scholarly journals Beamforming Techniques for Over-the-Air Computation in MIMO IoT Networks

Sensors ◽  
2020 ◽  
Vol 20 (22) ◽  
pp. 6464
Author(s):  
Young-Seok Lee ◽  
Ki-Hun Lee ◽  
Bang Chul Jung
Keyword(s):  
Mean Squared Error ◽  
Antenna Selection ◽  
Multiple Input Multiple Output ◽  
Access Point ◽  
Transmit Beamforming ◽  
Function Computation ◽  
Input Multiple Output ◽  
Multiple Transmit ◽  
Step Algorithm ◽  
Beamforming Technique

In this paper, a novel beamforming technique is proposed as the over-the-air computation (AirComp) framework in a multiple-input multiple-output (MIMO) Internet-of-things (IoT) network consisting of multiple IoT sensors (STAs) and a single access point (AP). We assume that each IoT device has the channel state information (CSI) from itself to the AP and the AP has the global CSI of all IoT devices. We consider the mean squared error (MSE), which represents the reliability of function computation, as a performance metric. In short, each IoT device exploits maximum-ratio transmission (MRT) as a transmit beamforming technique to improve MSE performance by taking full advantage of multiple transmit antennae. Moreover, for the receive beamforming, we first consider a receive antenna selection (RAS) technique as the simplest beamforming method at the AP. Then, a semi-definite relaxation (SDR) method and a successive convex approximation (SCA) algorithm are considered and compared with each other in terms of MSE. Finally, we propose a novel two-step beamforming algorithm to further improve the MSE performance of the aforementioned techniques. We have numerically verified through computer simulations that the proposed framework has an improved MSE performance of about 6dB compared to the conventional single-input multiple-output (SIMO) AirComp, even with only two transmit antennae, and the modified MRT outperforms the other transmit beamforming techniques. Furthermore, the proposed receive beamforming technique, a two-step algorithm, shows the best performance in terms of MSE compared to prior studies.

scholarly journals Location-Aided Uplink Transmission for User-Centric Cell-Free Massive MIMO Systems: A Fairness Priority Perspective

2022 ◽  
Author(s):  
Chen Wei ◽  
Kui Xu ◽  
Zhexian Shen ◽  
Xiaochen Xia ◽  
Wei Xie ◽  
...  
Keyword(s):  
Large Scale ◽  
Mean Squared Error ◽  
Mimo Systems ◽  
Multiple Input Multiple Output ◽  
Access Point ◽  
Estimation Accuracy ◽  
Minimum Mean Squared Error ◽  
Input Multiple Output ◽  
User Centric ◽  
Assignment Scheme

Abstract In this paper, we investigate the uplink transmission for user-centric cell-free massive multiple-input multiple-output (MIMO) systems. The largest-large-scale-fading-based access point (AP) selection method is adopted to achieve a user-centric operation. Under this user-centric framework, we propose a novel inter-cluster interference-based (IC-IB) pilot assignment scheme to alleviate pilot contamination. Considering the local characteristics of channel estimates and statistics, we propose a location-aided distributed uplink combining scheme based on a novel proposed metric representing inter-user interference to balance the relationship among the spectral efficiency (SE), user equipment (UE) fairness and complexity, in which the normalized local partial minimum mean-squared error (LP-MMSE) combining is adopted for some APs, while the normalized maximum ratio (MR) combining is adopted for the remaining APs. A new closed-form SE expression using the normalized MR combining is derived and a novel metric to indicate the UE fairness is also proposed. Moreover, the max-min fairness (MMF) power control algorithm is utilized to further ensure uniformly good service to the UEs. Simulation results demonstrate that the channel estimation accuracy of our proposed IC-IB pilot assignment scheme outperforms that of the conventional pilot assignment schemes. Furthermore, although the proposed location-aided uplink combining scheme is not always the best in terms of the per-UE SE, it can provide the more fairness among UEs and can achieve a good trade-off between the average SE and computational complexity.

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 Efficient Wireless Broadcasting through Joint Network Coding and Beamforming

2012 ◽  
Vol 2012 ◽  
pp. 1-15 ◽  
Author(s):  
Monchai Lertsutthiwong ◽  
Thinh Nguyen ◽  
Bechir Hamdaoui
Keyword(s):  
Network Coding ◽  
Multiple Input Multiple Output ◽  
Base Station ◽  
Broadcast Channels ◽  
Achievable Throughput ◽  
Transmission Opportunity ◽  
Mobile Stations ◽  
Multiple Input ◽  
Input Multiple Output ◽  
Multiple Transmit

We develop a framework that exploits network coding (NC) and multiple-input/multiple-output (MIMO) techniques, jointly together, to improve throughput of downlink broadcast channels. Specifically, we consider a base station (BS) equipped with multiple transmit antennas that serves multiple mobile stations (MSs) simultaneously by generating multiple signal beams. Given the large number of MSs and the small number of transmit antennas, the BS must decide, at any transmission opportunity, which group of MSs it should transmit packets to, in order to maximize the overall throughput. We propose two algorithms for grouping MSs that take advantage of NC and the orthogonality of user channels to improve the overall throughput. Our results indicate that the proposed techniques increase the achievable throughput significantly, especially in highly lossy environments.

scholarly journals Virtual MIMO Beamforming and Device Pairing Enabled by Device-to-Device Communications for Multidevice Networks

