Hybrid MIMO Architectures for Millimeter Wave Communications: Phase Shifters or Switches?

Hybrid analog/digital MIMO architectures were recently proposed as an alternative for fully-digitalprecoding in millimeter wave (mmWave) wireless communication systems. This is motivated by the possible reduction in the number of RF chains and analog-to-digital converters. In these architectures, the analog processing network is usually based on variable phase shifters. In this paper, we propose hybrid architectures based on switching networks to reduce the complexity and the power consumption of the structures based on phase shifters. We define a power consumption model and use it to evaluate the energy efficiency of both structures. To estimate the complete MIMO channel, we propose an open loop compressive channel estimation technique which is independent of the hardware used in the analog processing stage. We analyze the performance of the new estimation algorithm for hybrid architectures based on phase shifters and switches. Using the estimated, we develop two algorithms for the design of the hybrid combiner based on switches and analyze the achieved spectral efficiency. Finally, we study the trade-offs between power consumption, hardware complexity, and spectral efficiency for hybrid architectures based on phase shifting networks and switching networks. Numerical results show that architectures based on switches obtain equal or better channel estimation performance to that obtained using phase shifters, while reducing hardware complexity and power consumption. For equal power consumption, all the hybrid architectures provide similar spectral efficiencies.Comment: Submitted to IEEE Acces

Robust massive MIMO Equilization for mmWave systems with low resolution ADCs

Leveraging the available millimeter wave spectrum will be important for 5G. In this work, we investigate the performance of digital beamforming with low resolution ADCs based on link level simulations including channel estimation, MIMO equalization and channel decoding. We consider the recently agreed 3GPP NR type 1 OFDM reference signals. The comparison shows sequential DCD outperforms MMSE-based MIMO equalization both in terms of detection performance and complexity. We also show that the DCD based algorithm is more robust to channel estimation errors. In contrast to the common believe we also show that the complexity of MMSE equalization for a massive MIMO system is not dominated by the matrix inversion but by the computation of the Gram matrix.Comment: submitted to WCNC 2018 Workshop

On the Performance of MRC Receiver with Unknown Timing Mismatch-A Large Scale Analysis

There has been extensive research on large scale multi-user multiple-input multiple-output (MU-MIMO) systems recently. Researchers have shown that there are great opportunities in this area, however, there are many obstacles in the way to achieve full potential of using large number of receive antennas. One of the main issues, which will be investigated thoroughly in this paper, is timing asynchrony among signals of different users. Most of the works in the literature, assume that received signals are perfectly aligned which is not practical. We show that, neglecting the asynchrony can significantly degrade the performance of existing designs, particularly maximum ratio combining (MRC). We quantify the uplink achievable rates obtained by MRC receiver with perfect channel state information (CSI) and imperfect CSI while the system is impaired by unknown time delays among received signals. We then use these results to design new algorithms in order to alleviate the effects of timing mismatch. We also analyze the performance of introduced receiver design, which is called MRC-ZF, with perfect and imperfect CSI. For performing MRC-ZF, the only required information is the distribution of timing mismatch which circumvents the necessity of time delay acquisition or synchronization. To verify our analytical results, we present extensive simulation results which thoroughly investigate the performance of the traditional MRC receiver and the introduced MRC-ZF receiver

Spatial Multiplexing of QPSK Signals with a Single Radio: Antenna Design and Over-the-Air Experiments

The paper describes the implementation and performance analysis of the first fully-operational beam-space MIMO antenna for the spatial multiplexing of two QPSK streams. The antenna is composed of a planar three-port radiator with two varactor diodes terminating the passive ports. Pattern reconfiguration is used to encode the MIMO information onto orthogonal virtual basis patterns in the far-field. A measurement campaign was conducted to compare the performance of the beam-space MIMO system with a conventional 2-by-?2 MIMO system under realistic propagation conditions. Propagation measurements were conducted for both systems and the mutual information and symbol error rates were estimated from Monte-Carlo simulations over the measured channel matrices. The results show the beam-space MIMO system and the conventional MIMO system exhibit similar finite-constellation capacity and error performance in NLOS scenarios when there is sufficient scattering in the channel. In comparison, in LOS channels, the capacity performance is observed to depend on the relative polarization of the receiving antennas.Comment: 31 pages, 23 figure

Signal Processing and Learning for Next Generation Multiple Access in 6G

Wireless communication systems to date primarily rely on the orthogonality of resources to facilitate the design and implementation, from user access to data transmission. Emerging applications and scenarios in the sixth generation (6G) wireless systems will require massive connectivity and transmission of a deluge of data, which calls for more flexibility in the design concept that goes beyond orthogonality. Furthermore, recent advances in signal processing and learning have attracted considerable attention, as they provide promising approaches to various complex and previously intractable problems of signal processing in many fields. This article provides an overview of research efforts to date in the field of signal processing and learning for next-generation multiple access, with an emphasis on massive random access and non-orthogonal multiple access. The promising interplay with new technologies and the challenges in learning-based NGMA are discussed