Cooperation between rational users in wireless networks is studied using coalitional game theory. Using the rate achieved by a user as its utility, it is shown that the stable coalition structure, i.e., set of coalitions from which users have no incentives to defect, depends on the manner in which the rate gains are apportioned among the cooperating users. Specifically, the stability of the grand coalition (GC), i.e., the coalition of all users, is studied. Transmitter and receiver cooperation in an interference channel (IC) are studied as illustrative cooperative models to determine the stable coalitions for both flexible (transferable) andfixed (non-transferable) apportioning schemes. It is shown that the stable sum-rate optimal coalition when only receivers cooperate by jointly decoding (transferable) is the GC. The stability of the GC depends on the detector when receivers cooperate using linear multiuser detectors (non-transferable). Transmitter cooperation is studied assuming that all receivers cooperate perfectly and that users outside a coalition act as jammers. The stability of the GC is studied for both the case of perfectly cooperating transmitters (transferrable) and under a partial decode-and-forward strategy (non-transferable). In both cases, the stability is shown to depend on the channel gains and the transmitter jamming strengths.

Capacity gain from transmitter and receiver cooperation are compared in a relay network where the cooperating nodes are close together. Under quasi-static channels, when all nodes have equal average transmit power along with full channel state information (CSI), it is shown that transmitter cooperation outperforms receiver cooperation, whereas the opposite is true when power is optimally allocated among the cooperating nodes but only CSI at the receiver (CSIR) is available. When the nodes have equal power with CSIR only, cooperative schemes are shown to offer no capacity improvement over non-cooperation under the same network power constraint. When the system is under optimal power allocation with full CSI, the decode-and-forward transmitter cooperation rate is close to its cut-set capacity upper bound, and outperforms compress-and-forward receiver cooperation. Under Rayleigh fading in the high SNR regime, similar conclusions follow. Cooperative systems provide resilience to channel fading; however, capacity becomes more sensitive to power allocation, and the cooperating nodes need to be closer together for the decode-and-forward scheme to be capacity-achieving. Moreover, to realize capacity improvement, full CSI is necessary in transmitter cooperation, while in receiver cooperation optimal power allocation is essential.

This paper proposes a practical compress-and-forward cooperation scheme with vector coding at the relay node for a three-terminal classical relay network. We discuss the framework of the relay receiver and analyse two practical vector coding algorithms for the cooperation, nearest neighbour quantization and lattice vector quantization. The error rate performance of the compress-and-forward cooperation and some other protocols under different SNRs is investigated. The impact of the quantization rate at the relay node is also characterised. It is shown that for a quantization rate larger than 2 bits/sample, the vector coding whether employing nearest neighbour quantization or lattice vector quantization, outerforms both the decode-and-forward protocol and scalar coding. 1.

In wireless networks, we can improve system performance by exploiting cooperative communications, where neighbor nodes may interact to jointly encode, decode, or relay information. In this thesis, we show that cooperation can improve capacity, but only when the right cooperation strategy is chosen based on the network topology, signal-to-noise ratio (SNR), channel state information (CSI), and power allocation assumptions. In particular, when we consider the deployment of relay nodes in a wireless network, CSI at the transmitter is necessary for effective transmitter cooperation, while transmission power allocation between the cooperating nodes is crucial for receiver cooperation. The benefits of cooperation are further studied when the relay and receiver can iterate to exchange information over orthogonal, finite-capacity channels known as conference links. We show that a two-round iterative decoding scheme can achieve a higher capacity over non-iterative cooperation. This thesis also investigates cross-layer resource allocation where network resources such

