Conference Paper

Joint admission control & interference avoidance in self-organized femtocells

Centre for Wireless Commun., Univ. of Oulu, Oulu, Finland
DOI: 10.1109/ACSSC.2010.5757566 Conference: Signals, Systems and Computers (ASILOMAR), 2010 Conference Record of the Forty Fourth Asilomar Conference on
Source: IEEE Xplore


In this paper, we consider a femtocell deployment scenario in which radio resources are shared among self-organized femtocells. We propose a distributed Admission Control Mechanism (ACM) for traffic load balancing among sub-carriers when there are multiple Quality of Service (QoS) classes. Furthermore, we propose a mechanism based on Reinforcement Learning (RL) for slot allocation to the traffic streams on different sub-carriers, which is employed by each Femto Access Point (FAP) to mitigate interference among femtocells and the underlaid macrocell. Through simulations, the performance of the proposed scheme is evaluated where it is shown that femtocells are able to coexist with the overlay macrocell network with no information exchange and by relying only on local information.

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    • "Two-tier macrocell/ Maximize sum-rate Yes No No Yes No small cell network for two tiers [8] Two-tier macrocell/ Maximize sum-min Yes No For Yes No small cell network rate for small cells MUEs [9] Two-tier macrocell/ Maximize sum-rate Yes No For Yes No small cell network for two tiers MUEs [10] Two-tier macrocell/ Maximize sum-rate Yes No For Yes No small cell network for small cells MUEs [11] Two-tier macrocell/ Maximize sum-rate Yes No For Semi- No small cell network for small cells SUEs distributed [13] Single-tier small Minimize sum-power Yes No Yes Yes No cell network [14] Cognitive radio Maximize number of links No Yes Yes No No networks with max sum-rate [15] Cognitive radio Maximize number of users No Yes Yes Yes No networks with min sum-power [16] Cognitive radio Maximize min-rate and No Yes Yes No No networks maximize sum-log rate [17] Cognitive radio Maximize sum-rate Yes Yes Yes No No networks [18] Relay Maximize min-SINR, min No Yes Yes No No networks max-power and max sum-rate [19] Relay Maximize sum-rate, max Yes Yes Yes No No networks min-rate and minimize sum-power [20] Two-tier macrocell/ Minimize sum-power with No Yes For MUEs Yes No small cell network max number of SUEs and SUEs [21] Two-tier macrocell/ Maximize product of Yes Yes For SUEs Yes No small cell network minimum of (2×target rate -achieved rate) and achieved rate Our Two-tier macrocell/ Maximize sum-tolerable Yes Yes For MUEs Yes Yes proposed small cell network interference for MUEs and SUEs scheme and maximize admitted SUEs with minimum bandwidth channel gain of the link between BS i and UE j on sub-channel n. Channel gains are time varying and account for path-loss, log-normal shadowing, and fast fading. "
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    ABSTRACT: We present a joint sub-channel and power allocation framework for downlink transmission an orthogonal frequency-division multiple access (OFDMA)-based cellular network composed of a macrocell overlaid by small cells. In this framework, the resource allocation (RA) problems for both the macrocell and small cells are formulated as optimization problems. Numerical results confirm the performance gains of our proposed RA formulation for the macrocell over the traditional resource allocation based on minimizing the transmission power. Besides, it is shown that the formulation based on convex relaxation yields a similar behavior to the MINLP formulation. Also, the distributed solution converges to the same solution obtained by solving the corresponding convex optimization problem in a centralized fashion.
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    • "In [13], a frequency scheduling algorithm based on spectrum sensing was proposed for coexistence of MUEs and FUEs. In [14], distributed admission control and spectrum allocation algorithms were developed using reinforcement learning, which are, however, unable to provide performance guarantees for users of both network tiers. There are existing works in the literature that investigated the admission control problem based on Markov Decision Process (MDP) and also the power control problem for traditional one-tier CDMA wireless networks [16], [17], [21]. "
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    ABSTRACT: We consider the joint resource allocation and admission control problem for Orthogonal Frequency-Division Multiple Access (OFDMA)-based femtocell networks. We assume that Macrocell User Equipments (MUEs) can establish connections with Femtocell Base Stations (FBSs) to mitigate the excessive cross-tier interference and achieve better throughput. A cross-layer design model is considered where multiband opportunistic scheduling at the Medium Access Control (MAC) layer and admission control at the network layer working at different time-scales are assumed. We assume that both MUEs and Femtocell User Equipments (FUEs) have minimum average rate constraints, which depend on their geographical locations and their application requirements. In addition, blocking probability constraints are imposed on each FUE so that the connections from MUEs only result in controllable performance degradation for FUEs. We present an optimal design for the admission control problem by using the theory of Semi-Markov Decision Process (SMDP). Moreover, we devise a novel distributed femtocell power adaptation algorithm, which converges to the Nash equilibrium of a corresponding power adaptation game. This power adaptation algorithm reduces energy consumption for femtocells while still maintaining individual cell throughput by adapting the FBS power to the traffic load in the network. Finally, numerical results are presented to demonstrate the desirable operation of the optimal admission control solution, the significant performance gain of the proposed hybrid access strategy with respect to the closed access counterpart, and the great power saving gain achieved by the proposed power adaptation algorithm.
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    • "This solution has been shown to be able to demonstrate scalability with respect to the network load and the number of contending wireless devices. The same concept has been further extended in [6] to facilitate admission control in Femtocell networks for traffic load balancing among sub-carriers when there are multiple Quality of Service (QoS) classes. Similarly, in [8] the stochastic counter management is combined with a modified Dutch auction and a distributed association mechanism for Macro-to-Femto handover is proposed. "
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    ABSTRACT: In this paper, we consider cooperative multi-hop wireless Body Area Networks (BANs), connecting sensor nodes to multiple data sinks, referred to as hubs. Each network comprises a set of sensory devices, as well as a data sink, and the coexisting BANs cooperate in order to enable the sensor nodes to have their data traffic delivered to one of the data sinks. To reach a hub, either located in the local- or a nearby network, each sensor should choose a route and communicate with the relay at the tail of the chosen route. We propose a stochastic route selection mechanism, which takes into account the maximum perceived outage probability, maximum queue utilization factor, and the minimum remaining battery power of the relays of each route to determine how probable the route is to be selected to deliver a requesting sensor node's traffic to a particular hub. The performance of the proposed scheme is assessed through system-level simulations, revealing that the introduced mechanism scales well with the increase of the number of sensor nodes.
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