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Fronthaul data compression for Uplink CoMP in cloud radio access network (C-RAN)
Abstract
The design of efficient wireless fronthaul connections for future heterogeneous networks incorporating emerging paradigms such as cloud radio access network has become a challenging task that requires the most effective utilisation of fronthaul network resources. In this paper, we propose to use distributed compression to reduce the fronthaul traffic in uplink Coordinated Multi-Point for cloud radio access network. Unlike the conventional approach where each coordinating point quantises and forwards its own observation to the processing centre, these observations are compressed before forwarding. At the processing centre, the decompression of the observations and the decoding of the user message are conducted in a successive manner. The essence of this approach is the optimisation of the distributed compression using an iterative algorithm to achieve maximal user rate with a given fronthaul rate. In other words, for a target user rate the generated fronthaul traffic is minimised. Moreover, joint decompression and decoding is studied and an iterative optimisation algorithm is devised accordingly. Finally, the analysis is extended to multi-user case and our results reveal that, in both dense and ultra-dense urban deployment scenarios, the usage of distributed compression can efficiently reduce the required fronthaul rate and a further reduction is obtained with joint operation. Copyright
... To tackle this issue, compression techniques are a very important topic of research 4 and two main network alternatives stand out. One option is the use of functional split (FS), widely adopted by 3GPP under e-CPRI. ...
Wavelength‐division multiplexing passive optical network (WDM‐PON) is a promising solution to cope with the exponential data traffic growth, particularly regarding future mobile fronthaul. WDM‐PON schemes, based on self‐seeded wavelength agnostic transmitters using reflective semiconductor optical amplifiers (RSOAs), are seen as an option to provide an analog radio‐over‐fiber (A‐RoF) alternative to the current digital fronthaul. Although these A‐RoF have been already successfully demonstrated, it was observed that the arrayed waveguide grating (AWG)‐filtering characteristics affect both the optical seed generation and the radio signal integrity, requiring a design optimization. In order to do so, in this article, we optimize the A‐RoF transmission performance by comparing Bessel, Gaussian, and flat‐top AWG‐filter formats. The impact of seed linewidth and red‐shift on the signal error‐vector magnitude (EVM) and phase rotation is also investigated. We have found that EVM performance for BPSK and 16QAM transmission provided an improvement of 45% when compared to our previous results, with a phase offset of 0.8°, indicating little to no distortion, as a result of the selection of the optimal AWG filtering response. Self‐seeded WDM‐PON schemes with A‐RoF transport is an alternative to the current digital fronthaul. In this context, AWG‐filtering characteristics affects both the optical seed generation and the radio signal integrity, requiring a design optimization. Therefore, in this paper, we numerically analyze the performance of several AWG‐filter formats to evaluate the impacts of seed linewidth and red‐shift effect on the signal EVM and phase rotation. Results are a 45% EVM improvement, with no phase offset, when compared to our previous study.
The 5th generation of mobile communications (5G) will target unprecedented network performance and Quality of Service for end users. Among the various aspects which will be addressed in 5G, advanced cell coordination is deemed as crucial to maximize network throughput. In particular, in this paper we refer to Coordinated Multipoint (CoMP) techniques, that allow to coordinate groups of cells (i.e., clusters) through a coordination controller, namely a Radio Controller Coordinator (RCC), to enhance the mobile-network throughput by reducing interference. We focus on the placement of RCCs in the metro optical network and on its impact on the performance of cell coordination. We provide strategies to perform an optimized placement of such controllers in metro optical networks in order to maximize network throughput via cell coordination. Several CoMP techniques have been designed, whose throughput gain is affected by various factors, e.g., gain increases with the cluster size, while it decreases for larger latencies between the RCC and cells. As current metro networks are characterized by a hierarchical architecture with different levels of central offices, the choice of where to place controllers to maximize throughput gain can be optimized according to several factors, i.e., network geographical dimension, cells density and available technology. In addition, selection of the most appropriate CoMP technique to be used in each cluster is not trivial, as the gain provided by the various techniques is differently affected by cluster size and latency between the RCC and cells. Our results show that under certain conditions optimized placement provides up to around 10% higher coordination gain with respect to fixed controller placement. Moreover, when adopting fronthaul technology, the coordination gain provided by an optimized controller placement may increase up to 20% in comparison to fixed placement.
