• Title/Summary/Keyword: Massive-MIMO

Search Result 101, Processing Time 0.019 seconds

Deep Reinforcement Learning based Antenna Selection Scheme For Reducing Complexity and Feedback Overhead of Massive Antenna Systems (거대 다중 안테나 시스템의 복잡도와 피드백 오버헤드 감소를 위한 심화 강화학습 기반 안테나 선택 기법)

  • Kim, Ryun-Woo;Jeong, Moo-Woong;Ban, Tae-Won
    • Journal of the Korea Institute of Information and Communication Engineering
    • /
    • v.25 no.11
    • /
    • pp.1559-1565
    • /
    • 2021
  • In this paper, an antenna selection scheme is proposed in massive multi-user multiple input multiple output (MU-MIMO) systems. The proposed antenna selection scheme can achieve almost the same performance as a conventional scheme while significantly reducing the overhead of feedback by using deep reinforcement learning (DRL). Each user compares the channel gains of massive antennas in base station (BS) to the L-largest channel gain, converts them to one-bit binary numbers, and feed them back to BS. Thus, the feedback overhead can be significantly reduced. In the proposed scheme, DRL is adopted to prevent the performance loss that might be caused by the reduced feedback information. We carried out extensive Monte-Carlo simulations to analyze the performance of the proposed scheme and it was shown that the proposed scheme can achieve almost the same average sum-rates as a conventional scheme that is almost optimal.

Near-Optimal Low-Complexity Hybrid Precoding for THz Massive MIMO Systems

  • Yuke Sun;Aihua Zhang;Hao Yang;Di Tian;Haowen Xia
    • KSII Transactions on Internet and Information Systems (TIIS)
    • /
    • v.18 no.4
    • /
    • pp.1042-1058
    • /
    • 2024
  • Terahertz (THz) communication is becoming a key technology for future 6G wireless networks because of its ultra-wide band. However, the implementation of THz communication systems confronts formidable challenges, notably beam splitting effects and high computational complexity associated with them. Our primary objective is to design a hybrid precoder that minimizes the Euclidean distance from the fully digital precoder. The analog precoding part adopts the delay-phase alternating minimization (DP-AltMin) algorithm, which divides the analog precoder into phase shifters and time delayers. This effectively addresses the beam splitting effects within THz communication by incorporating time delays. The traditional digital precoding solution, however, needs matrix inversion in THz massive multiple-input multiple-output (MIMO) communication systems, resulting in significant computational complexity and complicating the design of the analog precoder. To address this issue, we exploit the characteristics of THz massive MIMO communication systems and construct the digital precoder as a product of scale factors and semi-unitary matrices. We utilize Schatten norm and Hölder's inequality to create semi-unitary matrices after initializing the scale factors depending on the power allocation. Finally, the analog precoder and digital precoder are alternately optimized to obtain the ultimate hybrid precoding scheme. Extensive numerical simulations have demonstrated that our proposed algorithm outperforms existing methods in mitigating the beam splitting issue, improving system performance, and exhibiting lower complexity. Furthermore, our approach exhibits a more favorable alignment with practical application requirements, underlying its practicality and efficiency.

Hybrid Transmitter Design for Massive MIMO Systems (대용량 MIMO 시스템을 위한 하이브리드 송신기 설계)

  • Seo, Bangwon
    • The Journal of the Institute of Internet, Broadcasting and Communication
    • /
    • v.22 no.3
    • /
    • pp.49-55
    • /
    • 2022
  • In the next generation mobile communication systems, hybrid massive multiple-input multiple output (MIMO) can be used to highly improve an achievable rate without increasing the number of RF chains. Recently, successive-interference-cancellation (SIC) based hybrid precoder design scheme was proposed to reduce the complexity. However, since this scheme uses simple diagonal matrix for baseband precoding, it cannot solve an interference problem between the transmitted streams. Also, there is a limitation for improving the data rate because of the use of one phase shifter for analog precoding. To solve these problems, in this paper we propose a digital precoding based on the SVD of the effective channel and an analog precoding using two phase shifters. Through simulation, we show that the proposed scheme has better achievable rate and SINR performances than the conventional one.

