Optimal Distributed Resource Allocation for Decode-and-Forward Relay Networks

This paper presents a distributed resource allocation algorithm to jointly optimize the power allocation, channel allocation and relay selection for decode-and-forward (DF) relay networks with a large number of sources, relays, and destinations. The well-known dual decomposition technique cannot directly be applied to resolve this problem, because the achievable data rate of DF relaying is not strictly concave, and thus the local resource allocation subproblem may have non-unique solutions. We resolve this non-strict concavity problem by using the idea of the proximal point method, which adds quadratic terms to make the objective function strictly concave. However, the proximal solution adds an extra layer of iterations over typical duality based approaches, which can significantly slow down the speed of convergence. To address this key weakness, we devise a fast algorithm without the need for this additional layer of iterations, which converges to the optimal solution. Our algorithm only needs local information exchange, and can easily adapt to variations of network size and topology. We prove that our distributed resource allocation algorithm converges to the optimal solution. A channel resource adjustment method is further developed to provide more channel resources to the bottleneck links and realize traffic load balance. Numerical results are provided to illustrate the benefits of our algorithm

Noisy Network Coding with Partial DF

In this paper, we propose a noisy network coding integrated with partial decode-and-forward relaying for single-source multicast discrete memoryless networks (DMN's). Our coding scheme generalizes the partial-decode-compress-and-forward scheme (Theorem 7) by Cover and El Gamal. This is the first time the theorem is generalized for DMN's such that each relay performs both partial decode-and-forward and compress-and-forward simultaneously. Our coding scheme simultaneously generalizes both noisy network coding by Lim, Kim, El Gamal, and Chung and distributed decode-and-forward by Lim, Kim, and Kim. It is not trivial to combine the two schemes because of inherent incompatibility in their encoding and decoding strategies. We solve this problem by sending the same long message over multiple blocks at the source and at the same time by letting the source find the auxiliary covering indices that carry information about the message simultaneously over all blocks.Comment: 5 pages, 1 figure, to appear in Proc. IEEE ISIT 201

Relay-Induced Error Propagation Reduction for Decode-and-Forward Cooperative Communications

An attractive hybrid method of mitigating the effects of error propagation that may be imposed by the relay node (RN) on the destination node (DN) is proposed. We selected the most appropriate relay location for achieving a specific target Bit Error Ratio (BER) at the relay and signalled the RN-BER to the DN. The knowledge of this BER was then exploited by the decoder at the destination. Our simulation results show that when the BER at the RN is low, we do not have to activate the RN-BER aided decoder at the DN. However, when the RN-BER is high, significant system performance improvements may be achieved by activating the proposed RN-BER based decoding technique at the DN. For example, a power-reduction of up to about 19dB was recorded at a DN BER of 10-4