This paper studies a downlink massive multiuser multiple-input multiple-output system with PSK modulation, where the base station employs 1-bit digital-to-analog converters (DACs). We first exploit the concept of cons...
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ISBN:
(纸本)9781665427722
This paper studies a downlink massive multiuser multiple-input multiple-output system with PSK modulation, where the base station employs 1-bit digital-to-analog converters (DACs). We first exploit the concept of constructive interference (CI) to express the received PSK signal in terms of the coordinate vector. With the coordinate vector, we construct a nonlinear mapping (NM) function in which the function value is small when the coordinate coefficient is large. Then we present a low-complexity NM-MinSum algorithm to solve a single-objective optimization problem which minimizes the sum of the NM function of the coordinate vector. Further, we propose a two-objective optimization problem and develop the NM-DualMax algorithm to find its solution. The numerical results show the proposed algorithms achieve comparable performance to the existing nonlinear precoding approaches.
The power consumption of digital-to-analog converters (DACs) constitutes a significant proportion of the total power consumption in a massive multiuser multiple-input multiple-output (MU-MIMO) base station (BS). Using...
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The power consumption of digital-to-analog converters (DACs) constitutes a significant proportion of the total power consumption in a massive multiuser multiple-input multiple-output (MU-MIMO) base station (BS). Using 1-bit DACs can significantly reduce the power consumption. This paper addresses the precoding problem for the massive narrow-band MU-MIMO downlink system equipped with 1-bit DACs at each BS. In such a system, the preceding problem plays a central role as the preceded symbols are affected by extra distortion introduced by 1-bit DACs. In this paper, we develop a highly efficient nonlinear preaxling algorithm based on the alternative direction method framework. Unlike the classic algorithms, such as the semidefinite relaxation (SDR) and squared-infinity norm Douglas-Rachford splitting (SQUID) algorithms, which solve convex relaxed versions of the original precoding problem, the new algorithm solves the original nonconvex problem directly. The new algorithm is guaranteed to globally converge under some mild conditions. A sufficient condition for its convergence has been derived. The experimental results in various conditions demonstrated that the new algorithm can achieve the state-of-the-art performance comparable with the SDR algorithm while being much more efficient (e.g., more than 300 times faster than the SDR algorithm).
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