This paper proposes two full-digital receive beamforming (BF) methods for low-complexity and high-accuracy uplink signal detection via Gaussian belief propagation (GaBP) at base stations (BSs) adopting massive multi-input multi-output (MIMO) for open radio access network (O-RAN). In addition, beyond fifth generation mobile communication (beyond 5G) systems will increase uplink capacity. In the scenarios such as O-RAN and beyond 5G, it is vital to reduce the cost of the BSs by limiting the bandwidth of fronthaul (FH) links, and the dimensionality reduction of the received signal based on the receive BF at a radio unit is a well-known strategy to reduce the amount of data transported via the FH links. In this paper, we clarify appropriate criteria for designing a BF weight considering the subsequent GaBP signal detection with the proposed methods: singular-value-decomposition-based BF and QR-decomposition-based BF with the aid of discrete-Fourier-transformation-based spreading. Both methods achieve the dimensionality reduction without compromising the desired signal power by taking advantage of a null space of channels. The proposed receive BF methods reduce correlations between the received signals in the BF domain, which improves the robustness of GaBP against spatial correlation among fading coefficients. Simulation results assuming realistic BS and user equipment arrangement show that the proposed methods improve detection capability while significantly reducing the computational cost.

In this paper, two receive beamforming techniques (Method 1 and Method 2) are proposed for a mobile station (MS) with multiple antenna arrays in an OFDM-based millimeter-wave (mm-wave) cellular communication system. Since the MS in mm-wave cellular communication requires fast processing due to its frequent movement and rotation, a receive beamforming technique with reduced computation complexity and processing time is proposed in Method 2. Of particular interest, estimation techniques for 2-dimensional (2D) direction-of-arrivals (DoAs) corresponding to each cell ID are proposed for uniform circular arrays (UCAs) and uniform rectangular arrays (URAs). Also, a cell selection technique for MSs with multiple antenna arrays is described that use the candidate cell IDs and parameters estimated for all antenna arrays to provide combining gain in addition to array gain in multipath channels. The proposed beamforming techniques are evaluated by computer simulation using a simple model of amm-wave cellular communication system with 3-dimensional spatial channel model (3D SCM).