spectral efficiency (SE) underlaying the existing heterogeneous networks (HetNets). Due to no sophisticated control, D2D-worked user equipments (DUEs) themselves cannot resist eavesdropping or security attacks. It is urgent to maximize the secure capacity for both cellular users and DUEs. This paper formulates the radio resource-allocation problem to maximize the secure capacity of DUEs for D2D communication underlaying HetNets, which consist of high-power nodes (HPNs) and low-power nodes (LPNs). The optimization objective function with transmit bit rate and power constraints, which is nonconvex and hard to directly derive, is first transformed into a matrix form. Then, the equivalent convex form of the optimization problem is derived according to Perron-Frobenius theory. A heuristic iterative algorithm based on the proximal theory is proposed to solve this equivalent convex problem through evaluating the proximal operator of the Lagrange function. Numerical results show that the proposed radio resource-allocation solution significantly improves the secure capacity with a fast convergence speed.
Introduction Cooperation among wireless nodes has attracted significant attention as a novel networking paradigm for future wireless cellular networks. It has been demonstrated that, by using cooperation at different layers (physical layer, multiple access channel (MAC) layer, network layer), the performance of wireless systems such as cellular networks can be significantly improved. In fact, cooperation can yield significant performance improvement in terms of reduced bit error rate (BER), improved throughput, efficient packet forwarding, reduced energy, and so on. In order to reap the benefits of cooperation, efficient and distributed cooperation strategies must be devised in future wireless networks. Designing such cooperation protocols encounters many challenges. On the one hand, any cooperation algorithm must take into account not only the gains but also the costs from cooperation which can both be challenging to model. On the other hand, the wireless network users tend to be selfish in nature and aim at improving their own performance. Therefore, giving incentives for these users to cooperate is another major challenge. Hence, there is a strong need to design cooperative strategies that can be implemented by the wireless nodes, in a distributed manner, while taking into account the selfish goals of each user as well as all the gains and losses from this cooperation. This chapter describes analytical tools from game theory that can be used to model the cooperative behavior in wireless cellular networks.
Device-To-device (D2D) communication has been proposed as a promising technology for future cellular communication systems due to its advantages of high spectrum efficiency, low energy consumption, and enhanced system capacity. Resource allocation for D2D communications, which occupies nonorthogonal channels with cellular transmissions, is an important problem in terms of achieving the aforementioned benefits. In this problem, there are two fundamental challenges to be addressed: 1) how to emulate cellular users to share their resources and 2) how to efficiently allocate resources in terms of channels for D2D pairs. In this paper, we exploit social ties in human-formed social networks to enhance D2D resource sharing and further propose a social-community-Aware D2D resource allocation framework, where cellular users would like to share their channels with D2D communications in the same community formed by a group of people with close social ties. After that, we propose a two-step coalition game, where a coalition formulation is established for communities, and an optimal resource allocation problem is formulated for D2D pairs. Extensive simulations on random networks and real mobile trace verify the effectiveness of the proposed scheme.
Device-to-device (D2D) communications underlaying cellular networks have been recently considered as a promising means to enhance resource utilization of the cellular network and local user throughput among devices in proximity to each other. In this paper, we investigate the joint resource block assignment and transmit power allocation problem to optimize the network performance in such a scenario. Specifically, we model the interference relationships among different D2D and cellular communication links as a novel interference graph with unique attributes and propose a corresponding joint resource-allocation scheme that can effectively lead to a near-optimal solution at the base station, with low computational complexity. Simulation results confirm that, with markedly reduced complexity, our proposed scheme achieves a network throughput that approaches the one corresponding to the optimal resource-sharing scheme obtained via exhaustive search.
Intelligent transportation systems (ITS) are becoming a crucial component of our society, whereas reliable and efficient vehicular communications consist of a key enabler of a well-functioning ITS. To meet a wide variety of ITS application needs, vehicular-to-vehicular and vehicular-to-infrastructure communications have to be jointly considered, configured, and optimized. The effective and efficient coexistence and cooperation of the two give rise to a dynamic spectrum management problem. One recently emerged and rapidly adopted solution of a similar problem in cellular networks is the so-termed device-to-device (D2D) communications. Its potential in the vehicular scenarios with unique challenges, however, has not been thoroughly investigated to date. In this paper, we for the first time carry out a feasibility study of D2D for ITS based on both the features of D2D and the nature of vehicular networks. In addition to demonstrating the promising potential of this technology, we will also propose novel remedies necessary to make D2D technology practical as well as beneficial for ITS.
