scholarly journals A statistical block fading channel model for multiuser massive MIMO system

2016 ◽  
Author(s):  
Suresh Dahiya
Keyword(s):  
Fading Channel ◽  
Massive Mimo ◽  
Channel Model ◽  
Mimo System ◽  
Block Fading Channel

Performance Evaluation of Precoding Schemes for Multi User Massive MIMO System Over Nakagami-m Fading Channel

2021 ◽  
Author(s):  
Sultan.F Feisso Meko ◽  
Muluneh Mekonnen Tulu ◽  
Terefe Bahiru Bashu
Keyword(s):  
Performance Evaluation ◽  
Wireless Communication ◽  
Antenna Arrays ◽  
Interference Cancellation ◽  
Fading Channel ◽  
Massive Mimo ◽  
Mimo System ◽  
Base Station ◽  
Communication Link ◽  
User Interference

Abstract Nowadays, wireless communication system plays great roles in our dailyactivities and different improvements are requiring because the number of users increase from time to time. At the same time, users need high throughput and link reliability. The forthcoming generation of wireless communication will have to deal with some core requirements for serving large number of users simultaneously, upholdinghigh throughput for each user, assuring less energy consumption, etc. Inter-user interference has a major impact when a wireless communication link has a large number of users. To maintain a particular desired quality of service, sophisticated transmission mechanisms such as interference cancellation need be implemented. As a result, MU-massive MIMO with extremely huge antenna arrays is recommended. The term ”MU-massive MIMO” refers to a system with hundreds or thousands of antennas servicing tens of thousands of customers.Inter-user interference was greatly decreased once the channel vectors were closely orthogonal. As a result, high data rates can be supplied to multiple users at the same time. In this work, researcher investigated performance evaluation of a MU-massive MIMO utilizing different precoding schemes (like, MMSE, ZF, MRT) over nakagami-m fading channel with CSI at base station and users’ terminal. In addition, the researcher analyzed the outcome of pilot reuse factors and shaping (m) parameter.

scholarly journals Turbo Codes Performance Optimization over Block Fading Channels

2017 ◽  
Vol 2 (3) ◽  
pp. 228
Author(s):  
Fulvio Babich ◽  
Guido Montorsi ◽  
Francesca Vatta
Keyword(s):  
Fading Channels ◽  
Mobile Communications ◽  
Turbo Codes ◽  
Performance Optimization ◽  
Fading Channel ◽  
Communication Systems ◽  
Channel Model ◽  
Turbo Code ◽  
Convolutional Codes ◽  
Block Fading Channel

In this paper, the best achievable performance of a turbo coded system on a block fading channel is obtained, assuming binary antipodal modulation. A rate 1/3 turbo code is considered, obtained by concatenating, through a random interleaver, an 8-states rate 1/2 and a rate 1 convolutional codes (CC). The block fading channel model is motivated by the fact that in many wireless systems the coherence time of the channel is much longer than one symbol interval, resulting in adjacent symbols being affected by the same fading value. The fading blocks will experience independent fades, assuming a sufficient separation in time, in frequency, or both in time and in frequency. This channel model is suitable for analyzing, forinstance, wireless communication systems employing techniques such as slow frequency-hopping, as is done in the Global System for Mobile communications (GSM).In such systems, coded information is transmitted over a small number of fading channels in order to achieve diversity. The best coded information allocations over a certain number of fading channels are evaluated, using the Eades-McKay algorithm to generate distinct permutations of a multiset. Bounds on the achievable performance due to coding are derived using information-theoretic techniques. In particular, in the paper an analytical method is proposed, based on the sphere-packing bounding technique, to assess the achievable performance. Moreover, simulation results are obtained and compared with the theoretical ones.

scholarly journals Performance Analysis of Dual-Polarized Massive MIMO System with Human-Care IoT Devices for Cellular Networks

2018 ◽  
Vol 2018 ◽  
pp. 1-8 ◽  
Author(s):  
Jun-Ki Hong
Keyword(s):  
Performance Analysis ◽  
Cellular Networks ◽  
Massive Mimo ◽  
Channel Model ◽  
Mimo System ◽  
Multiple Input Multiple Output ◽  
Input Multiple Output ◽  
Dual Polarized ◽  
Human Care ◽  
Iot Devices

The performance analysis of the dual-polarized massive multiple-input multiple-output (MIMO) system with Internet of things (IoT) devices is studied when outdoor human-care IoT devices are connected to a cellular network via a dual-polarized massive MIMO system. The research background of the performance analysis of dual-polarized massive MIMO system with IoT devices is that recently the data usage of outdoor human-care IoT devices has increased. Therefore, the outdoor human-care IoT devices are necessary to connect with 5G cellular networks which can expect 1000 times higher performance compared with 4G cellular networks. Moreover, in order to guarantee the safety of the patient for emergency cases, a human-care Iot device must be connected to cellular networks which offer more stable communication for outdoors compared to short-range communication technologies such as Wi-Fi, Zigbee, and Bluetooth. To analyze the performance of the dual-polarized massive MIMO system for human-care IoT devices, a dual-polarized MIMO spatial channel model (SCM) is proposed which considers depolarization effect between the dual-polarized transmit-antennas and the receive-antennas. The simulation results show that the performance of the dual-polarized massive MIMO system is improved about 16% to 92% for 20 to 150 IoT devices compared to conventional single-polarized massive MIMO system for identical size of the transmit array.

scholarly journals Channel Rectification and Signal Estimation Based on EIV Model in Massive MIMO System

2017 ◽  
Vol 2017 ◽  
pp. 1-7
Author(s):  
Liang Zhong ◽  
Li Huang ◽  
Zhengmin Kong
Keyword(s):  
Channel Estimation ◽  
Massive Mimo ◽  
Channel Model ◽  
Least Squares Method ◽  
Mimo System ◽  
Estimation Error ◽  
Estimation Algorithm ◽  
Channel Estimation Error ◽  
Signal Estimation ◽  
Pilot Contamination

The performance of Massive MIMO is severely limited by channel estimation error, which is caused by pilot contamination and channel aging. In this paper, we propose an estimation algorithm based on the weighted total least-squares method with errors-in-variables (EIV) model to alleviate the influence of pilot contamination and channel aging. Then, a channel rectification method has been investigated to diminish the inaccuracy of channel estimation. Comparing with the traditional methods, it not only helps to make the signal estimation more accurate, but also provides opportunities to correct the channel model with estimation error and update the aged channel statement information. Simulations are provided to verify the efficacy of this method.

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