A branch and bound method for stochastic global optimization
Mathematical Programming: Series A and B
Capacity theorems for the relay channel
IEEE Transactions on Information Theory
An achievable rate region for the multiple-access channel with feedback
IEEE Transactions on Information Theory
Cooperative diversity in wireless networks: Efficient protocols and outage behavior
IEEE Transactions on Information Theory
Cooperative Strategies and Capacity Theorems for Relay Networks
IEEE Transactions on Information Theory
On the achievable diversity-multiplexing tradeoff in half-duplex cooperative channels
IEEE Transactions on Information Theory
Outage analysis of coded cooperation
IEEE Transactions on Information Theory
Capacity bounds for Cooperative diversity
IEEE Transactions on Information Theory
Capacity Gain From Two-Transmitter and Two-Receiver Cooperation
IEEE Transactions on Information Theory
A Case for Amplify–Forward Relaying in the Block-Fading Multiple-Access Channel
IEEE Transactions on Information Theory
Cooperative lattice coding and decoding in half-duplex channels
IEEE Journal on Selected Areas in Communications
Joint optimization of relay strategies and resource allocations in cooperative cellular networks
IEEE Journal on Selected Areas in Communications
Grouping and partner selection in cooperative wireless networks
IEEE Journal on Selected Areas in Communications
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We consider a multiple access MAC fading channel with two users communicating with a common destination, where each user mutually acts as a relay for the other one as well as wishes to transmit its own information as opposed to having dedicated relays. We wish to evaluate the usefulness of relaying from the point of view of the system's throughput (sum rate) rather than from the sole point of view of the user benefiting from the cooperation as is typically done. We do this by allowing a trade-off between relaying and fresh data transmission through a resource allocation framework. Specifically, We propose a cooperative transmission scheme allowing each user to allocate a certain amount of power for its own transmitted data while the rest is devoted to relaying. The underlying protocol is based on a modification of the so-called non-orthogonal amplify-and-forward (NAF) protocol Azarian et al. [18]. We develop capacity expressions for our scheme and derive the rate-optimum power allocation, in closed form for centralized and distributed frameworks. In the distributed scenario, partially statistical and partially instantaneous channel information is exploited. The centralized power allocation algorithm indicates that even in a mutual cooperation setting like ours, on any given realization of the channel, cooperation is never truly mutual, i.e. one of the users will always allocate zero power to relaying the data of the other one, and thus act selfishly. But in a distributed framework, our results indicate that the sum rate is maximized when both mobiles act selfishly.