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 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.

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 Design and VLSI Implementation of a Reduced-Complexity Sorted QR Decomposition for High-Speed MIMO Systems

Electronics ◽  
2020 ◽  
Vol 9 (10) ◽  
pp. 1657
Author(s):  
Lu Sun ◽  
Bin Wu ◽  
Tianchun Ye
Keyword(s):  
Communication Systems ◽  
High Speed ◽  
Mimo Systems ◽  
Multiple Input Multiple Output ◽  
Cmos Technology ◽  
Qr Decomposition ◽  
Time Sharing ◽  
Hardware Complexity ◽  
Givens Rotation ◽  
Hardware Efficiency

In this article, a low-complexity and high-throughput sorted QR decomposition (SQRD) for multiple-input multiple-output (MIMO) detectors is presented. To reduce the heavy hardware overhead of SQRD, we propose an efficient SQRD algorithm based on a novel modified real-value decomposition (RVD). Compared to the latest study, the proposed SQRD algorithm can save the computational complexity by more than 44.7% with similar bit error rate (BER) performance. Furthermore, a corresponding deeply pipelined hardware architecture implemented with the coordinate rotation digital computer (CORDIC)-based Givens rotation (GR) is designed. In the design, we propose a time-sharing Givens rotation structure utilizing CORDIC modules in idle state to share the concurrent GR operations of other CORDIC modules, which can further reduce hardware complexity and improve hardware efficiency. The proposed SQRD processor is implemented in SMIC 55-nm CMOS technology, which processes 62.5 M SQRD per second at a 250-MHz operating frequency with only 176.5 kilo-gates. Compared to related studies, the proposed design has the best normalized hardware efficiency and achieves a 6-Gbps MIMO data rate which can support current high-speed wireless communication systems such as IEEE 802.11ax.

scholarly journals Partial Nulling Regularized Block Diagonalization Using Unfair Channel Selection for Post-Coding with Low-Complexity

2020 ◽  
Vol 10 (19) ◽  
pp. 6809
Author(s):  
Hyun-Sun Hwang ◽  
Jae-Hyun Ro ◽  
Young-Hwan You ◽  
Duckdong Hwang ◽  
Hyoung-Kyu Song
Keyword(s):  
Performance Enhancement ◽  
Mimo Systems ◽  
Multiple Input Multiple Output ◽  
Low Complexity ◽  
Diversity Gain ◽  
Block Diagonalization ◽  
Time Diversity ◽  
Multiple Input ◽  
Input Multiple Output ◽  
User Interference

A number of requirements for 5G mobile communication are satisfied by adopting multi-user multiple input multiple output (MU-MIMO) systems. The inter user interference (IUI) which is an inevitable problem in MU-MIMO systems becomes controllable when the precoding scheme is used. The proposed scheme, which is one of the precoding schemes, is built on regularized block diagonalization (RBD) precoding and utilizes the partial nulling concept, which is to leave part of the IUI at the same time. Diversity gain is obtained by leaving IUI, which is made by choosing the row vectors of the channel matrix that are not nullified. Since the criterion for choosing the row vectors of the channel is the power of the channel, the number of selected row vectors of the channel for each device can be unfair. The proposed scheme achieves performance enhancement by obtaining diversity gain. Therefore, the bit error rate (BER) performance is better and the computational complexity is lower than RBD when the same data rate is achieved. When the number of reduced data streams is not enough for most devices to achieve diversity gain, the proposed scheme has better performance compared to generalized block diagonalization (GBD). The low complexity at the receiver is achieved compared to GBD by using the simple way to remove IUI.

scholarly journals Controlling Initial and Final Radii to Achieve a Low-Complexity Sphere Decoding Technique in MIMO Channels

2012 ◽  
Vol 2012 ◽  
pp. 1-9 ◽  
Author(s):  
Fatemeh Eshagh Hosseini ◽  
Shahriar Shirvani Moghaddam
Keyword(s):  
Communication Systems ◽  
Multiple Input Multiple Output ◽  
Low Complexity ◽  
Sphere Decoding ◽  
Mimo Channels ◽  
Threshold Factor ◽  
Multiple Input ◽  
Input Multiple Output ◽  
The Cost ◽  
Practical Constraints

In order to apply sphere decoding algorithm in multiple-input multiple-output communication systems and to make it feasible for real-time applications, its computational complexity should be decreased. To achieve this goal, this paper provides some useful insights into the effect of initial and the final sphere radii and estimating them effortlessly. It also discusses practical ways of initiating the algorithm properly and terminating it before the normal end of the process as well as the cost of these methods. Besides, a novel algorithm is introduced which utilizes the presented techniques according to a threshold factor which is defined in terms of the number of transmit antennas and the noise variance. Simulation results show that the proposed algorithm offers a desirable performance and reasonable complexity satisfying practical constraints.

scholarly journals On the Probability of Erasure for MIMO-OFDM

2020 ◽  
Vol 2 (1) ◽  
Author(s):  
Kasturi Vasudevan ◽  
A. Phani Kumar Reddy ◽  
Gyanesh Kumar Pathak ◽  
Shivani Singh
Keyword(s):  
Fading Channels ◽  
Communication Systems ◽  
Mimo Systems ◽  
Multiple Input Multiple Output ◽  
Spatial Multiplexing ◽  
Main Requirement ◽  
Valid Signal ◽  
Input Multiple Output ◽  
Mimo Ofdm ◽  
Wireless Standards

Detecting the presence of a valid signal is an important task of a telecommunication receiver. When the receiver is unable to detect the presence of a valid signal, due to noise and fading, it is referred to as an erasure. This work deals with the probability of erasure computation for orthogonal frequency division multiplexed (OFDM) signals used by multiple input multiple output (MIMO) systems. The theoretical results are validated by computer simulations. OFDM is widely used in present day wireless communication systems due to its ability to mitigate intersymbol interference (ISI) caused by frequency selective fading channels. MIMO systems offer the advantage of spatial multiplexing, resulting in increased bit-rate, which is the main requirement of the recent wireless standards like 5G and beyond.

scholarly journals Low-Complexity Joint Weighted Neumann Series and Gauss-Seidel Soft-Output Detection  for Massive MIMO Systems

2021 ◽  
Author(s):  
Xiaoming Dai ◽  
Tiantian Yan ◽  
Yuanyuan Dong ◽  
Yuquan Luo ◽  
Hua Li
Keyword(s):  
Mean Squared Error ◽  
Mimo Systems ◽  
Multiple Input Multiple Output ◽  
Neumann Series ◽  
Low Complexity ◽  
Computation Method ◽  
Likelihood Ratios ◽  
Performance Loss ◽  
Minimum Mean Squared Error ◽  
Input Multiple Output

Abstract We introduce a joint weighted Neumann series (WNS) and Gauss-Seidel (GS) approach to implement an approximated linear minimum mean-squared error (LMMSE) detector for uplink massive multiple-input multiple-output (M-MIMO) systems. We first propose to initialize the GS iteration by a WNS method, which produces a closer-to-LMMSE initial solution than the conventional zero vector and diagonal-matrix based scheme. Then the GS algorithm is applied to implement an approximated LMMSE detection iteratively. Furthermore, based on the WNS, we devise a low-complexity approximate log-likelihood ratios (LLRs) computation method whose performance loss is negligible compared with the exact method. Numerical results illustrate that the proposed joint WNS-GS approach outperforms the conventional method and achieves near-LMMSE performance with significantly lower computational complexity.

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