Low Complexity Zero-Forcing Beamforming for Distributed Massive MIMO Systems in Large Public Venues

  • Li, Haoming;Leung, Victor C.M.
    • Journal of Communications and Networks
    • /
    • v.15 no.4
    • /
    • pp.370-382
    • /
    • 2013
  • Distributed massive MIMO systems, which have high bandwidth efficiency and can accommodate a tremendous amount of traffic using algorithms such as zero-forcing beam forming (ZFBF), may be deployed in large public venues with the antennas mounted under-floor. In this case the channel gain matrix H can be modeled as a multi-banded matrix, in which off-diagonal entries decay both exponentially due to heavy human penetration loss and polynomially due to free space propagation loss. To enable practical implementation of such systems, we present a multi-banded matrix inversion algorithm that substantially reduces the complexity of ZFBF by keeping the most significant entries in H and the precoding matrix W. We introduce a parameter p to control the sparsity of H and W and thus achieve the tradeoff between the computational complexity and the system throughput. The proposed algorithm includes dense and sparse precoding versions, providing quadratic and linear complexity, respectively, relative to the number of antennas. We present analysis and numerical evaluations to show that the signal-to-interference ratio (SIR) increases linearly with p in dense precoding. In sparse precoding, we demonstrate the necessity of using directional antennas by both analysis and simulations. When the directional antenna gain increases, the resulting SIR increment in sparse precoding increases linearly with p, while the SIR of dense precoding is much less sensitive to changes in p.

Grant-Free Random Access in Multicell Massive MIMO Systems with Mixed-Type Devices: Backoff Mechanism Optimizations under Delay Constraints

  • Yingying, Fang;Qi, Zhang
    • KSII Transactions on Internet and Information Systems (TIIS)
    • /
    • v.17 no.1
    • /
    • pp.185-201
    • /
    • 2023
  • Grant-free random access (GFRA) can reduce the access delay and signaling cost, and satisfy the short transmission packet and strict delay constraints requirement in internet of things (IoT). IoT is a major trend in the future, which is characterized by the variety of applications and devices. However, most existing studies on GFRA only consider a single type of device and omit the effect of access delay. In this paper, we study GFRA in multicell massive multipleinput multiple-output (MIMO) systems where different types of devices with various configurations and requirements co-exist. By introducing the backoff mechanism, each device is randomly activated according to the backoff parameter, and active devices randomly select an orthogonal pilot sequence from a predefined pilot pool. An analytical approximation of the average spectral efficiency for each type of device is derived. Based on it, we obtain the optimal backoff parameter for each type of devices under their delay constraints. It is found that the optimal backoff parameters are closely related to the device number and delay constraint. In general, devices that have larger quantity should have more backoff time before they are allowed to access. However, as the delay constraint become stricter, the required backoff time reduces gradually, and the device with larger quantity may have less backoff time than that with smaller quantity when its delay constraint is extremely strict. When the pilot length is short, the effect of delay constraints mentioned above works more obviously.

Uplink Achievable Rate analysis of Massive MIMO Systems in Transmit-correlated Ricean Fading Environments

  • Yixin, Xu;Fulai, Liu;Zixuan, Zhang;Zhenxing, Sun
    • KSII Transactions on Internet and Information Systems (TIIS)
    • /
    • v.17 no.1
    • /
    • pp.261-279
    • /
    • 2023
  • In this article, the uplink achievable rate is investigated for massive multiple-input multiple-output (MIMO) under correlated Ricean fading channel, where each base station (BS) and user are both deployed multiple antennas. Considering the availability of prior knowledge at BS, two different channel estimation approaches are adopted with and without prior knowledge. Based on these channel estimations, a two-layer decoding scheme is adopted with maximum ratio precoding as the first layer decoder and optimal second layer precoding in the second layer. Based on two aforementioned channel estimations and two-layer decoding scheme, the exact closed form expressions for uplink achievable rates are computed with and without prior knowledge, respectively. These derived expressions enable us to analyze the impacts of line-of-sight (LoS) component, two-layer decoding, data transmit power, pilot contamination, and spatially correlated Ricean fading. Then, numerical results illustrate that the system with spatially correlated Ricean fading channel is superior in terms of uplink achievable rate. Besides, it reveals that compared with the single-layer decoding, the two-layer decoding scheme can significantly improve the uplink achievable rate performance.

