BER performance analysis of coarsely quantized uplink massive MIMO

Azizzadeh, Azad; Mohammadkhani, Reza; Makki, Seyed Vahab Al‐Din; Björnson, Emil

doi:10.1016/j.sigpro.2019.03.005

Cited by 15 publications

(11 citation statements)

References 35 publications

(59 reference statements)

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“…In order to increase the signal detection performance, we can impose some additional constraints on x. In this paper, we will focus on QPSK signaling for the data signals whose bit error rate (BER) performance does not degrade as other higher order constellation schemes due to the adverse effect of one-bit quantization [11]. In this case, the elements of x are either 1/ √ 2 or −1/ √ 2.…”

Section: Admm-based Solutionmentioning

confidence: 99%

“…Some papers in the literature studied the effect of hardware impairments such as phase errors, low-noise amplifier non-linearities, or stochastic additive noise on massive MIMO [4][5][6][7][8]. In addition, several works considered low-cost analog-to-digital converters (ADC) with one-bit quantization [2,3,[9][10][11]. However, most of the existing works which analyze one-bit quantized massive MIMO have not considered other distortions caused by amplifiers, local oscillators, and mixers.…”

Section: Introductionmentioning

confidence: 99%

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ADMM-Based One-Bit Quantized Signal Detection for Massive MIMO Systems With Hardware Impairments

Demir

Björnson

2020

ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

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This paper considers signal detection in massive multiple-input multiple-output (MIMO) systems with general additive hardware impairments and one-bit quantization. First, we present the quantization-unaware and Bussgang decomposition-based linear receivers by generalizing them for the considered hardware impairment model. We propose an optimization problem to estimate the uplink data signals by choosing a suitable cost function that treats the unquantized received signal at the base station as the variable. We exploit the additional structure of the one-bit quantization and signal modulation by including proper constraints. To solve the non-convex quadratically-constrained quadratic programming (QCQP) problem, we propose an ADMM-based algorithm with closed-form update equations. Then, we replace the harsh projectors in the updates with their soft versions to improve the detection performance. We show that the proposed ADMM-based algorithm outperforms the state-ofthe-art linear receivers significantly in terms of bit error rate (BER) and the performance gain increases with the number of antennas and users.Index Terms-MIMO signal detection, massive MIMO, onebit quantization, ADMM, hardware impairments.

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Section: Admm-based Solutionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

ADMM-Based One-Bit Quantized Signal Detection for Massive MIMO Systems With Hardware Impairments

Demir

Björnson

2020

ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

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“…where 12) has the same form as (10). Hence, log 2 (|T N −2 |) can be further decomposed by using the similar method in (11), and it can be given by…”

Section: B Energy-efficient Hybrid Precoding Algorithm Based On Partly-connected Architecturementioning

confidence: 99%

Energy-Efficient Hybrid Precoding With Low Complexity for mmWave Massive MIMO Systems

Liu

Feng

et al. 2019

IEEE Access

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Millimeter-wave (mmWave) massive multiple-input multiple-output (MIMO) utilizes large antenna arrays and is considered a promising technology for fifth-generation (5G) and beyond wireless communication systems. However, the high-power consumption of the radio-frequency (RF) chains makes it infeasible. To solve this problem, hybrid precoding is proposed, which is a combination of analog and digital precoding. The fully connected architecture hybrid precoding still requires a large number of phase shifters (PSs). The sub-connected architecture can greatly reduce the required power consumption, and however, it cannot obtain a satisfactory achievable rate. To avoid the high energy consumption and obtain a high resolution, we propose a novel partly connected architecture in this paper. In addition, we propose an energy-efficient successive interference cancelation (SIC) hybrid precoding based on the partly connected architecture, which transforms the problem of maximizing the total achievable rate with non-convex constraints into a series of sub-rate optimization problems. Furthermore, a low-complexity energy-efficient SIC hybrid precoding based on the partly connected architecture is developed, which uses the partial singular value decomposition (SVD) to realize the sub-rate optimization and significantly reduce the complexity. Theoretical analysis demonstrates the superiority of the proposed hybrid precoding in terms of complexity. The simulation results indicate that the proposed hybrid precoding algorithms enjoy better energy efficiency and achievable rate performance than some recently proposed hybrid precoding algorithms.INDEX TERMS Millimeter wave communication, MIMO, energy efficiency, complexity theory, hybrid precoding.

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“…The disadvantage is that it cannot transmit parallel data streams to provide multiplexing gain. However, the traditional full-digital beamforming, although the best multiplexing gain can be obtained [10,11], each antenna requires a radio frequency (RF) chain, which is expensive and consumes a lot of power. Therefore, a hybrid precoding structure [12][13][14][15] that saves RF consumption and ensures good performance is extremely important.…”

mentioning

confidence: 99%

Multi-user hybrid precoding for mmWave massive MIMO systems with sub-connected structure

Wang

Zhang

et al. 2021

J Wireless Com Network

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Hybrid precoding achieves a compromise between the sum rate and hardware complexity of millimeter wave (mmWave) massive multiple-input multiple-output (MIMO) systems. However, most prior works on multi-user hybrid precoding only consider the full-connected structure. In this paper, a novel multi-user hybrid precoding algorithm is proposed for the sub-connected structure. Based on the improved successive interference cancellation (SIC), the analog precoding matrix optimization problem is decomposed into multiple analog precoding sub-matrix optimization problems. Further, a near-optimal analog precoder is designed through factorizing the precoding sub-matrix for each sub-array. Furthermore, digital precoding is designed according to the block diagonalization (BD) technology. Finally, the water-filling power allocation method is used to further improve the communication quality. The extensive simulation results demonstrate that the sum rate of the proposed algorithm is higher than the existing hybrid precoding methods with the sub-connected structure, and has higher energy efficiency compared with existing approaches. Moreover, the proposed algorithm is closer to the state-of-the-art optimization approach with the full-connected structure. In addition, the simulation results also verify the effectiveness of the proposed hybrid precoding design of the uniform planar array (UPA).

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BER performance analysis of coarsely quantized uplink massive MIMO

Cited by 15 publications

References 35 publications

ADMM-Based One-Bit Quantized Signal Detection for Massive MIMO Systems With Hardware Impairments

ADMM-Based One-Bit Quantized Signal Detection for Massive MIMO Systems With Hardware Impairments

Energy-Efficient Hybrid Precoding With Low Complexity for mmWave Massive MIMO Systems

Multi-user hybrid precoding for mmWave massive MIMO systems with sub-connected structure

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