On Optimizing Feedback-Rate Allocation for Downlink MIMO-NOMA With Quantized CSIT

Abstract

We consider multiple-input multiple output (MIMO) non-orthogonal multiple access (NOMA) downlink channels with zeroforcing beamforming transmission. The base station has multiple transmit antennas while all mobile devices have single receive antenna. With a limited feedback rate, channel direction information (CDI) needs to be quantized and fed back from mobile users to a base station. Thus, the accuracy of the quantized channel state information at the transmitter (CSIT) will depend on the feedback rate. To increase spectral efficiency, 2 active users in some clusters share the same beamforming vector and thus, will interfere fully with each other. Given a total-feedback rate, we analyze the feedback allocation for clusters with single active user and 2 active users. The objective is to either minimize the maximum outage probability or maximize the minimum rate among all active users in a cell. We show that the proposed feedback allocation is close to the optimum. Some numerical examples show that the resulting rate performance with the proposed feedback allocation is increased by 100% over that with the uniform feedback allocation. Index Terms-Non-orthogonal multiple access (NOMA), multiple-input multiple-output (MIMO), channel state information at transmitter (CSIT), random vector quantization (RVQ), zeroforcing, beamforming, feedback.

Optimal Transmit Power and Channel-Information Bit Allocation With Zeroforcing Beamforming in MIMO-NOMA and MIMO-OMA Downlinks

“…To reduce the number of optimizing variables, grouping of user pairs is proposed for the allocation. The proposed user-grouping scheme can support any number of user groups and hence, generalizes our previous scheme [24] in which only 2 groups of users were considered and only the CDI rate was optimized.…”

“…Assuming perfect CSI, several existing works [11]- [18, and references therein] studied beamforming design, power allocation, and user clustering for MIMO-NOMA. However, CSI errors incurred by quantizing with a finite number of bits or by estimating the channels can have an adverse effect on the system performance [8], [19]- [24].…”

“…For power-domain MIMO-NOMA, recent works focused on imperfect CSI or finite CSI quantization rate in conjunction with transmit power allocation [19]- [22], [24]- [29].…”

“…Other studies examined different objectives besides maximizing the sum rate. In our previous work [24], the allocation of CDI rates between 2 groups of users was optimized for a given total CDI rate to attain max-min fairness on either achievable rate or outage probability. In [22], power allocation and beamforming vectors were jointly optimized under some outage constraints to maximize the sum of user's utility, which is a function of the rate.…”

Joint Optimization of IRS Beamforming and Transmit Power for MIMO-NOMA Downlink With Statistical Channel Information

“…Non-orthogonal multiple access (NOMA) can provide massive connectivity necessary for next-generation networks [1]. For power-domain NOMA, multiple users in a cluster can transmit in the same frequency-time-space resource block, but are distinguished by proper power allocation [2]. The performance depends on the state of the channels.…”