scholarly journals An Improved Jacobi-Based Detector for Massive MIMO Systems

Information ◽  
2019 ◽  
Vol 10 (5) ◽  
pp. 165 ◽  
Author(s):  
Xiaoqing Zhao ◽  
Zhengquan Li ◽  
Song Xing ◽  
Yang Liu ◽  
Qiong Wu ◽  
...  
Keyword(s):  
Massive Mimo ◽  
Communication Systems ◽  
Mimo Systems ◽  
Minimum Mean Square Error ◽  
Multiple Input Multiple Output ◽  
Correction Method ◽  
Detection Algorithm ◽  
Detection Accuracy ◽  
Input Multiple Output ◽  
Mmse Detector

Massive multiple-input-multiple-output (MIMO) is one of the key technologies in the fifth generation (5G) cellular communication systems. For uplink massive MIMO systems, the typical linear detection such as minimum mean square error (MMSE) presents a near-optimal performance. Due to the required direct matrix inverse, however, the MMSE detection algorithm becomes computationally very expensive, especially when the number of users is large. For achieving the high detection accuracy as well as reducing the computational complexity in massive MIMO systems, we propose an improved Jacobi iterative algorithm by accelerating the convergence rate in the signal detection process.Specifically, the steepest descent (SD) method is utilized to achieve an efficient searching direction. Then, the whole-correction method is applied to update the iterative process. As the result, the fast convergence and the low computationally complexity of the proposed Jacobi-based algorithm are obtained and proved. Simulation results also demonstrate that the proposed algorithm performs better than the conventional algorithms in terms of the bit error rate (BER) and achieves a near-optimal detection accuracy as the typical MMSE detector, but utilizing a small number of iterations.

PROBLEM STATEMENT OF JOINT ANTENNA SELECTION AND PRECODING IN MASSIVE MIMO COMMUNICATION SYSTEMS

2021 ◽  
Author(s):  
В.Б. КРЕЙНДЕЛИН ◽  
М.В. ГОЛУБЕВ
Keyword(s):  
Massive Mimo ◽  
Communication Systems ◽  
Mimo Systems ◽  
Antenna Selection ◽  
Multiple Input Multiple Output ◽  
Research Areas ◽  
Multiple Input ◽  
Input Multiple Output ◽  
Legal Restrictions ◽  
Multiple Transmission

Совместный с прекодингом автовыбор антенн на приемной и передающей стороне - одно из перспективных направлений исследований для реализации технологий Multiple Transmission and Reception Points (Multi-TRP, множество точек передачи и приема) в системах со многими передающими и приемными антеннами Massive MIMO (Multiple-Input-Multiple-Output), которые активно развиваются в стандарте 5G. Проанализированы законодательные ограничения, влияющие на применимость технологий Massive MIMO, и специфика реализации разрабатываемого алгоритма в миллиметровомдиапа -зоне длин волн. Рассмотрены алгоритмы формирования матриц автовыбора антенн как на передающей, так и на приемной стороне. Сформулирована строгая математическая постановка задачи для двух критериев работы алгоритма: максимизация взаимной информации и минимизация среднеквадратичной ошибки. Joint precoding and antenna selection both on transmitter and receiver sides is one of the promising research areas for evolving toward the Multiple Transmission and Reception Points (Multi-TRP) concept in Massive MIMO systems. This technology is under active development in the coming 5G 3GPP releases. We analyze legal restrictions for the implementation of 5G Massive MIMO technologies in Russia and the specifics of the implementation of the developed algorithm in the millimeter wavelength range. Algorithms of antenna auto-selection matrices formation on both transmitting and receiving sides are considered. Two criteria are used for joint antenna selection and precoding: maximizing mutual information and minimizing mean square error.

scholarly journals An Efficient Precoding Scheme for Millimeter-Wave Massive MIMO Systems

Electronics ◽  
2019 ◽  
Vol 8 (9) ◽  
pp. 927 ◽  
Author(s):  
Alemaishat ◽  
Saraereh ◽  
Khan ◽  
Affes ◽  
Li ◽  
...  
Keyword(s):  
Computational Complexity ◽  
Millimeter Wave ◽  
Massive Mimo ◽  
Communication Systems ◽  
Mimo Systems ◽  
Multiple Input Multiple Output ◽  
Beam Control ◽  
Low Computational Complexity ◽  
Multiple Input ◽  
Input Multiple Output

