Abstract
Abstract We consider a large-scale MIMO system operating in the 60 GHz band employing beamforming for high-speed data transmission. We assume that the number of RF chains is smaller than the number of antennas, which motivates the use of antenna selection to exploit the beamforming gain afforded by the large-scale antenna array. However, the system constraint that at the receiver, only a linear combination of the receive antenna outputs is available, which together with the large dimension of the MIMO system makes it challenging to devise an efficient antenna selection algorithm. By exploiting the strong line-of-sight property of the 60 GHz channels, we propose an iterative antenna selection algorithm based on discrete stochastic approximation that can quickly lock onto a near-optimal antenna subset. Moreover, given a selected antenna subset, we propose an adaptive transmit and receive beamforming algorithm based on the stochastic gradient method that makes use of a low-rate feedback channel to inform the transmitter about the selected beams. Simulation results show that both the proposed antenna selection and the adaptive beamforming techniques exhibit fast convergence and near-optimal performance.
Highlights
The 60 GHz millimeter wave communication has received significant recent attention, and it is considered as a promising technology for short-range broadband wireless transmission with data rate up to multi-giga bits/s [1-4]
By exploiting the strong line-of-sight property of the 60 GHz channel, we propose a low-complexity iterative antenna selection technique based on the Gerschgorin circle and the stochastic approximation algorithm
One constraint of the system under consideration is that the receiver can only access a linear combination of the receive antenna outputs, which makes the traditional antenna selection schemes based on the channel matrix not applicable
Summary
The 60 GHz millimeter wave communication has received significant recent attention, and it is considered as a promising technology for short-range broadband wireless transmission with data rate up to multi-giga bits/s [1-4]. Given the selected antenna subset, we propose a stochastic gradientbased adaptive transmit and receive beamforming algorithm that makes use of a low-rate feedback channel to inform the transmitter about the selected beam. For the short wavelength, it is reasonable to assume that the size of antenna array is much smaller than the size of the communication area, which leads to a similar geographic information for all links It naturally accounts for the strong and neardeterministic LOS component and the independent realizations from reflection paths in modeling the overall channel response. Our problem is to compute the optimal antenna set ωand the corresponding transmit and receiver beamformers w and u for a ray-traced MIMO channel realization H. Once the antenna subset ω is selected, in the second stage, we iteratively update the transmit and receive beamformers w and u using a stochastic gradient algorithm. In the two sections, we discuss the detailed algorithms for antenna selection and beamformer adaptation, respectively
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