2017 ◽  
Vol 2017 ◽  
pp. 1-10
Author(s):  
Yeonjin Jeong ◽  
Jooheum Yoon ◽  
Sang Hyun Lee ◽  
Yun Hee Kim
Keyword(s):  
Multiple Input Multiple Output ◽  
Access Point ◽  
D2d Communications ◽  
Channel State ◽  
Multiple Input ◽  
Device To Device ◽  
Input Multiple Output ◽  
Sum Rate ◽  
Device Pairing ◽  
The Internet Of Things

We consider a multidevice network with asymmetric antenna configurations which supports not only communications between an access point and devices but also device-to-device (D2D) communications for the Internet of things. For the network, we propose the transmit and receive beamforming with the channel state information (CSI) for virtual multiple-input multiple-output (MIMO) enabled by D2D receive cooperation. We analyze the sum rate achieved by a device pair in the proposed method and identify the strategies to improve the sum rate of the device pair. We next present a distributed algorithm and its equivalent algorithm for device pairing to maximize the throughput of the multidevice network. Simulation results confirm the advantages of the transmit CSI and D2D cooperation as well as the validity of the distributive algorithm.

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.

scholarly journals Joint Optimization of Precoder and Decoder in Multiuser MIMO Systems

2012 ◽  
Vol 2 (1-2) ◽  
Author(s):  
M. Raja ◽  
Ha H. Nguyen ◽  
P. Muthuchidambaranathan
Keyword(s):  
Mean Squared Error ◽  
Mimo Systems ◽  
Multiple Input Multiple Output ◽  
Joint Optimization ◽  
Phase Shift Keying ◽  
Multiuser Mimo ◽  
Multiple Input ◽  
Shift Keying ◽  
Input Multiple Output ◽  
Binary Phase Shift Keying

This paper considers the joint optimization of precoder and decoder for both uplink and downlink transmissions in multiuser multiple-input, multiple-output (MU-MIMO) systems. Focusing on the scenario when an improper constellation such as binary phase shift-keying (BPSK) or M-ary amplitude shift-keying (M-ASK) is employed, novel joint linear precoders and decoders are proposed to minimize the total mean squared error (TMSE) of the symbol estimation. The superiority of the proposed transceivers over the previously-proposed designs is thoroughly verified by simulation results.

scholarly journals Linear Precoding Designs for MIMO VLC Using Multi-Color LEDs under Multiple Lighting Constraints

Crystals ◽  
2018 ◽  
Vol 8 (11) ◽  
pp. 408 ◽  
Author(s):  
Ye Xiao ◽  
Yi-Jun Zhu ◽  
Zheng-Guo Sun
Keyword(s):  
High Speed ◽  
Mean Squared Error ◽  
Transmission Rate ◽  
Multiple Input Multiple Output ◽  
Visible Light Communication ◽  
Mimo Channel ◽  
Practical Applications ◽  
Multiple Input ◽  
Input Multiple Output ◽  
Mimo Technology

Multiple-input multiple-output (MIMO) technology as an efficient approach to improve the transmission rate in visible light communication (VLC) has been well studied in recent years. In this paper, we focus on the MIMO VLC system using multi-color LEDs in the typical indoor scenario. Besides the correlation of the MIMO channel, the multi-color crosstalk interference and quadrangle chromaticity region are also considered to increase the practicality of this system. With the constraints of power, amplitude and chromaticity, an iterative algorithm to minimize mean-squared-error (MSE) is proposed to jointly design the precoder and equalizer. Our proposed algorithm provides an effective method to get the optimal precoder by updating optimization variables iteratively. As the equalizer matrix is fixed at each iteration, the main non-convex precoding design problem is transformed into a convex optimization problem and then solved. With the utilization of multi-color LEDs, our proposed precoding method would be promising to promote the practical applications of high-speed indoor optical wireless communication. Simulation results show that our proposed method owns better performance than conventional chromaticity-fixed schemes and zero-forcing precoding designs.

scholarly journals Deep Learning Based Antenna Selection for MIMO SDR System

Sensors ◽  
2020 ◽  
Vol 20 (23) ◽  
pp. 6987
Author(s):  
Shida Zhong ◽  
Haogang Feng ◽  
Peichang Zhang ◽  
Jiajun Xu ◽  
Huancong Luo ◽  
...  
Keyword(s):  
Decision Making ◽  
Deep Learning ◽  
Software Defined Radio ◽  
Antenna Selection ◽  
Mimo System ◽  
Multiple Input Multiple Output ◽  
Base Station ◽  
Input Multiple Output ◽  
Set Up ◽  
Time Division

In this paper, we propose and implement a novel framework of deep learning based antenna selection (DLBAS)-aided multiple-input–multiple-output (MIMO) software defined radio (SDR) system. The system is constructed with the following three steps: (1) a MIMO SDR communication platform is first constructed, which is capable of achieving uplink communication from users to the base station via time division duplex (TDD); (2) we use the deep neural network (DNN) from our previous work to construct a deep learning decision server to assist the MIMO SDR platform for making intelligent decision for antenna selection, which transforms the optimization-driven decision making method into a data-driven decision making method; and (3) we set up the deep learning decision server as a multithreading server to improve the resource utilization ratio. To evaluate the performance of the DLBAS-aided MIMO SDR system, a norm-based antenna selection (NBAS) scheme is selected for comparison. The results show that the proposed DLBAS scheme performed equally to the NBAS scheme in real-time and out-performed the MIMO system without AS with up to 53% improvement on average channel capacity gain.

Sign in / Sign up

Export Citation Format

Share Document