Device-to-device (D2D) communication underlaying cellular networks is a promising technology to improve network resource utilization. In D2D-enabled cellular networks, interference generated by D2D communications is usually viewed as an obstacle to cellular communications. However, in this paper, we present a new perspective on the role of D2D interference by taking security issues into consideration. We consider a large-scale D2D-enabled cellular network with eavesdroppers overhearing cellular communications. Using stochastic geometry, we model such a network and analyze the signal-to-interference-plus-noise ratio (SINR) distributions, connection probabilities and secrecy probabilities of both the cellular and D2D links. We propose two criteria for guaranteeing performances of secure cellular communications, namely the strong and weak performance guarantee criteria. Based on the obtained analytical results of link characteristics, we design optimal D2D link scheduling schemes under these two criteria respectively. Both analytical and numerical results show that the interference from D2D communications can enhance physical layer security of cellular communications and at the same time create extra transmission opportunities for D2D users.
Device-to-Device (D2D) communications have been proposed recently to improve the spectral efficiency. In this paper, we consider physical-layer security in D2D communication as an underlay to cellular networks with an eavesdropper. Benefiting from the underlaid spectrum reuse, D2D users can contribute to the system secrecy capacity, while D2D users may interfere the cellular users and decrease their secrecy capacity. We formulate this problem as a matching problem in the weighted bipartite graph and introduce the Kuhn-Munkres (KM) algorithm to provide the optimal solution. Simulation results show that the system secrecy capacity can be greatly improved by introducing D2D communications underlaying cellular networks.
With emerging demands for local area services, device-to-device communication is conceived as a vital component for the next-generation cellular networks to improve spectral reuse, bring hop gains, and enhance system capacity. Ripening these benefits depends on efficiently solving several main technical problems, including mode selection, resource allocation, and interference management. Aiming to establish a new paradigm for solving these challenging problems in D2D communication, in this article we propose a social-aware enhanced D2D communication architecture that exploits social networking characteristics for system design. By developing a profound understanding of the interplay between social networks' properties and mobile communication problems, we qualitatively analyze how D2D communications can benefit from social features, and quantitatively assess the achievable gains in a social-aware D2D communication system.
Thanks to the convergence of pervasive mobile communications and fast-growing online social networking, mobile social networking is penetrating into our everyday life. Aiming to develop a systematic understanding of the interplay between social structure and mobile communications, in this paper we exploit social ties in human social networks to enhance cooperative device-to-device communications. Specifically, as hand-held devices are carried by human beings, we leverage two key social phenomena, namely social trust and social reciprocity, to promote efficient cooperation among devices. With this insight, we develop a coalitional game theoretic framework to devise social-tie based cooperation strategies for device-to-device communications. We also develop a network assisted relay selection mechanism to implement the coalitional game solution, and show that the mechanism is immune to group deviations, individually rational, and truthful. We evaluate the performance of the mechanism by using real social data traces. Numerical results show that the proposed mechanism can achieve up-to 122% performance gain over the case without D2D cooperation.
Blowfish, a new secret-key block cipher, is proposed. It is a Feistel network, iterating a simple encryption function 16 times. The block size is 64 bits, and the key can be any length up to 448 bits. Although there is a complex initialization phase required before any encryption can take place, the actual encryption of data is very efficient on large microprocessors.
In this paper, we investigate joint relay and jammer selection in two-way cooperative networks, consisting of two sources, a number of intermediate nodes, and one eavesdropper, with secrecy constraints. Specifically, the proposed algorithms select two or three intermediate nodes to enhance security against the malicious eavesdropper. The first selected node operates in the conventional relay mode and assists the sources to deliver their data to the corresponding destinations via the amplify-and-forward protocol. The second and third nodes are used in different communication phases as jammers in order to create intentional interference upon the eavesdropper node. Firstly, we find that in a topology where the relay and jamming nodes are randomly and sparsely distributed, the proposed schemes with cooperative jamming outperforms the conventional non-jamming schemes within a certain transmitted power regime. We also find that, in the scenario in which the intermediate nodes gather as a close cluster, the jamming schemes may be less effective than their non-jamming counterparts. Therefore, we introduce a hybrid scheme to switch between jamming and non-jamming modes. Simulation results validate our theoretical analysis that the hybrid switching scheme further improves the secrecy rate.
