Energy Efficiency of Uplink Massive MIMO Systems With Successive Interference Cancellation

Liu, Tianle; Tong, Jun; Guo, Qinghua; Xi, Jiangtao; Yu, Yanguang; Xiao, Zhitao

doi:10.1109/lcomm.2016.2634558

Cited by 19 publications

(13 citation statements)

References 12 publications

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“…We assume that the large-scale fading between a UE and the BS antennas is the same. Following [3,33] suppose the UEs are uniformly distributed in a circular cell with radius d max and minimum distance d min…”

Section: Transmission Powermentioning

confidence: 99%

“…Compared with the previous studies on MIMO detection [13][14][15][16][17][18][19][23][24][25][26][27] that focus mainly on the transmission power required, this work provides a new perspective for study the detectors in realistic scenarios under the EE criterion. Our work also differs from the previous studies on EE [3,5,12,33] where the capacity, i.e., the upper bound of the achievable rate under Gaussian signaling, is considered, as the actual power consumption for practical modulation, signal processing schemes and reliability requirement is evaluated in our studies.…”

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confidence: 99%

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On the Energy Efficiency of Massive MIMO Systems With Low-Resolution ADCs and Lattice Reduction Aided Detectors

et al. 2020

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As an effective technology for boosting the performance of wireless communications, massive multiple-input multiple-output (MIMO) systems based on symmetric antenna arrays have been extensively studied. Using low-resolution analog-to-digital converters (ADCs) at the receiver can greatly reduce hardware costs and circuit complexity to further improve the energy efficiency (EE) of the system. There are significant research on the design of MIMO detectors but there is limited study on their performance in terms of EE. This paper studies the effect of signal detection on the EE in practical systems, and proposes to apply several signal detectors based on lattice reduction successive interference cancellation (LR-SIC) to massive MIMO systems with low-precision ADCs. We report results on their achievable EE in fading environments with typical modeling of the path loss and detailed analysis of the power consumption of the transceiver circuits. It is shown that the EE-optimal solution depends highly on the application scenarios, e.g., the number of antennas employed, the cell size, and the signal processing efficiency. Consequently, the signal detector must be properly selected according to the application scenario to maximize the system EE. In addition, medium-resolution ADCs should be selected to balance their own power consumption and the associated nonlinear distortion to maximize the EE of system. Symmetry 2020, 12, 406 2 of 20 Significant work has been done on the symbol detection in massive MIMO systems with low-precision ADCs. A class of techniques recover the transmitted symbols directly from the nonlinear model. In [13], iterative decision feedback receiver is studied for quantized MIMO systems. In [14], message passing dequantization (MPDQ) is applied to achieve multiuser detection for systems employing single-bit quantization. In [15], generalized approximate message passing is employed for massive MIMO with low-resolution ADCs. On the other hand, the tremendous detection algorithms designed for MIMO systems with ideal ADCs [16][17][18][19][20][21][22] can also be directly applied to quantized systems by using a linearized additive quantization noise model (AQNM). This will result in certain loss in the effective signal-to-noise ratio (SNR) but may offer solutions with moderate complexity, which are feasible for practical applications. Among the candidate techniques, the MMSE detector represents a linear option while lattice reduction-aided successive interference cancellation (LR-SIC) [23][24][25][26][27][28] provides nonlinear solutions with good tradeoff between performance and complexity for channels with large coherence blocks. The use of low-complexity, energy-efficient ADCs is also foreseen to be appealing in case of energy-constrained receive sides, such as cluster heads in massive MIMO-based wireless sensor networks (WSNs), as studied in [29][30][31][32].In general, more advanced detectors lead to improved bit error rate (BER) performance for MIMO systems (with either ideal or low-resolution ADCs) bu...