Aiming at the problem of high computational complexity due to a large number of antennas deployed in mmWave massive multiple-input multiple-output (MIMO) communication systems, this paper proposes an efficient algorithm for optimizing beam control vectors with low computational complexity based on codebooks for millimeter-wave massive MIMO systems with split sub-arrays hybrid beamforming architecture. A bidirectional method is adopted on the beam control vector of each antenna sub-array both at the transmitter and receiver, which utilizes the idea of interference alignment (IA) and alternating optimization. The simulation results show that the proposed algorithm has low computational complexity, fast convergence, and improved spectral efficiency as compared with the state-of-the-art algorithms.

scholarly journals Efficient Pilot Decontamination Schemes in 5G Massive MIMO Systems

Electronics ◽  
2019 ◽  
Vol 8 (1) ◽  
pp. 55 ◽  
Author(s):  
Omar A. Saraereh ◽  
Imran Khan ◽  
Byung Moo Lee ◽  
Ashraf Tahat
Keyword(s):  
Massive Mimo ◽  
Communication Systems ◽  
Mimo Systems ◽  
Multiple Input Multiple Output ◽  
Path Loss ◽  
Achievable Rate ◽  
Pilot Contamination ◽  
User Grouping ◽  
Channel Conditions ◽  
Input Multiple Output

Massive Multiple-input Multiple-output (MIMO) is an emerging technology for the 5G wireless communication systems which has the potential to provide high spectral efficient and improved link reliability and accommodate large number of users. Aiming at the problem of pilot contamination in massive MIMO systems, this paper proposes two algorithms to mitigate it. The first algorithm is depending on the idea of Path Loss to perform User Grouping (PLUG) which divide the users into the center and edge user groups depending on different levels of pilot contamination. It assigns the same pilot sequences to the center users which slightly suffer from pilot contamination and assign orthogonal pilot sequences to the edge users which severely suffer from pilot contamination. It is assumed that the number of users at the edge of each cell is the same. Therefore, to overcome such limitations of PLUG algorithm, we propose an improved PLUG (IPLUG) algorithm which provides the decision parameters for user grouping and selects the number of central and edge users in each cell in a dynamic manner. Thus, the algorithm prevents the wrong division of users in good channel conditions being considered as an edge user which causes large pilot overhead, and also identifies the users with worst channel conditions and prevents the wrong division of such users from the center user group. The second algorithm for pilot decontamination utilizes the idea of pseudo-random codes in which orthogonal pilot are assigned to different cells. Such codes are deployed to get a transmission pilot by scrambling the user pilot in the cell. Since the pilot contamination is generated because different cells multiplex the same set of orthogonal pilots and the pseudo-random sequences have good cross-correlation characteristics, this paper uses this feature to improve the orthogonality of pilots between different cells. Simulation results show that the proposed algorithms can effectively improve channel estimation performance and achievable rate as compared with other schemes.

scholarly journals Evaluation of Multi-Beam Massive MIMO Considering MAC Layer Using IEEE802.11ac and FDD-LTE

Electronics ◽  
2019 ◽  
Vol 8 (2) ◽  
pp. 225 ◽  
Author(s):  
Fumiya Muramatsu ◽  
Kentaro Nishimori ◽  
Ryotaro Taniguchi ◽  
Takefumi Hiraguri ◽  
Tsutomu Mitsui
Keyword(s):  
Massive Mimo ◽  
Communication Systems ◽  
Mimo Systems ◽  
Adaptive Modulation ◽  
Multiple Input Multiple Output ◽  
Modulation Scheme ◽  
Medium Access ◽  
Beam Selection ◽  
Input Multiple Output ◽  
Digital Components

Massive multiple-input multiple-output (MIMO) transmission has attracted attention as a key technology for use in fifth-generation mobile communication systems. Multi-beam massive MIMO systems that apply beam selection in analog components and blind algorithms in digital components to eliminate the requirement for channel state information have been proposed as a method for reducing overhead. In this study, we developed an adaptive modulation scheme for implementing multi-beam massive MIMO and used computer simulation to compare it with digital and analog–digital hybrid beam-forming methods. The effectiveness of the proposed system was verified in a medium access control layer based on the IEEE802.11ac and frequency division duplex-LTE representative wireless communication standards.

scholarly journals On The Performance Of 1-Bit ADC In Massive MIMO Communication Systems

2020 ◽  
Author(s):  
Hung N Dang ◽  
Thuy Van Nguyen ◽  
Hieu Trung Nguyen
Keyword(s):  
Channel Coding ◽  
Massive Mimo ◽  
Communication Systems ◽  
Mimo Systems ◽  
Rational Solution ◽  
Multiple Input Multiple Output ◽  
Analog To Digital ◽  
Input Multiple Output ◽  
Negative Effect ◽  
Hardware Costs