The evolution toward 5G mobile networks will be characterized by an increasing number of wireless devices, increasing device and service complexity, and the requirement to access mobile services ubiquitously. Two key enablers will allow the realization of the vision of 5G: very dense deployments and centralized processing. This article discusses the challenges and requirements in the design of 5G mobile networks based on these two key enablers. It discusses how cloud technologies and flexible functionality assignment in radio access networks enable network densification and centralized operation of the radio access network over heterogeneous backhaul networks. The article describes the fundamental concepts, shows how to evolve the 3GPP LTE a
This paper presents the approach of extending cellular networks with millimeter-wave backhaul and access links. Introducing a logical split between control and user plane will permit full coverage while seamlessly achieving very high data rates in the vicinity of mm-wave small cells.
Index coding (IC), which can be regarded as a special class of network coding, deals with the problem of sending a number of packets to a group of receivers, each of which requests one packet and may have some other packets in its cache. This paper generalizes the IC problem in that both the packet requested by a receiver and the packets in its cache can be linear combinations of the packets. To minimize the number of transmissions required, a heuristic algorithm based on the idea of partitioning the users into coding groups is designed. To realize this idea, a polynomial time algorithm to determine whether a set of users form a coding group over the binary field or a field with a size larger than the number of users is constructed. For users that form a coding group, the corresponding encoding vector can be also found. A lower bound is derived in order to evaluate the performance of the heuristic algorithm. Numerical results show that the number of transmissions required by the heuristic algorithm and the lower bound both grow roughly linearly with the number of users, and the heuristic algorithm outperforms some benchmark algorithms.
This paper introduces a concept of cloud cooperated heterogeneous cellular network (C-HetNet) where small power pico basestations (BSs) overlaid on a macrocell are connected to cloud radio access network (C-RAN) to operate cooperatively with the macro BS. Since the macro BS assists operation of the pico BSs, it is easy to deploy multi-band HetNet where e.g. macro BS is operated at 2GHz band and pico BSs at 3GHz or 60GHz band to expand operation bandwidth. Moreover, cell structure of pico BSs are controlled dynamically to track hotspot users via beam steering and cooperative transmission among pico BSs. In this paper, several numerical simulations show effectiveness of the proposed architecture, where 1,000 times system rate than that of current single band cellular network is achieved by using the proposed architecture.
The multiple access relay channel (MARC) where multiple users send independent information to a single destination aided by a single relay under large-scale path loss and slow fading is investigated. At the beginning, the users take turns to transmit their packets. The relay is not aware of the erasure status of each packet at the destination but has the knowledge of the average signal-to-noise-ratio (SNR) of every communication link. With this knowledge, the relay applies network coded retransmission on the overheard packets so as to maximize the expected total number of recovered packets or minimize the average packet loss rate at the destination. Several network coding (NC) strategies at the relay are designed. In particular, for the case where the relay is given only one time slot for retransmission, an optimal NC construction is derived. For the multiple-slot case, three sub-optimal schemes are investigated, namely network coding with maximum distance separable (MDS) code (NC-MDS), the worst-user-first (WUF) scheme and a hybrid of NC-MDS and WUF. We prove that NC-MDS and WUF are asymptotically optimal in the high and low SNR regimes, respectively. A lower bound on the average packet loss rate has been derived. Numerical studies show that, in a cellular system, the hybrid scheme offers significant performance gain over a number of existing schemes in a wide range of SNR. We also observe that performance curves of both WUF and the hybrid scheme touch the derived lower bound in the low SNR regime.
New research directions will lead to fundamental changes in the design of future fifth generation (5G) cellular networks. This article describes five technologies that could lead to both architectural and component disruptive design changes: device-centric architectures, millimeter wave, massive MIMO, smarter devices, and native support for machine-to-machine communications. The key ideas for each technology are described, along with their potential impact on 5G and the research challenges that remain.