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Section: Transmission Powermentioning

confidence: 99%

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confidence: 99%

On the Energy Efficiency of Massive MIMO Systems With Low-Resolution ADCs and Lattice Reduction Aided Detectors

et al. 2020

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“…As future extensions, we intend to consider other approaches such as massive MIMO [29]. For instance, it has been shown in [32] that the energy efficiency of a massive MIMO system depends strongly on the number of antennas at the BSs and on the receiver architecture. The receiver architecture is important since, compared to linear receivers, successive interference cancellation receivers have higher signal processing complexity due to ordering and filter computation.…”

Section: Final Commentsmentioning

confidence: 99%

Energy Efficiency of Multiple Antenna Cellular Networks Considering a Realistic Power Consumption Model

Krauss

Brante

Rayel

et al. 2019

IEEE Trans. on Green Commun. Netw.

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We analyze the area energy efficiency (AEE) of a cellular network employing spatial multiplexing (SM), maximal ratio transmission (MRT) and transmit antenna selection (TAS) schemes. Moreover, we consider a realistic power consumption model for small base stations (BSs), which includes the power consumed by the backhaul as well as different interference attenuation levels. Our goal is to maximize the AEE by deploying the optimal number of BSs given some requirements, such as demanded network capacity, amount of interference and employed MIMO scheme. Results show that TAS performs better in terms of AEE when the interference is not fully canceled and for no interference cancellation when the demand for system capacity is lower, while SM becomes more energy efficient when the demanded capacity is higher. Additionally, when the capacity demand and the area to be covered are fixed, we show that although achieving the highest AEE, TAS also demands more small BSs than SM. The system performance in terms of AEE is shown to be strongly dependent on the amount of interference, which in turn depends on the employed interference-mitigation scheme and on the power consumption model.

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“…Low complexity linear detectors, such as zeroforcing (ZF) [4][5][6][7] or minimum mean square error (MMSE), can provide near-optimal bit error rate (BER) performance when they are used in massive MIMO systems [1]. In [8], the authors proved that if the system uses the Bell Laboratory Space Time (BLAST) detector, it will obtain a huge energy e ciency compared to that of the classical MMSE.…”

Section: Introductionmentioning

confidence: 99%

“…us, they are not suitable detectors for signal recovery in high-load scenarios. In spite of the fact that it can provide high BER performance, the BLAST detector in [8] is also not applicable to massive MIMO systems with hundreds of antennas due to its high complexity.…”

Section: Introductionmentioning

confidence: 99%

Signal Detection Based on Parallel Group Detection Algorithm for High-Load Massive MIMO Systems

Nguyen

Le²,

Ngo

2019

Wireless Communications and Mobile Computing

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In this paper, a parallel group detection (PGD) algorithm is proposed in order to address the degradation in the bit error rate (BER) performance of linear detectors when they are used in high-load massive MIMO systems. e algorithm is constructed by converting the equivalent extended massive MIMO system into two subsystems, which can be simultaneously detected by the classical detection procedures. en, using the PGD and the classical ZF as well as the QR-decomposition-(QRD-) based detectors, we proposed two new detectors, called ZF-based PGD (ZF-PGD) and QRD-based PGD (QRD-PGD). e PGD is further combined with the sorted longest basis (SLB) algorithm to make the signal recovery more accurate, thereby resulting in two new detectors, namely, the ZF-PGD-SLB and the QRD-PGD-SLB. Various complexity evaluations and simulations prove that the proposed detectors can signi cantly improve the BER performance compared to their classical linear and QRD counterparts with the practical complexity levels. Hence, our proposed detectors can be used as e cient means of estimating the transmitted signals in high-load massive MIMO systems.

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Energy Efficiency of Uplink Massive MIMO Systems With Successive Interference Cancellation

Cited by 19 publications

References 12 publications

On the Energy Efficiency of Massive MIMO Systems With Low-Resolution ADCs and Lattice Reduction Aided Detectors

On the Energy Efficiency of Massive MIMO Systems With Low-Resolution ADCs and Lattice Reduction Aided Detectors

Energy Efficiency of Multiple Antenna Cellular Networks Considering a Realistic Power Consumption Model

Signal Detection Based on Parallel Group Detection Algorithm for High-Load Massive MIMO Systems

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