scholarly journals NOMA and OMA-Based Massive MIMO and Clustering Algorithms for Beyond 5G IoT Networks

2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Taj Rahman ◽  
Feroz Khan ◽  
Inayat Khan ◽  
Niamat Ullah ◽  
Maha M. Althobaiti ◽  
...  
Keyword(s):  
Computational Complexity ◽  
Interference Cancellation ◽  
Massive Mimo ◽  
Multiple Access ◽  
Clustering Algorithms ◽  
Mobile Network ◽  
Base Station ◽  
Signal Interference ◽  
Global Changes ◽  
Power Requirement

The Internet of Things (IoT) has brought about various global changes, as all devices will be connected. This article examines the latest 5G solutions for enabling a massive cellular network. It further explored the gaps in previously published articles, demonstrating that to deal with the new challenges. The mobile network must use massive multiple input and output (MIMO), nonorthogonal multiple access (NOMA), orthogonal multiple access (OMA), signal interference cancellation (SIC), channel state information (CSI), and clustering. Furthermore, this article has two objectives such as (1) to introduce the cluster base NOMA to reduce the computational complexity by applying SIC on a cluster, which ultimately results in faster communication and (2) to achieve massive connectivity by proposing massive MIMO with NOMA and OMA. The proposed NOMA clustering technique working principle pairs the close user with the far user; thus, it will reduce computational complexity, which was one such big dilemma in the existing articles. This will specifically help those users that are far away from the base station by maintaining the connectivity. Despite NOMA’s extraordinary benefits, one cannot deny the significance of the OMA; hence, the other objective of the proposed work is to introduce OMA with MIMO in small areas where the user is low in number, it is already in use, and quite cheap. The next important aspect of the proposed work is SIC, which helps remove interference and leads to enhancement in network performance. The simulation result has clearly stated that NOMA has gained a higher rate than OMA: current NOMA users’ power requirement (weak signal user 0.06, strong signal user 0.07), spectral efficiency ratio for P-NOMA and C-NOMA (21%, 5%), signal-to-noise ratio OMA, P-NOMA, C-NOMA (28, 40, 55%), and user rate pairs NOMA, OMA (7, 3), C-NOMA, and massive MIMO NOMA SINR (4.0, 2.5).

scholarly journals On the performance of non-orthogonal multiple access (NOMA) using FPGA

2020 ◽  
Vol 10 (2) ◽  
pp. 2151
Author(s):  
Mohamad Abdulrahman Ahmed ◽  
Khalid F. Mahmmod ◽  
Mohammed M. Azeez
Keyword(s):  
Gaussian Noise ◽  
Interference Cancellation ◽  
Multiple Access ◽  
Additive White Gaussian Noise ◽  
Base Station ◽  
Rate Performance ◽  
Allocation Mechanism ◽  
Close Match ◽  
Fifth Generation ◽  
Field Programmable

In this paper,  non-orthogonal multiple access (NOMA) is designed and implemented for the fifth generation (5G) of multi-user wireless communication.  Field-programmable gate array (FPGA) is considered for the implementation of this technique for two users. NOMA is applied in downlink phase of the base-station (BS) by applying power allocation mechanism for far and near users, in which one signal contains the superposition of two scaled signals depending on the distance of each user from the BS.  We assume an additive white Gaussian noise (AWGN) channel for each user in the presence of the interference due to the non-orthogonality between the two users’ signals. Therefore, successive-interference cancellation (SIC) is exploited to remove the undesired signal of the other user. The outage probability and the bit-error rate performance are presented over different signal-to-interference-plus-noise ratio (SINR). Furthermore, Monte-Carlo simulations via Matlab are utilized to verify the results obtained by FPGA, which show exact-close match.

scholarly journals A Novel Iterative Discrete Estimation Algorithm for Low-Complexity Signal Detection in Uplink Massive MIMO Systems