A noisy network coding scheme for communicating messages between multiple sources and destinations over a general noisy network is presented. For multi-message multicast networks, the scheme naturally generalizes network coding over noiseless networks by Ahlswede, Cai, Li, and Yeung, and compress-forward coding for the relay channel by Cover and El Gamal to discrete memoryless and Gaussian networks. The scheme also extends the results on coding for wireless relay networks and deterministic networks by Avestimehr, Diggavi, and Tse, and coding for wireless erasure networks by Dana, Gowaikar, Palanki, Hassibi, and Effros. The scheme involves lossy compression by the relay as in the compress-forward coding scheme for the relay channel. However, unlike previous compress-forward schemes in which independent messages are sent over multiple blocks, the same message is sent multiple times using independent codebooks as in the network coding scheme for cyclic networks. Furthermore, the relays do not use Wyner-Ziv binning as in previous compress-forward schemes, and each decoder performs simultaneous decoding of the received signals from all the blocks without uniquely decoding the compression indices. A consequence of this new scheme is that achievability is proved simply and more generally without resorting to time expansion to extend results for acyclic networks to networks with cycles. The noisy network coding scheme is then extended to general multi-message networks by combining it with decoding techniques for the interference channel. For the Gaussian multicast network, noisy network coding improves the previously established gap to the cutset bound. We also demonstrate through two popular Gaussian network examples that noisy network coding can outperform conventional compress-forward, amplify-forward, and hash-forward coding schemes.
Green Communications and Networking introduces novel solutions that can bring about significant reductions in energy consumption in the information and communication technology (ICT) industry-as well as other industries, including electric power. Containing the contributions of leading experts in the field, it examines the latest research advances in green communications and networking for next-generation wired, wireless, and smart-grid networks. The book presents cutting-edge algorithms, protocols, and network architectures to improve energy efficiency in communication networks. It illustrates the various aspects of modeling, analysis, design, management, deployment, and optimization of algorithms, protocols, and architectures of green communications and networking. The text examines energy-efficient hardware platforms, physical layer, networking, and applications. Containing helpful references in each chapter, it also: Proposes a mechanism for minimizing energy consumption of wireless networks without compromising QoS Reviews recent development in utility communication networks, including advanced metering infrastructure and SCADA Studies energy-efficient rate adaptation in long-distance wireless mesh networks Considers the architectural design of energy-efficient wireline Internet nodes Presents graph-theoretic solutions that can be adopted in an IP network to reduce the number of links used in the network during off-peak periods Outlines a methodology for optimizing time averages in systems with variable length frames Details a demand-based resources trading model for green communications The book introduces a new solution for delivering green last-mile access: broadband wireless access with fiber-connected massively distributed antennas (BWA-FMDA). It also presents a methodology for optimizing time averages in systems with variable length frames. Surveying a representative number of demand and response methods in smart grids, the text supplies you with the understanding of smart grid dynamics needed to participate in the development of next-generation wireless cellular networks.
We study the uplink Multi-Cell Processing (MCP) model where each base station (BS) is connected to a centralized processor (CP) via a noiseless backhaul link with fixed and finite capacity. User data is decoded in the CP. In this paper, a fixed-order Successive Interference Cancellation (SIC) decoding scheme is adopted in the CP and the rate region is also derived. Further, we extend the MCP model with fixed-order SIC scheme to include the constraint that each user has the requirement of signal-to- interference-and-noise ratio (SINR). We analyze the option of quantized levels and give the theoretical lower bound and upper bound of the quantized levels. The analysis reveals that the quantized levels can affect whether each user uses its own maximized power to achieve the SINR requirement or not. Finally, numerical simulation shows the lower bound and the upper bound are very closed to the theoretical results.
In this paper, we consider multi-relay cooperative networks for the Rayleigh fading channel, where each relay, upon receiving its own channel observation, independently compresses it and forwards the compressed information to the destination. Although the compression at each relay is distributed using Wyner-Ziv coding, there exists an opportunity for jointly optimizing compression at multiple relays to maximize the achievable rate. Considering Gaussian signalling, a primal optimization problem is formulated accordingly. We prove that the primal problem can be solved by resorting to its Lagrangian dual problem and an iterative optimization algorithm is proposed. The analysis is further extended to a hybrid scheme, where the employed forwarding scheme depends on the decoding status of each relay. The relays that are capable of successful decoding perform decode-and-forward and the rest conduct distributed compression. The hybrid scheme allows the cooperative network to adapt to the changes of the channel conditions and benefit from an enhanced level of flexibility. Numerical results from both spectrum and energy efficiency perspectives show that the joint optimization improves efficiency of compression and identify the scenarios where the proposed schemes outperform the conventional forwarding schemes. The findings provide important insights into the optimal deployment of relays in a realistic cellular network.
