Spectral-efficient hybrid precoding for multi-antenna multi-user mmWave massive MIMO systems with low complexity

Abstract

Millimeter-wave (mmWave) massive multiple-input multiple-output (MIMO) systems allow for a data transmission rate of gigabits per second owing to the large bandwidth available in the mmWave spectrum and the antenna gains provided by the massive MIMO system. However, hybrid precoding with high complexity and low spectral efficiency cannot address the challenge of high cost and power consumption of RF chains of multi-user systems. In this paper, we propose a low-complexity hybrid precoding scheme for downlink multi-antenna multi-user mmWave massive MIMO systems, aiming to enhance the sum spectral efficiency (SSE) performance. We first extend the dimension of the analog precoding matrix into a square matrix and find the optimal analog combiner by selecting some of the discrete Fourier transform (DFT) bases, which enhances the equivalent baseband channel matrix gain. Then, we directly aggregate the channel gain through the equal gain transmission (EGT) method to ensure the frequency efficiency performance. Finally, we propose an improved BD scheme to design the digital precoder and combiner to reduce the inter-user interference. We consider both the mmWave channel and the Rayleigh channel to evaluate the performance of the proposed algorithm. The simulation results verify that the proposed scheme enjoys near-optimal achievable sum spectrum efficiency and BER performance in both the mmWave channel and Rayleigh channel and performs even better in Rayleigh channel than in the mmWave channel.

Improving 6G Network Spectrum Efficiency with Non-Cooperative and Cooperative Spectrum Sharing Using NOMA and Massive-MIMO

“…The purpose of this action was to mitigate any conflicts and disruptions among users. The simulation findings demonstrate that the suggested technique achieves a cumulative SE and BER performance that is close to ideal in both the mm-Wave and Rayleigh channels [25].…”

Mmwave massive MIMO: one joint beam selection combining cuckoo search and ant colony optimization

“…It is worth noting that the dimension of the solution in ( 5) is smaller than that of (4) (i.e., the dimension of F is smaller than the dimension of B ), which can effectively reduce the search complexity compared with solving (4) directly. In order to solve (5), this paper proposes a CSACO algorithm to select beams simultaneously for all IUs. For user k ∈ G IU , the key idea is to select the Card(B IU ) = K − Card(B NIU ) beams by the proposed CSACO algorithm.…”

“…, I 1,Q . In the proposed CSACO algorithm, the key idea is to find a suitable I best by updating P to solve (5). The flow diagram of the proposed CSACO algorithm is shown as Fig.…”

“…In millimeter-wave (mmWave) massive multi-input multi-output (MIMO) systems [1,2], each beam corresponds to a single radio-frequency (RF) chain. For reducing hardware cost and energy consumption, beam selection has become one of the key techniques to reduce the number of RF chains [3][4][5]. The traditional magnitude maximization (MM) beam selection [6] assigns the beam with the largest power for each user directly, which may cause one beam to be selected for multiple users simultaneously, resulting in the inter-user interference.…”