Multi-Cell Massive MIMO in LoS

We consider a multi-cell Massive MIMO system in a line-of-sight (LoS) propagation environment, for which each user is served by one base station, with no cooperation among the base stations. Each base station knows the channel between its service antennas and its users, and uses these channels for precoding and decoding. Under these assumptions we derive explicit downlink and uplink effective SINR formulas for maximum-ratio (MR) processing and zero-forcing (ZF) processing. We also derive formulas for power control to meet pre-determined SINR targets. A numerical example demonstrating the usage of the derived formulas is provided.Comment: IEEE Global Communications Conference (GLOBECOM) 201

Interference in Multi-beam Antenna System of 5G Network

Massive multiple-input-multiple-output (MIMO) and beamforming are key technologies, which significantly influence on increasing effectiveness of emerging fifth-generation (5G) wireless communication systems, especially mobile-cellular networks. In this case, the increasing effectiveness is understood mainly as the growth of network capacity resulting from better diversification of radio resources due to their spatial multiplexing in macro- and micro-cells. However, using the narrow beams in lieu of the hitherto used cell-sector brings occurring interference between the neighboring beams in the massive-MIMO antenna system, especially, when they utilize the same frequency channel. An analysis of this effect is the aim of this paper. In this case, it is based on simulation studies, where a multi-elliptical propagation model and standard 3GPP model are used. We present the impact of direction and width of the neighboring beams of 5G new radio gNodeB base station equipped with the multi-beam antenna system on the interference level between these beams. The simulations are carried out for line-of-sight (LOS) and non-LOS conditions of a typical urban environment

Spectral Efficiency Analysis of Multi-Cell Massive MIMO Systems with Ricean Fading

This paper investigates the spectral efficiency of multi-cell massive multiple-input multiple-output systems with Ricean fading that utilize the linear maximal-ratio combining detector. We firstly present closed-form expressions for the effective signal-to-interference-plus-noise ratio (SINR) with the least squares and minimum mean squared error (MMSE) estimation methods, respectively, which apply for any number of base-station antennas $M$ and any Ricean $K$-factor. Also, the obtained results can be particularized in Rayleigh fading conditions when the Ricean $K$-factor is equal to zero. In the following, novel exact asymptotic expressions of the effective SINR are derived in the high $M$ and high Ricean $K$-factor regimes. The corresponding analysis shows that pilot contamination is removed by the MMSE estimator when we consider both infinite $M$ and infinite Ricean $K$-factor, while the pilot contamination phenomenon persists for the rest of cases. All the theoretical results are verified via Monte-Carlo simulations.Comment: 15 pages, 2 figures, the tenth International Conference on Wireless Communications and Signal Processing (WCSP 2018), to appea

MmWave Massive MIMO Based Wireless Backhaul for 5G Ultra-Dense Network

Ultra-dense network (UDN) has been considered as a promising candidate for future 5G network to meet the explosive data demand. To realize UDN, a reliable, Gigahertz bandwidth, and cost-effective backhaul connecting ultra-dense small-cell base stations (BSs) and macro-cell BS is prerequisite. Millimeter-wave (mmWave) can provide the potential Gbps traffic for wireless backhaul. Moreover, mmWave can be easily integrated with massive MIMO for the improved link reliability. In this article, we discuss the feasibility of mmWave massive MIMO based wireless backhaul for 5G UDN, and the benefits and challenges are also addressed. Especially, we propose a digitally-controlled phase-shifter network (DPSN) based hybrid precoding/combining scheme for mmWave massive MIMO, whereby the low-rank property of mmWave massive MIMO channel matrix is leveraged to reduce the required cost and complexity of transceiver with a negligible performance loss. One key feature of the proposed scheme is that the macro-cell BS can simultaneously support multiple small-cell BSs with multiple streams for each smallcell BS, which is essentially different from conventional hybrid precoding/combining schemes typically limited to single-user MIMO with multiple streams or multi-user MIMO with single stream for each user. Based on the proposed scheme, we further explore the fundamental issues of developing mmWave massive MIMO for wireless backhaul, and the associated challenges, insight, and prospect to enable the mmWave massive MIMO based wireless backhaul for 5G UDN are discussed.Comment: This paper has been accepted by IEEE Wireless Communications Magazine. This paper is related to 5G, ultra-dense network (UDN), millimeter waves (mmWave) fronthaul/backhaul, massive MIMO, sparsity/low-rank property of mmWave massive MIMO channels, sparse channel estimation, compressive sensing (CS), hybrid digital/analog precoding/combining, and hybrid beamforming. http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=730653