Heterogeneous networks (HetNets) are a powerful solution to handle the rapidly increasing demand for mobile broadband bandwidth and are a key concept of Alcatel-Lucent's lightRadio™ strategy. HetNets consist of small cells embedded in a macrocellular network and enable flexible and scalable capacity enhancements. The first part of this paper discusses basic HetNet-specific aspects, e.g., small cell placement and fairness with respect to service quality. We present solutions for cell range expansion of small cells, which enables more user equipment (UEs) to profit from the additional capacity. The second part discusses advanced approaches for interference management optimized for HetNets. We present advanced solutions which exploit the possibilities offered by new Long Term Evolution (LTE)-Advanced features like enhanced inter-cell interference coordination (eICIC) and carrier aggregation (CA). We evaluate the performance of these advanced solutions based on standards compliant downlink (DL) system simulations in different application scenarios and provide recommendations on advanced scheduling strategies. © 2013 Alcatel-Lucent.
Uplink Coordinated Multi-Point (CoMP) joint processing has the potential to improve uplink capacity by joint processing the received signal from more antennas and nodes. With C-RAN architecture, centralized and coordinated baseband processing among base stations become feasible. This paper introduces LTE uplink CoMP joint processing - the principles, simulation evaluations, field testbed and test results. The field test is done with C-RAN field testbed which is built around Ericsson office in Beijing. Both the simulation evaluations and field test results show that uplink CoMP has great gain at the cell edge especially when there is interference, so it can be a good solution to improve the cell edge throughput of the LTE system.
A novel end-to-end transport network solution is proposed to meet the operational and technical challenges of heterogeneous networks built as C-RANs with centralized base band processing and CPRI links. The flexibility of the proposed architecture to support distributed architectures and Ethernet links is also described and the results of a C-RAN proof of concept demonstration are discussed. Substantiated by the evolution of key optical technologies, including a novel WDM-PON based solution, we conclude that backhaul and metro network strategies need to flexibly support both centralized and distributed radio baseband solutions, as well as being multiservice capable. Additionally, as a complement to fiber, we propose use of the 70/80 GHz frequency band (E-band) to provide high performance microwave links for both centralized and distributed architectures.
This chapter presents an introduction to the class of mixed-integer nonlinear MINLP optimization problems. Section 20.1 presents the motivation for studying MINLP problems. Section 20.2 discusses the mathematical formulation and outlines the theoretical and algorithmic challenges. Section 20.3 provides an overview of the local MINLP optimization algorithms which can address convex MINLP problems rigorously. Finally, section 20.4 outlines the global MINLP optimization approaches for nonconvex MINLP optimization problems.
Filling a void in chemical engineering and optimization literature, this book presents the theory and methods for nonlinear and mixed-integer optimization, and their applications in the important area of process synthesis. Other topics include modeling issues in process synthesis, and optimization-based approaches in the synthesis of heat recovery systems, distillation-based systems, and reactor-based systems. The basics of convex analysis and nonlinear optimization are also covered and the elementary concepts of mixed-integer linear optimization are introduced. All chapters have several illustrations and geometrical interpretations of the material as well as suggested problems. Nonlinear and Mixed-Integer Optimization will prove to be an invaluable source--either as a textbook or a reference--for researchers and graduate students interested in continuous and discrete nonlinear optimization issues in engineering design, process synthesis, process operations, applied mathematics, operations research, industrial management, and systems engineering.
The problem of a nomadic terminal sending information to a remote destination via agents with lossless connections to the destination is investigated. Such a setting suits, e.g., access points of a wireless network where each access point is connected by a wire to a wireline-based network. The Gaussian codebook capacity for the case where the agents do not have any decoding ability is characterized for the Gaussian channel. This restriction is demonstrated to be severe, and allowing the nomadic transmitter to use other signaling improves the rate. For both general and degraded discrete memoryless channels, lower and upper bounds on the capacity are derived. An achievable rate with unrestricted agents, which are capable of decoding, is also given and then used to characterize the capacity for the deterministic channel.
