On Capacity and Optimal Scheduling for the Half-Duplex Multiple-Relay Channel

We study the half-duplex multiple-relay channel (HD-MRC) where every node can either transmit or listen but cannot do both at the same time. We obtain a capacity upper bound based on a max-flow min-cut argument and achievable transmission rates based on the decode-forward (DF) coding strategy, for both the discrete memoryless HD-MRC and the phase-fading HD-MRC. We discover that both the upper bound and the achievable rates are functions of the transmit/listen state (a description of which nodes transmit and which receive). More precisely, they are functions of the time fraction of the different states, which we term a schedule. We formulate the optimal scheduling problem to find an optimal schedule that maximizes the DF rate. The optimal scheduling problem turns out to be a maximin optimization, for which we propose an algorithmic solution. We demonstrate our approach on a four-node multiple-relay channel, obtaining closed-form solutions in certain scenarios. Furthermore, we show that for the received signal-to-noise ratio degraded phase-fading HD-MRC, the optimal scheduling problem can be simplified to a max optimization.Comment: Author's final version (to appear in IEEE Transactions on Information Theory

Analysis and Optimization of Cooperative Wireless Networks

Recently, cooperative communication between users in wireless networks has attracted a considerable amount of attention. A significant amount of research has been conducted to optimize the performance of different cooperative communication schemes, subject to some resource constraints such as power, bandwidth, and time. However, in previous research, each optimization problem has been investigated separately, and the optimal solution for one problem is usually not optimal for the other problems. This dissertation focuses on joint optimization or cross-layer optimization in wireless cooperative networks. One important obstacle is the non-convexity of the joint optimization problem, which makes the problem difficult to solve efficiently. The first contribution of this dissertation is the proposal of a method to efficiently solve a joint optimization problem of power allocation, time scheduling and relay selection strategy in Decode-and-Forward cooperative networks. To overcome the non-convexity obstacle, the dual optimization method for non-convex problems \cite{Yu:2006}, is applied by exploiting the time-sharing properties of wireless OFDM systems when the number of subcarriers approaches infinity. The second contribution of this dissertation is the design of practical algorithms to implement the aforementioned method for optimizing the cooperative network. The difficulty of this work is caused by the randomness of the data, specifically, the randomness of the channel condition, and the real-time requirements of computing. The proposed algorithms were analyzed rigorously and the convergence of the algorithms is shown.\\ Furthermore, a joint optimization problem of power allocation and computational functions for the advanced cooperation scheme, Compute-and-Forward, is also analyzed, and an iterative algorithm to solve this problem is also introduced

Transmission schedule optimization for half-duplex multiple-relay networks.

Half duplex devices are widely used in today's wireless networks. These devices can only send or receive, but not do both at the same time. In this paper, we use cooperative decode-forward relay strategies to increase the throughput of half-duplex wireless networks. Due to the half duplex constraint, relays need to carefully choose their transmission states in order to maximize the throughput. We show that the transmission schedule optimization can be formulated as a linear programming problem. Although the number of possible states grows exponentially as the number of relays increases, only a small subset of these states needs to be used in the optimal transmission schedule. This observation allows us to use heuristic algorithms to solve for near-optimal schedule in large networks. Our numerical results show that the decode-forward strategy can provide nearly 3 times more throughput than the traditional multi-hop relaying strategy in half duplex wireless networks