We study the problem of channel pairing and power allocation in a multichannel multihop relay network to enhance the end-to-end data rate. Both amplify-and-forward (AF) and decode-and-forward (DF) relaying strategies are considered. Given fixed power allocation to the channels, we show that channel pairing over multiple hops can be decomposed into independent pairing problems at each relay, and a sorted-SNR channel pairing strategy is sum-rate optimal, where each relay pairs its incoming and outgoing channels by their SNR order. For the joint optimization of channel pairing and power allocation under both total and individual power constraints, we show that the problem can be decoupled into two subproblems solved separately. This separation principle is established by observing the equivalence between sorting SNRs and sorting channel gains in the jointly optimal solution. It significantly reduces the computational complexity in finding the jointly optimal solution. It follows that the channel pairing problem in joint optimization can be again decomposed into independent pairing problems at each relay based on sorted channel gains. The solution for optimizing power allocation for DF relaying is also provided, as well as an asymptotically optimal solution for AF relaying. Numerical results are provided to demonstrate substantial performance gain of the jointly optimal solution over some suboptimal alternatives. It is also observed that more gain is obtained from optimal channel pairing than optimal power allocation through judiciously exploiting the variation among multiple channels. Impact of the variation of channel gain, the number of channels, and the number of hops on the performance gain is also studied through numerical examples.
For an OFDM system as a typical example of multi-channel systems, the concept of CP was first introduced independently in @cite_21 and @cite_0 for a dual-hop AF relaying system where heuristic algorithms for pairing based on the order of channel quality were proposed. For relaying without the direct source-destination link available, @cite_21 used integer programming to find the optimal pairing that maximizes the sum SNR. From a system-design perspective, the sorted-SNR CP scheme was proposed in @cite_0 and was shown optimal for the noise-free relaying case, under the assumption of uniform power allocation.
@cite_0 @cite_21
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The combination of a multihop relay system and orthogonal frequency-division multiplexing (OFDM) modulation is a promising way to increase the capacity and coverage area. For the OFDM two-hop relay system with separate power constraints, joint subcarrier matching and power allocation is considered in this paper, which uses the ldquodecode-and-forwardrdquo relay strategy. The aforementioned problem can be formulated as a mixed binary integer programming problem, which is prohibitive when trying to find the global optimum. By separating the subcarrier matching and the power allocation, the optimal scheme, i.e., the optimal joint subcarrier matching and power allocation, is presented in this paper. After that, a suboptimal scheme with less complexity is also proposed, which can also be used to better understand the effects of power allocation. Simulation results show that the capacity of the optimal scheme is almost equivalent to the upper bound of the system capacity, and the capacity of the suboptimal scheme is close to that of the optimal scheme. In addition, simulation results also show that the one-to-one subcarrier matching is almost optimal, although it simplifies the system architecture. In this paper we study the resource allocation problem for the multiuser orthogonal frequency division multiplexing (OFDM)-based cognitive radio (CR) systems with proportional rate constraints. The mutual interference introduced by primary user (PU) and cognitive radio user (also referred to secondary user, SU) makes the optimization problem of CR systems more complex. Moreover, the interference introduced to PUs must be kept under a given threshold. In this paper, the highest achievable rate of each OFDM subchannel is calculated by jointly considering the channel gain and interference level. First, a subchannel is assigned to the SU with the highest achievable rate. The remaining subchannels are always allocated to the SU that suffers the severest unjustness. Second, an efficient bit allocation algorithm is developed to maximize the sum capacity, which is again based on the highest achievable rate of each subchannel. Finally, an adjustment procedure is designed to maintain proportional fairness. Simulation results show that the proposed algorithm maximizes the sum capacity while keeping the proportional rate constraints satisfied. The algorithm exhibits a good tradeoff between sum capacity maximization and proportional fairness. Furthermore, the proposed algorithm has lower complexity compared with other algorithms, rendering it promising for practical applications. Copyright © 2011 John Wiley & Sons, Ltd. (By jointly considering the channel gain and the interference level of the OFDM-based cognitive radio systems, the highest achievable rate of each subchannel can be calculated, which indicates the ability of carrying bits of the subchannel. Using the normalized cost index list, an efficient algorithm is proposed to maximize the sum capacity of the cognitive OFDM systems while keeping the proportional rate constraints satisfied.) We consider a two-hop relaying network in which orthogonal frequency division multiplexing (OFDM) is employed for the source-to-destination, the source-to-relay and the relay- to-destination links. Amplify-and-forward (AF) and decode-and- forward (DF) policies are both discussed with or without two-hop diversity, respectively, for the relaying network with a sum-power constraint. An unified approach is used for optimal power allocation in the four different relaying scenarios. First, equivalent channel gains are developed for any given subcarrier pair in each scenario, and then optimal power allocation can be obtained by applying the classic water-filling method. Moreover, we provide the proof to the optimality of sorted subcarrier pairing for AF and DF relaying without diversity, which, combined with optimal power allocation, can offer further performance gain. We consider multi-hop OFDM relaying systems employing either decode-and-forward (DF) or amplify-and-forward (AF) relaying protocols in this paper. We propose adaptive power allocation (PA) algorithms under joint transmit power constraint at source and relays in order to maximize system capacity with channel state information (CSI) known at all nodes. The paring of subcarriers is also discussed. Simulation results show that the proposed adaptive PA algorithms achieve higher system capacity than uniform PA algorithms. If paring techniques are employed, system capacity can be further enhanced.