Joint Beamforming, Terminal Scheduling, and Adaptive Modulation with Imperfect CSIT in Rayleigh Fading Correlated Channels with Co-channel Interference
Ref: CISTER-TR-170403 Publication Date: 21 to 25, May, 2017
Joint Beamforming, Terminal Scheduling, and Adaptive Modulation with Imperfect CSIT in Rayleigh Fading Correlated Channels with Co-channel InterferenceRef: CISTER-TR-170403 Publication Date: 21 to 25, May, 2017
This paper presents a joint scheduling, beamforming, and resource allocation algorithm for multi-user wireless networks affected by co-channel interference. The analysis considers a network with one base station (BS) that uses a multiple antenna transmitter (beamformer) to schedule (in a time-division manner) transmissions towards a set of $J$ one-antenna terminals in the presence of $K$ persistent interferers. The transmitter is assumed to employ maximum-ratio combining (MRC) beamforming in the presence of spatially-correlated branches with channel envelopes modelled as Rayleigh-distributed processes. The BS has access to an imperfect (outdated) copy of the instantaneous channel state information (CSI) of each terminal. Based on this CSI at the transmitter side (CSIT), the BS proceeds to select (at each time interval or time-slot) the terminal with the highest channel strength for purposes of transmission. This imperfect CSIT is also used to calculate the coefficients of the beamformer that will be used to transmit information towards the scheduled terminal, as well as for selecting the most appropriate modulation format (threshold-based decision). In addition, the transmission towards each scheduled terminal is assumed to experience persistent co-channel interference that will degrade the quality of the information reception process. The main merits of this work are: 1) the joint analysis of MRC-based beamforming, terminal scheduling based on maximum channel strength, and modulation assignment, and 2) joint modelling of the effects of spatial correlation, co-channel interference and imperfect CSIT.
Accepted in The Second International Conference on Advances in Signal, Image and Video Processing - from Sensing to Applications (SIGNAL 2017), 5G.