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1. Linear One-Bit Precoding in Massive MIMO: Asymptotic SEP Analysis and Optimization

   https://doi.org/10.1109/SPAWC53906.2023.10304450  

   Wu, Zheyu; Ma, Junjie; Liu, Ya-Feng; Swindlehurst, A Lee (September 2023, IEEE)

   This paper focuses on the analysis and optimization of a class of linear one-bit precoding schemes for a downlink massive MIMO system under Rayleigh fading channels. The considered class of linear one-bit precoding is fairly general, including the well-known matched filter (MF) and zero-forcing (ZF) precoding schemes as special cases. Our analysis is based on an asymptotic framework where the numbers of transmit antennas and users in the system grow to infinity with a fixed ratio. We show that, under the asymptotic assumption, the symbol error probability (SEP) of the considered linear one-bit precoding schemes converges to that of a scalar “signal plus independent Gaussian noise” model. This result enables us to provide accurate predictions for the SEP of linear one-bit precoding. Additionally, we also derive the optimal linear one-bit precoding scheme within the considered class based on our analytical results. Simulation results demonstrate the excellent accuracy of the SEP prediction and the optimality of the derived precoder. 

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2. Block-Level MU-MISO Interference Exploitation Precoding: Optimal Structure and Explicit Duality

   https://doi.org/10.1109/JIOT.2024.3438569  

   Yang, Junwen; Li, Ang; Liao, Xuewen; Masouros, Christos; Swindlehurst, A Lee (November 2024, IEEE Internet of Things Journal)

   This article investigates block-level interference exploitation (IE) precoding for multiuser multiple-input-single-output (MU-MISO) downlink systems. To overcome the need for symbol-level IE precoding to frequently update the precoding matrix, we propose to jointly optimize all the precoders or transmit signals within a transmission block. The resultant precoders only need to be updated once per block, and while not necessarily constant over all the symbol slots, we refer to the technique as block-level slot-variant IE precoding. Through a careful examination of the optimal structure and the explicit duality inherent in block-level power minimization (PM) and signal-to-interference-plus-noise ratio (SINR) balancing (SB) problems, we discover that the joint optimization can be decomposed into subproblems with smaller variable sizes. As a step further, we propose block-level slot-invariant IE precoding by adding a structural constraint on the slot-variant IE precoding to maintain a constant precoder throughout the block. A novel linear precoder for IE is further presented, and we prove that the proposed slot-variant and slot-invariant IE precoding share an identical solution when the number of symbol slots does not exceed the number of users. Numerical simulations demonstrate that the proposed precoders achieve a significant complexity reduction compared against benchmark schemes, without sacrificing performance. 

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3. Sparse Linear Precoders For Mitigating Nonlinearities In Massive MIMO

   https://doi.org/10.1109/SSP49050.2021.9513791  

   Mezghani, Amine; Plabst, Daniel; Swindlehurst, Lee A.; Fijalkow, Inbar; Nossek, Josef A. (July 2021, IEEE Statistical Signal Processing Workshop (SSP))

   null (Ed.)

   Dealing with nonlinear effects of the radio-frequency (RF) chain is a key issue in the realization of very large-scale multi-antenna (MIMO) systems. Achieving the remarkable gains possible with massive MIMO requires that the signal processing algorithms systematically take into account these effects. Here, we present a computationally-efficient linear precoding method satisfying the requirements for low peak-to-average power ratio (PAPR) and low-resolution D/Aconverters (DACs). The method is based on a sparse regularization of the precoding matrix and offers advantages in terms of precoded signal PAPR as well as processing complexity. Through simulation, we find that the method substantially improves conventional linear precoders. 

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4. Hybrid Analog-Digital Precoding Design for Secrecy mmWave MISO-OFDM Systems

   https://doi.org/10.1109/TCOMM.2017.2734666  

   Ramadan, Yahia R.; Minn, Hlaing; Ibrahim, Ahmed S. (August 2017, IEEE Transactions on Communications)

   Millimeter-wave large-scale antenna systems typically apply hybrid analog-digital precoders to reduce hardware complexity and power consumption. In this paper, we design hybrid precoders for physical-layer security under two types of channel knowledge. With full channel knowledge at transmitter, we provide sufficient conditions on the minimum number of RF chains needed to realize the performance of the fully digital precoding. Then, we design the hybrid precoder to maximize the secrecy rate. By maximizing the average projection between the fully digital precoder and the hybrid precoder, we propose a low-complexity closed-form hybrid precoder. We extend the conventional projected maximum ratio transmission scheme to realize the hybrid precoder. Moreover, we propose an iterative hybrid precoder design to maximize the secrecy rate.With partial channel knowledge at transmitter, we derive a secrecy outage probability upper-bound. The secrecy throughput maximization is converted into a sequence of secrecy outage probability minimization problems. Then, the hybrid precoder is designed to minimize the secrecy outage probability by an iterative hybrid precoder design. Performance results show the proposed hybrid precoders achieve performance close to that of the fully digital precoding at low and moderate signal-to-noise ratios (SNRs), and sometimes at high SNRs depending on the system parameters. 

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5. One-Bit Sigma-Delta MIMO Precoding

   https://doi.org/10.1109/JSTSP.2019.2938687  

   Shao, Mingjie; Ma, Wing-Kin; Li, Qiang; Swindlehurst, Lee (August 2019, IEEE Journal of Selected Topics in Signal Processing)

   Coarsely quantized MIMO signalling methods have gained popularity in the recent developments of massive MIMO as they open up opportunities for massive MIMO implementation using cheap and power-efficient radio-frequency front-ends. This paper presents a new one-bit MIMO precoding approach using spatial Sigma-Delta (∑Δ) modulation. In previous one-bit MIMO precoding research, one mainly focuses on using optimization to tackle the difficult binary signal optimization problem that arise from the precoding design. Our approach attempts a different route. Assuming angular MIMO channels, we apply ∑Δ modulation—a classical concept in analog-to-digital conversion of temporal signals—in space. The resulting ∑Δ precoding approach has two main advantages: First, we no longer need to deal with binary optimization in ∑Δ precoding design. Particularly, the binary signal restriction is replaced by convex signal amplitude constraints. Second, the impact of the quantization error can be well controlled via modulator design and under appropriate operating conditions. Through symbol error probability analysis, we reveal that the very large number of antennas in massive MIMO provides favorable operating conditions for ∑Δ precoding. In addition, we develop a new ∑Δ modulation architecture that is capable of adapting the channel to achieve nearly zero quantization error for a targeted user. Furthermore, we consider multi-user ∑Δ precoding using the zero-forcing and symbol-level precoding schemes. These two ∑Δ precoding schemes perform considerably better than their direct one-bit quantized counterparts, as simulation results show. 

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