scholarly journals Self-Interference Channel Training for Full-Duplex Massive MIMO Systems

Sensors ◽  
2021 ◽  
Vol 21 (9) ◽  
pp. 3250
Author(s):  
Taehyoung Kim ◽  
Kyungsik Min ◽  
Sangjoon Park
Keyword(s):  
Massive Mimo ◽  
Communication Systems ◽  
Channel Model ◽  
Mimo Systems ◽  
Multiple Input Multiple Output ◽  
Full Duplex ◽  
Estimation Accuracy ◽  
Rician Fading ◽  
Channel Training ◽  
Training Schemes

Full-duplex (FD) is a promising technology for increasing the spectral efficiency of next-generation wireless communication systems. A major technical challenge in enabling FD in a real network is to remove the self-interference (SI) caused by simultaneous transmission and reception at the transceiver, and the SI cancellation performance depends significantly on the estimation accuracy of the SI channel. In this study, we proposed a novel partial SI channel training method for minimizing the residual SI power for FD massive multiple-input multiple-output (MIMO) systems. Based on an SI channel training framework under a limited training overhead, using the proposed scheme, the BS estimates only a part of the SI channel vectors, while skipping the channel training for the other remaining SI channel vectors by using their last estimates. With this partial training framework, the proposed scheme finds the optimal partial SI channel training strategy for pilot allocation to minimize the expected residual SI power, considering the time-varying Rician fading channel model for the SI channel. Therefore, the proposed scheme can improve the sum-rate performance compared with other simple partial training schemes for FD massive MIMO systems under a limited training overhead. Numerical results confirm the effectiveness of the proposed scheme for FD massive MIMO systems compared with the full training scheme, as well as other partial training schemes.

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 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.

scholarly journals Low complexity full duplex MIMO systems: Analog canceler architectures, beamforming design, and future directions

2021 ◽  
Vol 2 (2) ◽  
pp. 109-127
Author(s):  
George C. Alexandropoulos
Keyword(s):  
Communication Systems ◽  
Mimo Systems ◽  
Multiple Input Multiple Output ◽  
Low Complexity ◽  
Full Duplex ◽  
Hardware Complexity ◽  
Algorithmic Solution ◽  
Input Multiple Output ◽  
The One ◽  
Rate Optimization

The hardware complexity of the analog Self-Interference (SI) canceler in conventional full duplex Multiple Input Multiple Output (MIMO) designs mostly scales with the number of transmit and receive antennas, thus exploiting the benefits of analog cancellation becomes impractical for full duplex MIMO transceivers, even for a moderate number of antennas. In this paper, we provide an overview of two recent hardware architectures for the analog canceler comprising of reduced number of cancellation elements, compared to the state of the art, and simple multiplexers for efficient signal routing among the transceiver radio-frequency chains. The one architecture is based on analog taps and the other on AUXiliary (AUX) Transmitters (TXs). In contrast to the available analog cancellation architectures, the values for each tap or each AUX TX and the configuration of the multiplexers are jointly designed with the digital transceiver beamforming filters according to desired performance objectives. We present a general optimization framework for the joint design of analog SI cancellation and digital beamforming, and detail an example algorithmic solution for the sum-rate optimization objective. Our representative computer simulation results demonstrate the superiority, both in terms of hardware complexity and achievable performance, of the presented low complexity full duplex MIMO schemes over the relative available ones in the literature. We conclude the paper with a discussion on recent simultaneous transmit and receive operations capitalizing on the presented architectures, and provide a list of open challenges and research directions for future FD MIMO communication systems, as well as their promising applications.

scholarly journals Compressive Sensing Based Channel Estimation for Massive MIMO Communication Systems

