1 research outputs found
Learning-based Rate Adaptation for Uplink Massive MIMO Networks with Cooperative Data-Assisted Detection
In this paper, the uplink adaptation for massive
multiple-input-multiple-output (MIMO) networks without the knowledge of user
density is considered. Specifically, a novel cooperative uplink transmission
and detection scheme is first proposed for massive MIMO networks, where each
uplink frame is divided into a number of data blocks with independent coding
schemes and the following blocks are decoded based on previously detected data
blocks in both service and neighboring cells. The asymptotic
signal-to-interference-plus-noise ratio (SINR) of the proposed scheme is then
derived, and the distribution of interference power considering the randomness
of the users' locations is proved to be Gaussian. By tracking the mean and
variance of interference power, an online robust rate adaptation algorithm
ensuring a target packet outage probability is proposed for the scenario where
the interfering channel and the user density are unknown.Comment: 9 pages, 5 figures, extended conference versio