We show that any point in the Berger-Tung rate region can be achieved via successive Wyner-Ziv coding. We generalize the concept of successive refinement from single source coding to multisource coding, where we refer to it as distributed successive refinement. The quadratic Gaussian CEO problem is used as an example to illustrate some interesting aspects of distributed successive refinement.
Let X , Y , Z be zero-mean, jointly Gaussian random vectors of dimensions nx, ny, and nz, respectively. Let P be the set of random variables W such that W harr Y harr (X, Z) is a Markov string. We consider the following optimization problem: WisinP min I(Y; Z) subject to one of the following two possible constraints: 1) I(X; W|Z) ges RI, and 2) the mean squared error between X and Xcirc = E(X|W, Z) is less than d . The problem under the first kind of constraint is motivated by multiple-input multiple-output (MIMO) relay channels with an oblivious transmitter and a relay connected to the receiver through a dedicated link, while for the second case, it is motivated by source coding with decoder side information where the sensor observation is noisy. In both cases, we show that jointly Gaussian solutions are optimal. Moreover, explicit water filling interpretations are given for both cases, which suggest transform coding approaches performed in different transform domains, and that the optimal solution for one problem is, in general, suboptimal for the other.
It is known that next generation mobile communications systems will most likely employ multi-cell signal processing - often referred to as network MIMO - in order to improve spectral efficiency and fairness. Many publications exist that predict strong achievable rate improvements, but usually neglecting various practical issues connected to network MIMO. In this paper, we analyse the impact of a constrained backhaul infrastructure and imperfect channel knowledge on uplink network MIMO from an information theoretical point of view. Especially the latter aspect leads to the fact that the channel conditions for which network MIMO is reasonably beneficial are strongly constrained. We observe different base station cooperation schemes in scenarios of maximal 3 base stations and 3 terminals, provide simulation results, and discuss the practicability of the discussed schemes and the implications of our results.
Coordinated Multi-Point (CoMP) is known to be a key technology for next generation mobile communications systems, as it allows to overcome the burden of inter-cell interference. Especially in the uplink, it is likely that interference exploitation schemes will be used in the near future, as they can be used with legacy terminals and be based on operator-proprietary signal processing concepts, hence requiring no or little changes in standardization. Major drawbacks, however, are the extent of additional backhaul infrastructure needed, and the sensitivity to imperfect channel knowledge. This paper jointly addresses both issues in a new framework incorporating a multitude of proposed theoretical uplink CoMP concepts, which are then put into perspective with practical CoMP algorithms. This comprehensive analysis provides new insight into the potential value of different uplink CoMP concepts in next generation wireless communications systems, and reveals the subset of schemes that are most likely to be used in practice.
In a wireless network with a single source and a single destination and an
arbitrary number of relay nodes, what is the maximum rate of information flow
achievable? We make progress on this long standing problem through a two-step
approach. First we propose a deterministic channel model which captures the key
wireless properties of signal strength, broadcast and superposition. We obtain
an exact characterization of the capacity of a network with nodes connected by
such deterministic channels. This result is a natural generalization of the
celebrated max-flow min-cut theorem for wired networks. Second, we use the
insights obtained from the deterministic analysis to design a new
quantize-map-and-forward scheme for Gaussian networks. In this scheme, each
relay quantizes the received signal at the noise level and maps it to a random
Gaussian codeword for forwarding, and the final destination decodes the
source's message based on the received signal. We show that, in contrast to
existing schemes, this scheme can achieve the cut-set upper bound to within a
gap which is independent of the channel parameters. In the case of the relay
channel with a single relay as well as the two-relay Gaussian diamond network,
the gap is 1 bit/s/Hz. Moreover, the scheme is universal in the sense that the
relays need no knowledge of the values of the channel parameters to
(approximately) achieve the rate supportable by the network. We also present
extensions of the results to multicast networks, half-duplex networks and
ergodic networks.