2019 ◽  
Vol 2019 ◽  
pp. 1-15 ◽  
Author(s):  
Athar Waseem ◽  
Aqdas Naveed ◽  
Sardar Ali ◽  
Muhammad Arshad ◽  
Haris Anis ◽  
...  
Keyword(s):  
Channel Estimation ◽  
Compressive Sensing ◽  
Massive Mimo ◽  
Communication Systems ◽  
Mimo Systems ◽  
Multiple Input Multiple Output ◽  
Sampling Theorem ◽  
Base Station ◽  
Mimo Channels ◽  
Pilot Design

Massive multiple-input multiple-output (MIMO) is believed to be a key technology to get 1000x data rates in wireless communication systems. Massive MIMO occupies a large number of antennas at the base station (BS) to serve multiple users at the same time. It has appeared as a promising technique to realize high-throughput green wireless communications. Massive MIMO exploits the higher degree of spatial freedom, to extensively improve the capacity and energy efficiency of the system. Thus, massive MIMO systems have been broadly accepted as an important enabling technology for 5th Generation (5G) systems. In massive MIMO systems, a precise acquisition of the channel state information (CSI) is needed for beamforming, signal detection, resource allocation, etc. Yet, having large antennas at the BS, users have to estimate channels linked with hundreds of transmit antennas. Consequently, pilot overhead gets prohibitively high. Hence, realizing the correct channel estimation with the reasonable pilot overhead has become a challenging issue, particularly for frequency division duplex (FDD) in massive MIMO systems. In this paper, by taking advantage of spatial and temporal common sparsity of massive MIMO channels in delay domain, nonorthogonal pilot design and channel estimation schemes are proposed under the frame work of structured compressive sensing (SCS) theory that considerably reduces the pilot overheads for massive MIMO FDD systems. The proposed pilot design is fundamentally different from conventional orthogonal pilot designs based on Nyquist sampling theorem. Finally, simulations have been performed to verify the performance of the proposed schemes. Compared to its conventional counterparts with fewer pilots overhead, the proposed schemes improve the performance of the system.

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 Achievable Rates for Full-Duplex Massive MIMO Systems Over Rician Fading Channels

IEEE Access ◽  
2018 ◽  
Vol 6 ◽  
pp. 30208-30216 ◽  
Author(s):  
Juan Liu ◽  
Jianxin Dai ◽  
Jin-Yuan Wang ◽  
Junxi Zhao ◽  
Chonghu Cheng
Keyword(s):  
Fading Channels ◽  
Massive Mimo ◽  
Mimo Systems ◽  
Full Duplex ◽  
Rician Fading ◽  
Rician Fading Channels

scholarly journals Low-Complexity Joint Channel Estimation for Multi-User mmWave Massive MIMO Systems

Electronics ◽  
2020 ◽  
Vol 9 (2) ◽  
pp. 301
Author(s):  
Jianhe Du ◽  
Jiaqi Li ◽  
Jing He ◽  
Yalin Guan ◽  
Heyun Lin
Keyword(s):  
Channel Estimation ◽  
Massive Mimo ◽  
Mimo Systems ◽  
Multiple Input Multiple Output ◽  
Estimation Algorithm ◽  
Step Length ◽  
Low Complexity ◽  
Base Station ◽  
Estimation Accuracy ◽  
Input Multiple Output

For multi-user millimeter wave (mmWave) massive multiple-input multiple-output (MIMO) systems, the precise acquisition of channel state information (CSI) is a huge challenge. With the increase of the number of antennas at the base station (BS), the traditional channel estimation techniques encounter the problems of pilot training overhead and computational complexity increasing dramatically. In this paper, we develop a step-length optimization-based joint iterative scheme for multi-user mmWave massive MIMO systems to improve channel estimation performance. The proposed estimation algorithm provides the BS with full knowledge of all channel parameters involved in up- and down-links. Compared with existing algorithms, the proposed algorithm has higher channel estimation accuracy with low complexity. Moreover, the proposed scheme performs well even with a small number of training sequences and a large number of users. Simulation results are shown to demonstrate the performance of the proposed channel estimation algorithm.

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.

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