Massive multiple-input multiple-output (MIMO) with low-resolution analog-to-digital converters is a rational solution to deal with hardware costs and accomplish optimal energy efficiency. In particular, utilizing 1-bit ADCs is one of the best choices for massive MIMO systems. This paper investigates the performance of the 1-bit ADC in the wireless coded communication systems where the robust channel coding, protograph low-density parity-check code (LDPC), is employed. The investigation reveals that the performance of the conventional 1-bit ADC with the truncation limit of 3-sigma is severely destroyed by the quantization distortion even when the number of antennas increases to 100. The optimized 1-bit ADC, though having substantial performance gain over the conventional one, is also affected by the quantization distortion at high coding rates and low MIMO configurations. Importantly, the investigation results suggest that the protograph LDPC codes should be re-designed to combat the negative effect of the quantization distortion of the 1-bit ADC.

scholarly journals Linear detectors and precoding methods for massive MIMO

2021 ◽  
Vol 42 (2) ◽  
pp. 209
Author(s):  
Jean Marcel Faria Tonin ◽  
Taufik Abrao
Keyword(s):  
Massive Mimo ◽  
Communication Systems ◽  
Mean Squared Error ◽  
Mimo Systems ◽  
Multiple Input Multiple Output ◽  
Wireless Channel ◽  
Single Input Single Output ◽  
Single Output ◽  
Minimum Mean Squared Error ◽  
Input Multiple Output

Detection in multiple-input-multiple-output (MIMO) wireless communication systems is a crucial procedure in receivers since the multiple access transmission schemes generate interference due to the simultaneous transmission along with the several antennas, unlike single-input-single-output (SISO) transmission schemes. Precoding is a technique in MIMO systems used to mitigate the effects of the channel over the received signal. Hence, it is possible to adjust continuously the transmitted information to reverse the effect of the wireless channel at the receiver side. In this work, linear sub-optimal detectors and precoders for massive MIMO (M-MIMO) systems are implemented, analyzed, and compared in terms of performance-complexity trade-off. It is also being considered numerical results in both channel scenarios: a) receiver and transmitter have perfect channel state information (CSI); b) complex channel coefficients are estimated with different levels of inaccuracy. Monte-Carlo simulations (MCS) reveal that linear zero-forcing (ZF) and minimum mean squared error (MMSE) massive MIMO detectors result in a certain robustness against multi-user interference when operating under low and medium system loading, L = K/M, thanks to the favourable propagation phenomenon arising in massive MIMO systems.

scholarly journals Low Complexity Angular-Domain Detection for the Uplink of Multi-User mmWave Massive MIMO Systems

Electronics ◽  
2020 ◽  
Vol 9 (5) ◽  
pp. 795
Author(s):  
Xiaoxuan Xia ◽  
Wence Zhang ◽  
Yinkai Fu ◽  
Xu Bao ◽  
Jing Xia
Keyword(s):  
Energy Efficiency ◽  
Computational Complexity ◽  
Massive Mimo ◽  
Communication Systems ◽  
Mimo Systems ◽  
Minimum Mean Square Error ◽  
Multiple Input Multiple Output ◽  
Digital Processing ◽  
Low Complexity ◽  
Angular Domain

To compromise between the system performance and hardware cost, millimeter wave (mmWave) massive multiple-input multiple-output (MIMO) systems have been regarded as an enabling technology for the fifth generation of mobile communication systems (5G). This paper considers a low-complexity angular-domain compressing based detection (ACD) for uplink multi-user mmWave massive MIMO systems, which involves hybrid analog and digital processing. In analog processing, we perform angular-domain compression on the received signal by exploiting the sparsity of the mmWave channel to reduce the dimension of the signal space. In digital processing, the proposed ACD scheme works well with zero forcing (ZF)/maximum ratio combining (MRC)/minimum mean square error (MMSE) detection schemes. The performance analysis of the proposed ACD scheme is provided in terms of achievable rates, energy efficiency and computational complexity. Simulations are carried out and it shows that compared with existing works, the proposed ACD scheme not only reduces the computational complexity by more than 50 % , but also improves the system’s achievable rates and energy efficiency.

scholarly journals Efficient Detectors based on Group Detection for Massive MIMO systems

2018 ◽  
Author(s):  
Thanh-Binh Nguyen ◽  
Minh-Tuan Le ◽  
Vu-Duc Ngo ◽  
Tien-Dong Nguyen ◽  
Huy-Dung Han
Keyword(s):  
Massive Mimo ◽  
Mimo Systems ◽  
Mimo System ◽  
Minimum Mean Square Error ◽  
Multiple Input Multiple Output ◽  
Bell Laboratory ◽  
Channel Matrix ◽  
Input Multiple Output ◽  
Group Detection ◽  
Ber Performance