Embedding pico/femto base-stations and relay nodes in a macro-cellular network is a promising method for achieving substantial gains in coverage and capacity compared to macro-only networks. These new types of base-stations can operate on the same wireless channel as the macro-cellular network, providing higher spatial reuse via cell splitting. However, these base-stations are deployed in an unplanned manner, can have very different transmit powers, and may not have traffic aggregation among many users. This could potentially result in much higher interference magnitude and variability. Hence, such deployments require the use of innovative cell association and inter-cell interference coordination techniques in order to realize the promised capacity and coverage gains. In this paper, we describe new paradigms for design and operation of such heterogeneous cellular networks. Specifically, we focus on cell splitting, range expansion, semi-static resource negotiation on third-party backhaul connections, and fast dynamic interference management for QoS via over-the-air signaling. Notably, our methodologies and algorithms are simple, lightweight, and incur extremely low overhead. Numerical studies show that they provide large gains over currently used methods for cellular networks.
In this paper we generalize (to nondiscrete sources) the results of a previous paper (Wyner and Ziv, 1976) on source coding with a fidelity criterion in a situation where the decoder (but not the encoder) has access to side information about the source. We define R*(d) as the minimum rate (in the usual Shannon sense) required for encoding the source at a distortion level about d. The main result is the characterization of R*(d) by an information theoretic minimization. In a special case in which the source and the side information are jointly Gaussian, it is shown that R*(d) is equal to the rate which would be required if the encoder (as well as the decoder) is informed of the side information.
This paper revisits an algorithm isolating the real roots of a univariate polynomial using Descartes’ rule of signs. It follows work of Vincent, Uspensky, Collins and Akritas, Johnson, Krandick.Our first contribution is a generic algorithm which enables one to describe all the known algorithms based on Descartes’ rule of sign and the bisection strategy in a unified framework.Using that framework, a new algorithm is presented, which is optimal in terms of memory usage and as fast as both Collins and Akritas’ algorithm and Krandick's variant, independently of the input polynomial. From this new algorithm, we derive an adaptive semi-numerical version, using multi-precision interval arithmetic.We finally show that these critical optimizations have important consequences since our new algorithm still works with huge polynomials, including orthogonal polynomials of degree 1000 and more, which were out of reach of previous methods.
Yu and Liu's strong duality theorem under the time-sharing property requires the Slater condition to hold for the considered general nonconvex problem, what is satised for the specic application. We further extend the scope of the theorem under Ky Fan
..... joint decoding provides more freedom in choosing the compression at the
relay.
However, the question remains whether this freedom of selecting the
compression necessarily improves the achievable rate of the original message.
It has been shown in (El Gamal and Kim, 2010) that the answer is negative in
the single-relay case. In this paper, it is further demonstrated that in the
case of multiple relays, there is no improvement on the achievable rate by
joint decoding either. More interestingly, it is discovered that any
compressions not supporting successive decoding will actually lead to strictly
lower achievable rates for the original message. Therefore, to maximize the
achievable rate for the original message, the compressions should always be
chosen to support successive decoding. Furthermore, it is shown that any
compressions not completely decodable even with joint decoding will not provide
any contribution to the decoding of the original message.
The above phenomenon is also shown to exist under the repetitive encoding
framework recently proposed by (Lim, Kim, El Gamal, and Chung, 2010), which
improved the achievable rate in the case of multiple relays. Here, another
interesting discovery is that the improvement is not a result of repetitive
encoding, but the benefit of delayed decoding after all the blocks have been
finished. The same rate is shown to be achievable with the simpler classical
encoding process of (Cover and El Gamal, 1979) with a block-by-block backward
decoding process.
