Traffic-Aware Training and Scheduling in MISO Downlink Systems
Résumé
In this paper, the problem of feedback and active user selection in 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the queue state information and the users contend for the channel in a CSMA-based manner with parameters based on the outdated queue state information and real-time channel state information are calculated analytically. We show that, using infrequent signaling between the base station and the users, the decentralized policies outperforms the centralized policy. In addition a threshold-based user selection and training schemes for discrete-time contention is proposed. The results of this work 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.