Electronics ◽  
2019 ◽  
Vol 8 (9) ◽  
pp. 980 ◽  
Author(s):  
Hui Feng ◽  
Xiaoqing Zhao ◽  
Zhengquan Li ◽  
Song Xing
Keyword(s):  
Computational Complexity ◽  
Massive Mimo ◽  
Mimo Systems ◽  
Estimation Algorithm ◽  
Low Complexity ◽  
Detection Algorithm ◽  
Base Station ◽  
Damping Factor ◽  
Mimo Detection ◽  
Discrete Estimation

In this paper, a novel iterative discrete estimation (IDE) algorithm, which is called the modified IDE (MIDE), is proposed to reduce the computational complexity in MIMO detection in uplink massive MIMO systems. MIDE is a revision of the alternating direction method of multipliers (ADMM)-based algorithm, in which a self-updating method is designed with the damping factor estimated and updated at each iteration based on the Euclidean distance between the iterative solutions of the IDE-based algorithm in order to accelerate the algorithm’s convergence. Compared to the existing ADMM-based detection algorithm, the overall computational complexity of the proposed MIDE algorithm is reduced from O N t 3 + O N r N t 2 to O N t 2 + O N r N t in terms of the number of complex-valued multiplications, where Ntand Nr are the number of users and the number of receiving antennas at the base station (BS), respectively. Simulation results show that the proposed MIDE algorithm performs better in terms of the bit error rate (BER) than some recently-proposed approximation algorithms in MIMO detection of uplink massive MIMO systems.

scholarly journals Optimal Low-Power Design of a Multicell Multiuser Massive MIMO System at 3.7 GHz for 5G Wireless Networks

2018 ◽  
Vol 2018 ◽  
pp. 1-17 ◽  
Author(s):  
Michel Matalatala ◽  
Margot Deruyck ◽  
Emmeric Tanghe ◽  
Luc Martens ◽  
Wout Joseph
Keyword(s):  
Low Power ◽  
Communication Networks ◽  
Massive Mimo ◽  
Mimo System ◽  
Low Power Design ◽  
Base Station ◽  
Base Stations ◽  
Reference Network ◽  
Power Requirement ◽  
Time Frequency

Massive MIMO techniques are expected to deliver significant performance gains for the future wireless communication networks by improving the spectral and the energy efficiencies. In this paper, we propose a method to optimize the positions, the coverage, and the energy consumption of the massive MIMO base stations within a suburban area in Ghent, Belgium, while meeting the low power requirements. The results reveal that massive MIMO provides better performances for the crowded scenario where users’ mobility is limited. With 256 antennas, a massive MIMO base station can simultaneously multiplex 18 users at the same time-frequency resource while consuming 8 times less power and providing 200 times more capacity than a 4G reference network for the same coverage. Moreover, a pilot reuse pattern of 3 is recommended in a multiuser multicell environment to obtain a good tradeoff between the high spectral efficiency and the low power requirement.

scholarly journals Enhanced Transmit-Antenna Selection Schemes for Multiuser Massive MIMO Systems

2017 ◽  
Vol 2017 ◽  
pp. 1-6 ◽  
Author(s):  
Byung-Jin Lee ◽  
Sang-Lim Ju ◽  
Nam-il Kim ◽  
Kyung-Seok Kim
Keyword(s):  
Computational Complexity ◽  
Radio Frequency ◽  
Spectral Efficiency ◽  
Massive Mimo ◽  
Mimo Systems ◽  
Antenna Selection ◽  
Base Station ◽  
Base Stations ◽  
Transmit Antenna Selection ◽  
Selection Scheme