The design and optimization of multicarrier communications systems often involve a maximization of the total throughput subject to system resource constraints. The optimization problem is numerically difficult to solve when the problem does not have a convexity structure. This paper makes progress toward solving optimization problems of this type by showing that under a certain condition called the time-sharing condition, the duality gap of the optimization problem is always zero, regardless of the convexity of the objective function. Further, we show that the time-sharing condition is satisfied for practical multiuser spectrum optimization problems in multicarrier systems in the limit as the number of carriers goes to infinity. This result leads to efficient numerical algorithms that solve the nonconvex problem in the dual domain. We show that the recently proposed optimal spectrum balancing algorithm for digital subscriber lines can be interpreted as a dual algorithm. This new interpretation gives rise to more efficient dual update methods. It also suggests ways in which the dual objective may be evaluated approximately, further improving the numerical efficiency of the algorithm. We propose a low-complexity iterative spectrum balancing algorithm based on these ideas, and show that the new algorithm achieves near-optimal performance in many practical situations
Coding strategies that exploit node cooperation are developed for relay networks. Two basic schemes are studied: the relays decode-and-forward the source message to the destination, or they compress-and-forward their channel outputs to the destination. The decode-and-forward scheme is a variant of multihopping, but in addition to having the relays successively decode the message, the transmitters cooperate and each receiver uses several or all of its past channel output blocks to decode. For the compress-and-forward scheme, the relays take advantage of the statistical dependence between their channel outputs and the destination's channel output. The strategies are applied to wireless channels, and it is shown that decode-and-forward achieves the ergodic capacity with phase fading if phase information is available only locally, and if the relays are near the source node. The ergodic capacity coincides with the rate of a distributed antenna array with full cooperation even though the transmitting antennas are not colocated. The capacity results generalize broadly, including to multiantenna transmission with Rayleigh fading, single-bounce fading, certain quasi-static fading problems, cases where partial channel knowledge is available at the transmitters, and cases where local user cooperation is permitted. The results further extend to multisource and multidestination networks such as multiaccess and broadcast relay channels.
This paper provides bounds on the rate-distortion region for the distributed compression scenario where two (or more) sources are compressed separately for a decoder that has access to side information. Conclusive rate-distortion results are found for the case where the sources are conditionally independent, given the side information.
Let {(X_{k}, Y_{k}) }^{ infty}_{k=1} be a sequence of independent drawings of a pair of dependent random variables X, Y . Let us say that X takes values in the finite set cal X . It is desired to encode the sequence {X_{k}} in blocks of length n into a binary stream of rate R , which can in turn be decoded as a sequence { hat{X}_{k} } , where hat{X}_{k} in hat{ cal X} , the reproduction alphabet. The average distortion level is (1/n) sum^{n}_{k=1} E[D(X_{k},hat{X}_{k})] , where D(x,hat{x}) geq 0, x in {cal X}, hat{x} in hat{ cal X} , is a preassigned distortion measure. The special assumption made here is that the decoder has access to the side information {Y_{k}} . In this paper we determine the quantity R ast (d) , defined as the infimum ofrates R such that (with varepsilon > 0 arbitrarily small and with suitably large n )communication is possible in the above setting at an average distortion level (as defined above) not exceeding d + varepsilon . The main result is that R ast (d) = inf [I(X;Z) - I(Y;Z)] , where the infimum is with respect to all auxiliary random variables Z (which take values in a finite set cal Z ) that satisfy: i) Y,Z conditionally independent given X ; ii) there exists a function f: {cal Y} times {cal Z} rightarrow hat{ cal X} , such that E[D(X,f(Y,Z))] leq d . Let R_{X | Y}(d) be the rate-distortion function which results when the encoder as well as the decoder has access to the side information { Y_{k} } . In nearly all cases it is shown that when d > 0 then R ast(d) > R_{X|Y} (d) , so that knowledge of the side information at the encoder permits transmission of the {X_{k}} at a given distortion level using a smaller transmission rate. This is in contrast to the situation treated by Slepian and Wolf [5] where, for arbitrarily accurate reproduction of {X_{k}} , i.e., d = varepsilon for any varepsilon >0 , knowledge of the side information at the-
encoder does not allow a reduction of the transmission rate.
Beyond 4G radio evolution for the gigabit experience
- NSN white paper
C-RAN White paper V2.5
- China Mobile Research institute
Coordinated multi-point under a constrained fronthaul and imperfect channel knowledge
- Marschp
D2.2: Definition and parameterization of reference systems and scenarios
- Holtkamph
Coordinated Multi-Point in Mobile Communications: From Theory to Practice
- Marsch P
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C-RAN - Road Towards Green Radio Access Network
- China Mobile Research Institute
5G: a technical vision
- Huawei White Paper
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Evaluation of joint transmission coMP in C-RAN based LTE-A HetNets with large coordination areas
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A Evaluation of joint transmission coMP in C-RAN based LTE-A HetNets with large coordination areas Proceedings of IEEE Globecom workshop Atlanta
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Weiler RJ Enabling 5G fronthaul and access with millimeter-waves Proc
Enabling 5G fronthaul and access with millimeter-waves
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Distributed source coding via successive refinement
- Chenj Bergert