In Multiple Input Multiple Output (MIMO) systems, the complexities of detectors depend on the size of the channel matrix. In Massive MIMO systems, detection complexity becomes remarkably higher because the dimensions of the channel matrix get much larger. In order to recover the signals in the up-link of a Massive MIMO system at reduced complexities, we first divide the system into two sub-systems. After that, we apply the Minimum Mean Square Error (MMSE) and Bell Laboratory Layer Space Time (BLAST) detectors to each subsystem, resulting in the so-called MMSE-GD and BLAST-GD detectors, respectively. To further enhance the BER performance of Massive MIMO systems under the high-load conditions, we propose two additional detectors, called MMSE-IGD and BLAST-IGD by respectively applying the conventional MMSE and BLAST on the sub-systems in an iterative manner. It is shown via computer simulation and analytical results that the proposed detectors enable the system to achieve not only higher BER performance but also low detection complexities as compared to the conventional linear detectors. Moreover, the MMSE-IGD and BLAST-IGD can significantly improve BER performance of Massive MIMO systems.

scholarly journals Low-complexity sparse-aware multiuser detection for large-scale MIMO systems

2021 ◽  
Vol 2021 (1) ◽  
Author(s):  
Rong Ran ◽  
Hayoung Oh
Keyword(s):  
Large Scale ◽  
Mimo Systems ◽  
Minimum Mean Square Error ◽  
Multiple Input Multiple Output ◽  
Low Complexity ◽  
Finite Alphabet ◽  
Multiuser Detectors ◽  
Input Multiple Output ◽  
Error Detector ◽  
Significant Performance

AbstractSparse-aware (SA) detectors have attracted a lot attention due to its significant performance and low-complexity, in particular for large-scale multiple-input multiple-output (MIMO) systems. Similar to the conventional multiuser detectors, the nonlinear or compressive sensing based SA detectors provide the better performance but are not appropriate for the overdetermined multiuser MIMO systems in sense of power and time consumption. The linear SA detector provides a more elegant tradeoff between performance and complexity compared to the nonlinear ones. However, the major limitation of the linear SA detector is that, as the zero-forcing or minimum mean square error detector, it was derived by relaxing the finite-alphabet constraints, and therefore its performance is still sub-optimal. In this paper, we propose a novel SA detector, named single-dimensional search-based SA (SDSB-SA) detector, for overdetermined uplink MIMO systems. The proposed SDSB-SA detector adheres to the finite-alphabet constraints so that it outperforms the conventional linear SA detector, in particular, in high SNR regime. Meanwhile, the proposed detector follows a single-dimensional search manner, so it has a very low computational complexity which is feasible for light-ware Internet of Thing devices for ultra-reliable low-latency communication. Numerical results show that the the proposed SDSB-SA detector provides a relatively better tradeoff between the performance and complexity compared with several existing detectors.

scholarly journals The Downlink Performance for Cell-Free Massive MIMO with Instantaneous CSI in Slowly Time-Varying Channels

Entropy ◽  
2021 ◽  
Vol 23 (11) ◽  
pp. 1552
Author(s):  
Tongzhou Han ◽  
Danfeng Zhao
Keyword(s):  
Power Control ◽  
Massive Mimo ◽  
Mimo Systems ◽  
Mimo System ◽  
Multiple Input Multiple Output ◽  
Time Varying ◽  
Input Multiple Output ◽  
Efficiency Performance ◽  
A Cell ◽  
Time Varying Channel

In centralized massive multiple-input multiple-output (MIMO) systems, the channel hardening phenomenon can occur, in which the channel behaves as almost fully deterministic as the number of antennas increases. Nevertheless, in a cell-free massive MIMO system, the channel is less deterministic. In this paper, we propose using instantaneous channel state information (CSI) instead of statistical CSI to obtain the power control coefficient in cell-free massive MIMO. Access points (APs) and user equipment (UE) have sufficient time to obtain instantaneous CSI in a slowly time-varying channel environment. We derive the achievable downlink rate under instantaneous CSI for frequency division duplex (FDD) cell-free massive MIMO systems and apply the results to the power control coefficients. For FDD systems, quantized channel coefficients are proposed to reduce feedback overhead. The simulation results show that the spectral efficiency performance when using instantaneous CSI is approximately three times higher than that achieved using statistical CSI.

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