Cloud Compute-and-Forward with Relay Cooperation

We study a cloud network with M distributed receiving antennas and L users, which transmit their messages towards a centralized decoder (CD), where M>=L. We consider that the cloud network applies the Compute-and-Forward (C&F) protocol, where L antennas/relays are selected to decode integer equations of the transmitted messages. In this work, we focus on the best relay selection and the optimization of the Physical-Layer Network Coding (PNC) at the relays, aiming at the throughput maximization of the network. Existing literature optimizes PNC with respect to the maximization of the minimum rate among users. The proposed strategy maximizes the sum rate of the users allowing nonsymmetric rates, while the optimal solution is explored with the aid of the Pareto frontier. The problem of relay selection is matched to a coalition formation game, where the relays and the CD cooperate in order to maximize their profit. Efficient coalition formation algorithms are proposed, which perform joint relay selection and PNC optimization. Simulation results show that a considerable improvement is achieved compared to existing results, both in terms of the network sum rate and the players' profits.Comment: Submitted to IEEE Transactions on Wireless Communication

Sparse multiple relay selection for network beamforming with individual power constraints using semidefinite relaxation

This paper deals with the multiple relay selection problem in two-hop wireless cooperative networks with individual power constraints at the relays. In particular, it addresses the problem of selecting the best subset of K cooperative nodes and their corresponding beamforming weights so that the signal-to-noise ratio (SNR) is maximized at the destination. This problem is computationally demanding and requires an exhaustive search over all the possible combinations. In order to reduce the complexity, a new suboptimal method is proposed. This technique exhibits a near-optimal performance with a computational burden that is far less than the one needed in the combinatorial search. The proposed method is based on the use of the l1-norm squared and the Charnes-Cooper transformation and naturally leads to a semidefinite programming relaxation with an affordable computational cost. Contrary to other approaches in the literature, the technique exposed herein is based on the knowledge of the second-order statistics of the channels and the relays are not limited to cooperate with full power.Peer ReviewedPostprint (author's final draft

End-to-End Joint Antenna Selection Strategy and Distributed Compress and Forward Strategy for Relay Channels

Multi-hop relay channels use multiple relay stages, each with multiple relay nodes, to facilitate communication between a source and destination. Previously, distributed space-time codes were proposed to maximize the achievable diversity-multiplexing tradeoff, however, they fail to achieve all the points of the optimal diversity-multiplexing tradeoff. In the presence of a low-rate feedback link from the destination to each relay stage and the source, this paper proposes an end-to-end antenna selection (EEAS) strategy as an alternative to distributed space-time codes. The EEAS strategy uses a subset of antennas of each relay stage for transmission of the source signal to the destination with amplify and forwarding at each relay stage. The subsets are chosen such that they maximize the end-to-end mutual information at the destination. The EEAS strategy achieves the corner points of the optimal diversity-multiplexing tradeoff (corresponding to maximum diversity gain and maximum multiplexing gain) and achieves better diversity gain at intermediate values of multiplexing gain, versus the best known distributed space-time coding strategies. A distributed compress and forward (CF) strategy is also proposed to achieve all points of the optimal diversity-multiplexing tradeoff for a two-hop relay channel with multiple relay nodes.Comment: Accepted for publication in the special issue on cooperative communication in the Eurasip Journal on Wireless Communication and Networkin

Optimal Relay Selection with Non-negligible Probing Time

In this paper an optimal relay selection algorithm with non-negligible probing time is proposed and analyzed for cooperative wireless networks. Relay selection has been introduced to solve the degraded bandwidth efficiency problem in cooperative communication. Yet complete information of relay channels often remain unavailable for complex networks which renders the optimal selection strategies impossible for transmission source without probing the relay channels. Particularly when the number of relay candidate is large, even though probing all relay channels guarantees the finding of the best relays at any time instant, the degradation of bandwidth efficiency due to non-negligible probing times, which was often neglected in past literature, is also significant. In this work, a stopping rule based relay selection strategy is determined for the source node to decide when to stop the probing process and choose one of the probed relays to cooperate with under wireless channels' stochastic uncertainties. This relay selection strategy is further shown to have a simple threshold structure. At the meantime, full diversity order and high bandwidth efficiency can be achieved simultaneously. Both analytical and simulation results are provided to verify the claims.Comment: 8 pages. ICC 201

Relay subset selection in cognitive networks with imperfect CSI and individual power constraints

This paper considers the relay subset selection problem in an underlay cognitive network in which two secondary users communicate assisted by a set of N potential relays. More specifically, this paper deals with the joint problem of choosing the best subset of L secondary relays and their corresponding weights which maximize the Signal-to-Interference-plus-Noise ratio (SINR) at the secondary user receiver, subject to per-relay power constraints and interference power constraints at the primary user. This problem is a combinatorial problem with a high computational burden. Nevertheless, we propose a sub-optimal technique, based on a convex relaxation of the problem, which achieves a near-optimal performance with a reduced complexity. Contrary to other approaches in the literature, the secondary relays are not limited to cooperate at full power.Peer ReviewedPostprint (author's final draft

Cyclic Distributed Space–Time Codes for Wireless Relay Networks With No Channel Information

In this paper, we present a coding strategy for half duplex wireless relay networks, where we assume no channel knowledge at any of the transmitter, receiver, or relays. The coding scheme uses distributed space–time coding, that is, the relay nodes cooperate to encode the transmitted signal so that the receiver senses a space–time codeword. It is inspired by noncoherent differential techniques. The proposed strategy is available for any number of relays nodes. It is analyzed, and shown to yield a diversity linear in the number of relays. We also study the resistance of the scheme to relay node failures, and show that a network with R relay nodes and d of them down behaves, as far as diversity is concerned, as a network with R-d nodes. Finally, our construction can be easily generalized to the case where the transmitter and receiver nodes have several antennas

Coalition Formation Game for Cooperative Cognitive Radio Using Gibbs Sampling

This paper considers a cognitive radio network in which each secondary user selects a primary user to assist in order to get a chance of accessing the primary user channel. Thus, each group of secondary users assisting the same primary user forms a coaltion. Within each coalition, sequential relaying is employed, and a relay ordering algorithm is used to make use of the relays in an efficient manner. It is required then to find the optimal sets of secondary users assisting each primary user such that the sum of their rates is maximized. The problem is formulated as a coalition formation game, and a Gibbs Sampling based algorithm is used to find the optimal coalition structure.Comment: 7 pages, 2 figure

Crystallization in large wireless networks

We analyze fading interference relay networks where M single-antenna source-destination terminal pairs communicate concurrently and in the same frequency band through a set of K single-antenna relays using half-duplex two-hop relaying. Assuming that the relays have channel state information (CSI), it is shown that in the large-M limit, provided K grows fast enough as a function of M, the network "decouples" in the sense that the individual source-destination terminal pair capacities are strictly positive. The corresponding required rate of growth of K as a function of M is found to be sufficient to also make the individual source-destination fading links converge to nonfading links. We say that the network "crystallizes" as it breaks up into a set of effectively isolated "wires in the air". A large-deviations analysis is performed to characterize the "crystallization" rate, i.e., the rate (as a function of M,K) at which the decoupled links converge to nonfading links. In the course of this analysis, we develop a new technique for characterizing the large-deviations behavior of certain sums of dependent random variables. For the case of no CSI at the relay level, assuming amplify-and-forward relaying, we compute the per source-destination terminal pair capacity for M,K converging to infinity, with K/M staying fixed, using tools from large random matrix theory.Comment: 30 pages, 6 figures, submitted to journal IEEE Transactions on Information Theor