Generating a shared key between two parties from the wireless channel is of increasing interest. The procedure for obtaining information from wireless channel is called channel probing. Previous works used a constant channel probing rate to generate a key, but they neither consider the tradeoff between the bit generation rate (BGR) and channel resource consumption, nor adjust the probing rate according to different scenarios. In order to satisfy users' requirement for BGR and to use the wireless channel efficiently, we first build a mathematical model of channel probing and derive the relationship between BGR and probing rate. Second, we introduce an adaptive channel probing system based on Lempel-Ziv complexity (LZ76) and Proportional-Integral-Derivative (PID) controller. Our scheme uses LZ76 to estimate the entropy rate of the channel statistics, e.g. the Received Signal Strength (RSS), and uses the PID controller to control the channel probing rate. Our experiments show that this system is able to dynamically adjust its probing rate to achieve a desired BGR under different moving speeds, different mobile types, and different sites. Our results also show that the standard deviation of the LZ76 calculator is less than 0.15 bits/s. The PID controller is able to stabilize the bit generation rate at a desired value with mean error of less than 0.9 bits/s.
We consider the partitioning of a society into coalitions in purely hedonic settings, i.e., where each player's payoff is completely determined by the identity of other members of her coalition. We first discuss how hedonic and nonhedonic settings differ and some sufficient conditions for the existence of core stable coalition partitions in hedonic settings. We then focus on a weaker stability condition: individual stability, where no player can benefit from moving to another coalition while not hurting the members of that new coalition. We show that if coalitions can be ordered according to some characteristic over which players have single-peaked preferences, or where players have symmetric and additively separable preferences, then there exists an individually stable coalition partition. Examples show that without these conditions, individually stable coalition partitions may not exist. We also discuss some other stability concepts, and the incompatibility of stability with other normative properties. Journal of Economic Literature Classification Numbers: C71, A14, D20.
Blowfish, a new secret-key block cipher, is proposed. It is a Feistel network, iterating a simple encryption function 16 times. The block size is 64 bits, and the key can be any length up to 448 bits. Although there is a complex initialization phase required before any encryption can take place, the actual encryption of data is very efficient on large microprocessors. The cryptographic community needs to provide the world with a new encryption standard. DES (16), the workhorse encryption algorithm for the past fifteen years, is nearing the end of its useful life. Its 56-bit key size is vulnerable to a brute-force attack (22), and recent advances in differential cryptanalysis (1) and linear cryptanalysis (10) indicate that DES is vulnerable to other attacks as well. Many of the other unbroken algorithms in the literature--Khufu (11,12), REDOC II (2,23, 20), and IDEA (7,8,9)--are protected by patents. RC2 and RC4, approved for export with a small key size, are proprietary (18). GOST (6), a Soviet government algorithm, is specified without the S-boxes. The U.S. government is moving towards secret algorithms, such as the Skipjack algorithm in the Clipper and Capstone chips (17). If the world is to have a secure, unpatented, and freely- available encryption algorithm by the turn of the century, we need to develop several candidate encryption algorithms now. These algorithms can then be subjected to years of public scrutiny and cryptanalysis. Then, the hope is that one or more candidate algorithms will survive this process, and can eventually become a new standard. This paper discusses the requirements for a standard encryption algorithm. While it may not be possible to satisfy all requirements with a single algorithm, it may be possible to satisfy them with a family of algorithms based on the same cryptographic principles.
THE problems of cryptography and secrecy systems furnish an interesting application of communication theory.1 In this paper a theory of secrecy systems is developed. The approach is on a theoretical level and is intended to complement the treatment found in standard works on cryptography.2 There, a detailed study is made of the many standard types of codes and ciphers, and of the ways of breaking them. We will be more concerned with the general mathematical structure and properties of secrecy systems.
Adaptive wireless channel probing for shared key generation
- Y Wei
- K Zengy
- P Mohapatra