Spatio-Radio Resource Management and Hybrid Beamforming for Limited Feedback Massive MIMO Systems

Abstract

In this paper, a joint spatio–radio frequency resource allocation and hybrid beamforming scheme for the massive multiple-input multiple-output (MIMO) systems is proposed. We consider limited feedback two-stage hybrid beamformimg for decomposing the precoding matrix at the base-station. To reduce the channel state information (CSI) feedback of massive MIMO, we utilize the channel covariance-based RF precoding and beam selection. This beam selection process minimizes the inter-group interference. The regularized block diagonalization can mitigate the inter-group interference, but requires substantial overhead feedback. We use channel covariance-based eigenmodes and discrete Fourier transforms (DFT) to reduce the feedback overhead and design a simplified analog precoder. The columns of the analog beamforming matrix are selected based on the users’ grouping performed by the K-mean unsupervised machine learning algorithm. The digital precoder is designed with joint optimization of intra-group user utility function. It has been shown that more than 50 % feedback overhead is reduced by the eigenmodes-based analog precoder design. The joint beams, users scheduling and limited feedbacK-based hybrid precoding increases the sum-rate by 27 . 6 % compared to the sum-rate of one-group case, and reduce the feedback overhead by 62 . 5 % compared to the full CSI feedback.

Iterative Analog–Digital Multi-User Equalizer for Wideband Millimeter Wave Massive MIMO Systems

“…d,k,r−1 is set to its optimum value accordingly to optimization problem (22), i.e.,W (24). Replacing (27) in (19), the problem (22) simplifies to…”

“…The update of the digital component needs the inversion of a U × U matrix, and therefore has complexity O(U 3 ). The computation of the analog component requires the evaluation of the metric in (27) for all elements of the codebook F a . The complexity of a matrix-vector product of sizes U × N rx and N rx , respectively, is O(N rx U).…”

“…This approach was then extended to the partially connected case, and a novel technique that dynamically constructs the hybrid subarrays knowing the long-term channel characteristics was proposed. Recently, solutions for wideband mmWave multi-user downlink massive MIMO-OFDM systems were proposed in [26], and for uplink in [27][28][29][30][31]. Hybrid precoders for downlink OFDM wideband mMIMO systems, aimed at minimizing the total transmit power of the base station, subject to both the coverage constraint of signaling and data rate requirements of users were proposed in [26].…”

“…Hybrid precoders for downlink OFDM wideband mMIMO systems, aimed at minimizing the total transmit power of the base station, subject to both the coverage constraint of signaling and data rate requirements of users were proposed in [26]. The authors of [27] designed a joint spatio-radio resource and three hybrid precoding algorithms for systems with limited feedback: (1) a hybrid precoder with user-beam selection to maximize the sum proportional rate; (2) a low complexity suboptimal solution using limited statistical channel state information (CSI) feedback; (3) a k-mean algorithm based on an unsupervised machine learning scheme. In [28], a hybrid linear equalizer for sub-connected hybrid architectures that minimizes the average BER over all the subcarriers was designed.…”

Massive MIMO Systems: Present and Future

“…In millimeter-wave communication, almost line-of-sight (LoS) channel or Ricean fading channel is expected. Exploiting CSI of the LoS component, spectral efficiency of equal gain transmission and combining (EGT/EGC) was analyzed in Ricean fading frequency selective fading channel with cooperative relaying scenarios [16]. Such relaying approach is also effective in heterogeneous network where small cell BSs play a role of relay the macro cell BS and user terminals.…”