The power consumption of digital-to-analog converters (DACs) constitutes a significant proportion of the total power consumption in a massivemultiusermultiple-inputmultiple-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 massivemultiusermultiple-inputmultiple-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).
massivemulti-user (MU) multiple-inputmultiple-output (MIMO) will be a core tech- nology in future cellular communication systems. In massive MU-MIMO systems, the number of antennas at the base station (BS) is scaled...
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massivemulti-user (MU) multiple-inputmultiple-output (MIMO) will be a core tech- nology in future cellular communication systems. In massive MU-MIMO systems, the number of antennas at the base station (BS) is scaled up by several orders of magnitude compared to traditional multi-antenna systems with the goals of enabling large gains in capacity and energy efficiency. However, scaling up the number of active antenna elements at the BS will lead to significant increases in power consumption and system costs unless power-efficient and low-cost hardware components are used. In this thesis, we investigate the performance of massive MU-MIMO systems for the case when the BS is equipped with low-resolution data converters. First, we consider the massive MU-MIMO uplink for the case when the BS uses low- resolution analog-to-digital converters (ADCs) to convert the received signal into the dig- ital domain. Our focus is on the case where neither the transmitter nor the receiver have any a priori channel state information (CSI), which implies that the channel realizations have to be learned through pilot transmission followed by BS-side channel estimation, based on coarsely quantized observations. We derive a low-complexity channel estimator and present lower bounds and closed-form approximations for the information-theoretic rates achievable with the proposed channel estimator together with conventional linear detection algorithms. Second, we consider the massive MU-MIMO downlink for the case when the BS uses low-resolution digital-to-analog converters (DACs) to generate the transmit signal. We derive lower bounds and closed-form approximations for the achievable rates with linear precoding under the assumption that the BS has access to perfect CSI. We also propose novel nonlinear precoding algorithms that are shown to significantly outperform linear precoding for the extreme case of 1-bit DACs. Specifically, for the case of symbol-rate 1-bit DACs and frequency-flat channels
massivemultiuser (MU) multiple-inputmultiple-output (MIMO) is foreseen to be one of the key technologies in fifth-generation wireless communication systems. In this paper, we investigate the problem of downlink prec...
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massivemultiuser (MU) multiple-inputmultiple-output (MIMO) is foreseen to be one of the key technologies in fifth-generation wireless communication systems. In this paper, we investigate the problem of downlink precoding for a narrow-band massive MU-MIMO system with low-resolution digital-to-analog converters (DACs) at the base station (BS). We analyze the performance of linear precoders, such as maximal-ratio transmission and zero-forcing, subject to coarse quantization. Using Bussgang's theorem, we derive a closed-form approximation on the rate achievable under such coarse quantization. Our results reveal that the performance attainable with infinite-resolution DACs can be approached using DACs having only 3-4 bits of resolution, depending on the number of BS antennas and the number of user equipments (UEs). For the case of 1-bit DACs, we also propose novel nonlinear precoding algorithms that significantly outperform linear precoders at the cost of an increased computational complexity. Specifically, we show that nonlinear precoding incurs only a 3 dB penalty compared with the infinite-resolution case for an uncoded bit-error rate of 10-3, in a system with 128 BS antennas that uses 1-bit DACs and serves 16 single-antenna UEs. In contrast, the penalty for linear precoders is about 8 dB.
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