DOA-based Beamforming for Multi-Cell Massive MIMO Systems

  • Hu, Anzhong
    • Journal of Communications and Networks
    • /
    • v.18 no.5
    • /
    • pp.735-743
    • /
    • 2016
  • This paper proposes a direction-of-arrival (DOA)-based beamforming approach for multi-cell massive multiple-input multiple-output systems with uniform rectangular arrays (URAs). The proposed approach utilizes the steering vectors of the URA to form a basis of the spatial space and selects the partial space for beamforming according to the DOA information. As a result, the proposed approach is of lower computational complexity than the existing methods which utilize the channel covariance matrices. Moreover, the analysis demonstrates that the proposed approach can eliminate the interference in the limit of infinite number of the URA antennas. Since the proposed approach utilizes the multipaths to enhance the signal rather than discarding them, the proposed approach is of better performance than the existing low-complexity method, which is verified by the simulation results.

Hybrid combiner design for downlink massive MIMO systems

  • Seo, Bangwon
    • ETRI Journal
    • /
    • v.42 no.3
    • /
    • pp.333-340
    • /
    • 2020
  • We consider a hybrid combiner design for downlink massive multiple-input multiple-output systems when there is residual inter-user interference and each user is equipped with a limited number of radio frequency (RF) chains (less than the number of receive antennas). We propose a hybrid combiner that minimizes the mean-squared error (MSE) between the information symbols and the ones estimated with a constant amplitude constraint on the RF combiner. In the proposed scheme, an iterative alternating optimization method is utilized. At each iteration, one of the analog RF and digital baseband combining matrices is updated to minimize the MSE by fixing the other matrix without considering the constant amplitude constraint. Then, the other matrix is updated by changing the roles of the two matrices. Each element in the RF combining matrix is obtained from the phase component of the solution matrix of the optimization problem for the RF combining matrix. Simulation results show that the proposed scheme performs better than conventional matrix-decomposition schemes.

Spectral Efficiency of Full-Duplex Wireless Backhaul with Hardware Impaired Massive MIMO for Heterogeneous Cellular Networks

  • Anokye, Prince;Lee, Kyoung-Jae
    • Journal of Advanced Information Technology and Convergence
    • /
    • v.8 no.2
    • /
    • pp.13-25
    • /
    • 2018
  • The paper analyzes the sum spectral efficiency (SE) for a heterogeneous cellular network (HetNet) which has the backhaul, provided with wireless full-duplex massive multiple-input multiple-out (MIMO) with hardware distortions. We derive approximate expressions to obtain the uplink/downlink sum SE of the backhaul. The analytic results have been shown to be exact when compared to Monte Carlo simulations. From the analysis, it is shown that the desired signal and the hardware distortion noise have the same order. The sum SE generally improves when the number of receive antennas increases but degrades when the hardware quality reduces. A sum SE performance ceiling is introduced by the hardware quality level.

Resource allocation for Millimeter Wave mMIMO-NOMA System with IRS

  • Bing Ning;Shuang Li;Xinli Wu;Wanming Hao
    • KSII Transactions on Internet and Information Systems (TIIS)
    • /
    • v.18 no.7
    • /
    • pp.2047-2066
    • /
    • 2024
  • In order to improve the coverage and achieve massive spectrum access, non-orthogonal multiple access (NOMA) technology is applied in millimeter wave massive multiple-input multiple-output (mMIMO) communication network. However, the power assumption of active sensors greatly limits its wide applications. Recently, Intelligent Reconfigurable Surface (IRS) technology has received wide attention due to its ability to reduce power consumption and achieve passive transmission. In this paper, spectral efficiency maximum problem in the millimeter wave mMIMO-NOMA system with IRS is considered. The sparse RF chain antenna structure is designed at the base station based on continuous phase modulation. Furthermore, a joint optimization problem for power allocation, power splitting, analog precoding and IRS reconfigurable matrices are constructed, which aim to achieve the maximum spectral efficiency of the system under the constraints of user's quality of service, minimum energy harvesting and total transmit power. A three-stage iterative algorithm is proposed to solve the above mentioned non-convex optimization problems. We obtain the local optimal solution by fixing some optimization parameters firstly, then introduce the relaxation variables to realize the global optimal solution. Simulation results show that the spectral efficiency of the proposed scheme is superior compared to the conventional system with phase shifter modulation. It is also demonstrated that IRS can effectively assist mmWave communication and improve the system spectral efficiency.