scholarly journals Application of Reinforcement Learning and Deep Learning in Multiple-Input and Multiple-Output (MIMO) Systems

Sensors ◽  
2021 ◽  
Vol 22 (1) ◽  
pp. 309
Author(s):  
Muddasar Naeem ◽  
Giuseppe De Pietro ◽  
Antonio Coronato
Keyword(s):  
Wireless Communication ◽  
Communication Systems ◽  
Mimo Systems ◽  
Data Rate ◽  
System Throughput ◽  
Multiple Antenna ◽  
Mimo Communication ◽  
High Data ◽  
Recent Success ◽  
Multiple Input

The current wireless communication infrastructure has to face exponential development in mobile traffic size, which demands high data rate, reliability, and low latency. MIMO systems and their variants (i.e., Multi-User MIMO and Massive MIMO) are the most promising 5G wireless communication systems technology due to their high system throughput and data rate. However, the most significant challenges in MIMO communication are substantial problems in exploiting the multiple-antenna and computational complexity. The recent success of RL and DL introduces novel and powerful tools that mitigate issues in MIMO communication systems. This article focuses on RL and DL techniques for MIMO systems by presenting a comprehensive review on the integration between the two areas. We first briefly provide the necessary background to RL, DL, and MIMO. Second, potential RL and DL applications for different MIMO issues, such as detection, classification, and compression; channel estimation; positioning, sensing, and localization; CSI acquisition and feedback, security, and robustness; mmWave communication and resource allocation, are presented.

scholarly journals Capacity Optimization of MIMO Systems Involving Conformal Antenna Arrays using a Search Group Algorithm

2020 ◽  
Vol 5 (4) ◽  
pp. 209-214
Author(s):  
Abdelmadjid RECIOUI
Keyword(s):  
Wireless Communication ◽  
Antenna Arrays ◽  
Communication Systems ◽  
Mimo Systems ◽  
Mimo System ◽  
Wireless Communication Systems ◽  
Capacity Optimization ◽  
Mimo Communication ◽  
Conformal Antenna

MIMO systems constitute a backbone of the fourth and fifth generations of wireless communication systems. The purpose of this paper is to introduce the involvement of conformal antenna arrays into MIMO systems. The Search Group Algorithm (SGA) is then used to further enhance the capacity of MIMO system employing conformal antenna arrays at both ends (Transmitter; Tx and Receiver; Rx). The results reveal that compared to the linear and 2D cases, conformal antenna arrays promise higher capacity values which motivates their employment in future MIMO communication systems.

scholarly journals Doppler Effect in 2 × 2 to 4 × 4 Mimo Systems of Wireless Communication with Orthogonal Pilot Channel Estimation

2020 ◽  
Vol 223 (4) ◽  
pp. 5-20
Author(s):  
Vadim Romanuke
Keyword(s):  
Wireless Communication ◽  
Channel Estimation ◽  
Doppler Shift ◽  
Doppler Effect ◽  
Communication Systems ◽  
Mimo Systems ◽  
Data Rate ◽  
Pilot Signal ◽  
Express Train ◽  
The Doppler Effect

Abstract The Doppler effect in 2×2, 3×3, 4×4 MIMO wireless communication systems with channel estimation is studied. The orthogonal pilot signal approach is used for the channel estimation, where the Hadamard sequences are used for piloting, along with the eight alternative orthogonal sets similar to the Walsh set. MIMO transmissions are simulated for 10 cases of the frame length and pilot symbols per frame by no Doppler shift to 1100 Hz Doppler shift with a step of 100 Hz. Based on the simulation, it is ascertained that MIMO transmissions of shorter frames are less sensitive to the Doppler effect. Despite increasing the number of antennas does not mitigate the Doppler effect, and the bit-error rate performance of 4×4 MIMO systems worsens faster than that of 2×2 MIMO systems, it is better to use the maximum number of antennas. The Doppler effect does badly worsen the performance at highway and express train speeds (100 km/hr, and faster), leaving only possibility to further shorten transmissions. This, however, decreases the data rate, but the respective accuracy-versus-data-rate tradeoff must be acceptable.

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.

Sign in / Sign up

Export Citation Format

Share Document