Joint Channel Estimation and Beamforming for Millimeter Wave Cellular System

Abstract

In this paper, we propose a joint channel estimation and beamforming (BF) scheme for the wide band millimeter wave (mmWave) cellular system. Specifically, low complexity compressive sensing (CS) based estimation algorithm is used to estimate the sparse mmWave channels. Based on the estimated channel, low complexity BF scheme is proposed to adapt to the channel for data communications. The algorithm is designed by considering the practical hardware and channel constraints. Furthermore, the complexity is very low without matrix inverse and singular value decomposition (SVD) compared with traditional algorithms, which is well suitable to practical realization. Finally, we show by simulations that the performance of proposed scheme is close to the optimal scheme with extremely less overhead.

Effect of Wideband Beam Squint on Codebook Design in Phased-Array Wireless Systems

“…Beamforming with a phased array having a large number of antennas is a promising approach to compensate for higher attenuation at mmWave frequencies while supporting mobile applications [4]- [6]. First, the short wavelength of mmWave allows for integration of a large number of antennas into This work has been supported by Huawei Technologies Co., Ltd. a phased array of small size suitable for a mobile wireless device.…”

Beam Designs for Millimeter-Wave Backhaul With Dual-Polarized Uniform Planar Arrays

“…The array response vectors in (8) and (9) are normalized with M tx,h and M tx,v , respectively. The dimension of Kronecker product of these two vectors, which represents the single-polarization UPA structure in (7), is doubled by the Kronecker product in (6) to model the dualpolarization UPA structure. To normalize this doubling effect for both Tx and Rx parts in the channel gain, we need to have the normalization constant 2 2 in (5).…”

“…MmWave communications use a carrier frequency of 30 to 300 GHz and the corresponding wavelength of 1 to 10 mm. With its huge bandwidth, mmWave communications can support enormous data rates [5]- [7]. An important characteristic of mmWave systems is its high attenuation [7], [8], which requires sharp beam patterns to concentrate signal power and compensate for the attenuation.…”

“…With its huge bandwidth, mmWave communications can support enormous data rates [5]- [7]. An important characteristic of mmWave systems is its high attenuation [7], [8], which requires sharp beam patterns to concentrate signal power and compensate for the attenuation. To enjoy the benefit of the large bandwidth, hence, beamforming techniques are necessary to overcome harsh mmWave environments.…”

“…Considering the use of numerous antennas in mmWave systems, the digital beamforming is practically infeasible due to the cost and power consumption of RF chains [19]- [21]. One feasible solution is the analog beamforming, which requires only one RF chain in return for abandonment of amplitude control and variety of beam pattern shapes [2], [7]. The hybrid beamforming, which reduces the use of RF chains by conjoining the digital and analog beamformings, is another practical solution to accomplish both the feasibility and diversity of beam pattern shapes [13], [15]- [18], [22]- [26].…”