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Traffic-Aware Training and Scheduling for MISO Wireless Downlink Systems

机译：MISO无线下行链路系统的流量感知培训和计划

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摘要

In this paper, the problem of feedback and active user selection in multiple-input single-output (MISO) wireless systems such that the system’s stability region is as big as possible is examined. The focus is on a system in a Rayleigh fading environment where zero forcing precoding is used to serve all active users in every slot. Acquisition of the channel states is done via uplink training in time division duplexing mode by the active users. Clearly, only a subset of users can perform uplink training and the selection of this subset is a challenging and interesting problem especially in MISO systems. The stability regions of a baseline centralized scheme and two novel decentralized policies are examined analytically. In the decentralized schemes, the transmitter broadcasts periodically the queue state information and the users contend for the channel in a carrier sense multiple access-based manner with parameters based on the outdated queue state information and real-time channel state information. We show that, using infrequent signaling between the base station and the users, the decentralized policies outperform the centralized policy. In addition, a threshold-based user selection and training scheme for discrete-time contention is proposed. The results of this paper imply that, as far as stability is concerned, the users must be involved in the active user selection and feedback/training decision. This should be leveraged in future communication systems.
机译：本文研究了多输入单输出（MISO）无线系统中反馈和主动用户选择的问题，即系统的稳定区域尽可能大。重点是瑞利衰落环境中的系统，其中零强制预编码用于为每个时隙中的所有活动用户提供服务。活动用户通过时分双工模式的上行链路训练来完成信道状态的获取。显然，只有一部分用户可以执行上行链路训练，而选择该子集是一个具有挑战性和有趣的问题，尤其是在MISO系统中。基线集中方案和两个新的分散策略的稳定区域进行了分析性检查。在分散方案中，发送器周期性地广播队列状态信息，并且用户以基于载波侦听多路访问的方式竞争信道，并且具有基于过时队列状态信息和实时信道状态信息的参数。我们表明，使用基站和用户之间的不频繁信令，分散策略要优于集中策略。另外，提出了基于阈值的离散时间竞争用户选择和训练方案。本文的结果暗示，就稳定性而言，用户必须参与主动的用户选择和反馈/培训决策。在未来的通信系统中应该利用这一点。

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