School of Electronic Information Engineering, Tianjin University, Nankai District, Tianjin 300072, China.
Sensors (Basel). 2013 Aug 9;13(8):10306-32. doi: 10.3390/s130810306.
The paper presents a joint subcarrier-pair based resource allocation algorithm in order to improve the efficiency and fairness of cooperative multiuser orthogonal frequency division multiplexing (MU-OFDM) cognitive radio (CR) systems. A communication model where one source node communicates with one destination node assisted by one half-duplex decode-and-forward (DF) relay is considered in the paper. An interference-limited environment is considered, with the constraint of transmitted sum-power over all channels and aggregate average interference towards multiple primary users (PUs). The proposed resource allocation algorithm is capable of maximizing both the system transmission efficiency and fairness among secondary users (SUs). Besides, the proposed algorithm can also keep the interference introduced to the PU bands below a threshold. A proportional fairness constraint is used to assure that each SU can achieve a required data rate, with quality of service guarantees. Moreover, we extend the analysis to the scenario where each cooperative SU has no channel state information (CSI) about non-adjacent links. We analyzed the throughput and fairness tradeoff in CR system. A detailed analysis of the performance of the proposed algorithm is presented with the simulation results.
本文提出了一种基于联合子载波对的资源分配算法，以提高协作多用户正交频分复用（MU-OFDM）认知无线电（CR）系统的效率和公平性。本文考虑了一种通信模型，其中一个源节点由一个半双工解码转发（DF）中继辅助与一个目的节点进行通信。在考虑传输总功率和多个主用户（PU）的总平均干扰的约束条件下，本文考虑了一个受干扰限制的环境。所提出的资源分配算法能够最大化系统传输效率和次级用户（SU）之间的公平性。此外，该算法还可以将引入到 PU 频带的干扰保持在阈值以下。使用比例公平约束来确保每个 SU 都能达到所需的数据速率，并保证服务质量。此外，我们将分析扩展到每个协作 SU 都没有关于非相邻链路的信道状态信息（CSI）的场景。我们分析了 CR 系统中的吞吐量和公平性权衡。通过仿真结果给出了所提出算法的性能详细分析。
