摘要
移动通信近几十年来得到了广泛的研究,为人类社会的发展进步做出了巨大的贡献。尽管如此,电磁波在实际传输中却面临着更为复杂的传播环境。其中多径衰落效应是无线通信质量的最大限制。分集技术可以通过在接收端分别接收多个各自经历独立衰落的信号副本,以对抗信道的衰落。近年来提出的多输入多输出MIMO技术,通过在发射端和接收端放置多天线,形成空间分集,从而提高系统容量和可靠性。但在实际应用中,由于移动终端物理条件的制约限制了空间分集技术的应用。
针对MIMO技术的缺陷,Sendonaris等人提出了协作分集的概念。使得单天线用户能够通过协作通信的方式形成虚拟的MIMIO系统,从而提高了系统性能,并获得了广泛的关注和研究。现有文献多集中于协作分集的性能分析,而伙伴选择问题作为实现协作分集的重要步骤,也是不可忽视的研究方向。本文总结现有文献中关于伙伴问题的解决方法,并针对近年来提出的基于IDMA叠加调制的方式,分析了该方式相对于前文提到的传统协作分集方式所带来的进一步增益。并针对该方式下协作伙伴需要互为中继的限制对传统伙伴选择方式做出了改进,即：用户公平优先算法和纳什谈判解算法。前者基于用户之间公平性的考虑,而后者主要考虑系统级的性能最优和用户节点之间公平性两者的折衷,仿真结果表明这两种算法都获得了预期的效果。
Mobile communications has been extensive research in recent decades, and has made a great contribution to the development and progress of human society. But electromagnetic waves are faced with more complex propagation environment. Multi-path fading effect limits the quality of wireless communications. Diversity technique can separate the independent fading signals at the receiver in order to combat channel fading. MIMO (Multiple Input Multiple Output) technique which was proposed in recent years forms a spatial diversity by placing the multi-antenna in the transmitter and receiver to increase system capacity and reliability. However, in practical applications, the physical conditions in the mobile terminals limit the application of spatial diversity techniques.
Sendonaris proposed the concept of cooperative diversity due to the lack of MIMO technique. It makes single-antenna users to communicate through a cooperative way to create virtual MIMIO system to improve system performance. The existing literature focused more on the cooperative diversity performance analysis, while the partner selection to achieve cooperative diversity as an important step in the cooperative diversity should not be ignored. In this paper, we summarize the existing partner selection algorithm, and then we introduce two traditional resource allocation strategies named Max-Min algorithm and Nash bargaining solution (NBS) algorithm into cooperative networks based on IDMA superposition modulation, which has a special restriction that every two cooperative nodes have to be mutual partners. Considering this restriction, we introduce the New Max-Min algorithm considers the fairness among users in the networks, and the New NBS algorithm considers the tradeoff between system efficiency and fairness among users. Simulation results show that the New Max-Min algorithm can archive higher fairness with the concern of Jain's fairness index, and the New NBS algorithm can archive more fairness within reducing some system-level performance.
引文
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