A New Millimeter Wave MIMO System for 5G Networks

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Abstract

Millimeter Wave (mmWave) band provides a large spectrum to meet the high-demand capacity by the 5th generation (5G) wireless networks. However, to fully exploit the available spectrum, obstacles such as high path loss, channel sparsity, and hardware complexity should be overcome. To this end, the present paper aims to design a new multiple-input multiple-output (MIMO) system using lens-based multi-beam reconfigurable antennas. The proposed MIMO system uses complete lens at the transmitter and incomplete lens at the receiver. To reduce hardware complexity, we utilize an optimal beam selection technique. Our analysis demonstrates that the proposed MIMO system along with the optimal beam selection technique increases the average signal-to-noise ratio (SNR). Also, simulations show that the system achieves full-diversity gain.

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A simple transmit diversity technique for wireless communications

S.M. Alamouti (1998)

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Spatially Sparse Precoding in Millimeter Wave MIMO Systems

Omar Ayach, Sridhar Rajagopal, Shadi Abu-Surra … (2013)

Millimeter wave (mmWave) signals experience orders-of-magnitude more pathloss than the microwave signals currently used in most wireless applications. MmWave systems must therefore leverage large antenna arrays, made possible by the decrease in wavelength, to combat pathloss with beamforming gain. Beamforming with multiple data streams, known as precoding, can be used to further improve mmWave spectral efficiency. Both beamforming and precoding are done digitally at baseband in traditional multi-antenna systems. The high cost and power consumption of mixed-signal devices in mmWave systems, however, make analog processing in the RF domain more attractive. This hardware limitation restricts the feasible set of precoders and combiners that can be applied by practical mmWave transceivers. In this paper, we consider transmit precoding and receiver combining in mmWave systems with large antenna arrays. We exploit the spatial structure of mmWave channels to formulate the precoding/combining problem as a sparse reconstruction problem. Using the principle of basis pursuit, we develop algorithms that accurately approximate optimal unconstrained precoders and combiners such that they can be implemented in low-cost RF hardware. We present numerical results on the performance of the proposed algorithms and show that they allow mmWave systems to approach their unconstrained performance limits, even when transceiver hardware constraints are considered.