We investigate the relay selection problem for a decode and forward collaborative network. Users are able to collaborate; decode messages of each other, re-encode and forward along with their own messages. We study the performance obtained from collaboration in terms of 1) increasing the achievable rate, 2) saving the transmit energy and 3) reducing the resource requirement (resource means timebandwidth). To ensure fairness, we fix the transmit-energy-to-rate ratio among all users. We allocate resource optimally for the collaborative protocol (CP), and compare the result with the non-collaborative protocol (NCP) where users transmits their messages directly. The collaboration gain is a function of the channel gain and available energies and allows us 1) to decide to collaborate or not, 2) to select one relay among the possible relay users, and 3) to determine the involved gain and loss of possible collaboration. A considerable gain can be obtained if the direct source-destination channel gain is significantly smaller than those of alternative involved links. We demonstrate that a rate and energy improvement of up to 1 + η

(IC) is considered in which a noiseless unidirectional link connects one encoder to the other. Having a constant capacity, the additional link provides partial cooperation between the encoders. It is shown that the available cooperation can dramatically increase the sum-capacity of the channel. This fact is proved based on comparison of proposed lower and upper bounds on the sum-capacity. Partitioning the data into three independent messages, namely private, common, and cooperative ones, the transmission strategy used to obtain the lower bound enjoys a simple type of Han-Kobayashi scheme together with a cooperative communication scheme. A Genie-aided upper bound is developed which incorporates the capacity of the cooperative link. Other upper bounds are based on the sum-capacity of the Cognitive Radio Channel and cut-set bounds. For the strong interference regime, the achievablity scheme is simplified to employ common and/or cooperative messages but not the private one. Through a careful analysis it is shown that the gap between these bounds is at most one and two bits per real dimension for strong and weak interference regimes, respectively. Moreover, the Generalized Degrees-of-Freedom of the channel is characterized. I.

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the source pair via decode and forward coding to transmit a part of the message of the source pair and the private message of the relay pair. In the second scheme the relay pair partially cancels the interference of other users and sends the compressed observed signal to the intended receiver of source pair, the 4th user. Collaboration between wireless users has been investigated recently by several authors. Liang and Veeravalli [3] studied a cooperative relay broadcast channel with three users where relay links are incorporated into standard two-user broadcast channels to support user cooperation. Liang and Kramer [4] have found improved bounds for the relay broadcast channel. Tannious and Nosratinia in [5] developed decode and forward and compress and forward strategies for a network of one relay channel with private messages where in addition to the traditional communication from source to destination (assisted by relay), the source has a private message for the relay, and the relay has a private message for the destination (see [6] for a survey on decode and forward and compress and forward strategies). Akhavan and Gazor [7] investigated multi-hopping strategies and resource allocation in such networks. Reznik, Kulkarni and Verdu in [8] further studied the relay broadcast collaborative model for the case of more than two destinations. Sendonaris, Erkip and Aazhang in [9], [10] showed that collaboration enlarges the achievable rate region in a channel with two collaborative transmitters and a single receiver. Laneman, Tse and Wornell considered a fading channel with two cooperative transmitters and two non-cooperative receivers [11]. Host-Madsen in [12], [13] presented the achievable rate regions for channels with transmitter and/or receiver collaboarXiv:0807.0868v1

Abstract—We investigate capacity bounds for a wireless multicast relay network where two sources simultaneously multicast to two destinations with the help of a full-duplex relay node. The two sources and the relay use the same channel resources (i.e. co-channel transmission). We assume Gaussian channels with time-invariant channel gains which are known by all nodes. The two source nodes are connected by orthogonal limited-rate errorfree conferencing links. By extending the proof of the converse for the Gaussian relay channel and introducing two lemmas on conditional (co-)variance, we present two genie-aided outer bounds of the capacity region for this multicast relay network. We extend noisy network coding to use source cooperation with the help of the theory of network equivalence. We also propose a new coding scheme, partial-decode-and-forward based linear network coding, which is essentially a hybrid scheme utilizing rate-splitting and messages conferencing at the source nodes, partial decoding and linear network coding at the relay, and joint decoding at each destination. A low-complexity alternative scheme, analog network coding based on amplify-and-forward relaying, is also investigated and shown to benefit greatly from the help of the conferencing links and can even outperform noisy network coding when the coherent combining gain is dominant. Index Terms—Relays, source cooperation, network coding, wireless multicast, cooperative communication. I.