Massive multiple-input multiple-output (MIMO) systems are a core technology designed to achieve the performance objectives defined for 5G wireless communications. They achieve high spectral efficiency, reliability, and diversity gain. However, the many radio frequency chains required in base stations equipped with a high number of transmit antennas imply high hardware costs and computational complexity. Therefore, in this paper, we investigate the use of a transmit-antenna selection scheme, with which the number of required radio frequency chains in the base station can be reduced. This paper proposes two efficient transmit-antenna selection (TAS) schemes designed to consider a trade-off between performance and computational complexity in massive MIMO systems. The spectral efficiency and computational complexity of the proposed schemes are analyzed and compared with existing TAS schemes, showing that the proposed algorithms increase the TAS performance and can be used in practical systems. Additionally, the obtained results enable a better understanding of how TAS affects massive MIMO systems.

scholarly journals Massive MIMO-NOMA Networks with Imperfect SIC: Design and Fairness Enhancement

2020 ◽  
Author(s):  
Arthur Sousa de Sena ◽  
Pedro Nardelli
Keyword(s):  
Outage Probability ◽  
Power Allocation ◽  
Interference Cancellation ◽  
Massive Mimo ◽  
Multiple Access ◽  
Mimo Systems ◽  
Multiple Input Multiple Output ◽  
Optimal Solution ◽  
Input Multiple Output ◽  
The Impact

This paper addresses multi-user multi-cluster massive multiple-input-multiple-output (MIMO) systems with non-orthogonal multiple access (NOMA). Assuming the downlink mode, and taking into consideration the impact of imperfect successive interference cancellation (SIC), an in-depth analytical analysis is carried out, in which closed-form expressions for the outage probability and ergodic rates are derived. Subsequently, the power allocation coefficients of users within each sub-group are optimized to maximize fairness. The considered power optimization is simplified to a convex problem, which makes it possible to obtain the optimal solution via Karush-Kuhn-Tucker (KKT) conditions. Based on the achieved solution, we propose an iterative algorithm to provide fairness also among different sub-groups. Simulation results alongside with insightful discussions are provided to investigate the impact of imperfect SIC and demonstrate the fairness superiority of the proposed dynamic power allocation policies. For example, our results show that if the residual error propagation levels are high, the employment of orthogonal multiple access (OMA) is always preferable than NOMA. It is also shown that the proposed power allocation outperforms conventional massive MIMO-NOMA setups operating with fixed power allocation strategies in terms of outage probability.

scholarly journals Analysis of Multiuser Detectors and Performance improvement in DS-CDMA system using Multistage Multiuser Detection Techniques

2021 ◽  
Author(s):  
Ravindrababu Jaladanki ◽  
Krishnarao Ede ◽  
Raja Rao Yasoda
Keyword(s):  
Computational Complexity ◽  
Multiuser Detection ◽  
System Performance ◽  
Interference Cancellation ◽  
Multiple Access ◽  
Signal Amplitude ◽  
Cdma System ◽  
Parallel Interference Cancellation ◽  
Detection Techniques ◽  
Code Division Multiple

Abstract Among the various interferences, the Multiple Access Interference (MAI) is a significant issue in Direct Sequence Code Division Multiple Access (DS-CDMA) system due to its users. When the number of users is increasing the MAI is likewise increments, subsequently the system performance progressively diminishes particularly in fading environment. In this paper, the system performance is improved by the proposed multistage multiuser detection technique called Multistage Multiuser Differencing Partial Parallel Interference Cancellation (DPPIC). This is the combination of Partial Parallel Interference Cancellation (PPIC) and Differencing Parallel Interference Cancellation (DPIC). Multistage Multiuser Parallel Interference Cancellation (PIC) and Multistage Multiuser PPIC techniques that exist gave improved system performance meaning as the number of stages increases the MAI decreases but at the cost of increased computational complexity. The computational complexity was reduced by utilizing Multistage Difference PIC (DPIC) technique but with no improvement in the performance. To improve the system performance as well as reduce the computational complexity Multistage Multiuser Partial Differencing Parallel Interference Cancellation (PDPIC) method can be used. The simulation results show that the proposed DPPIC technique performs better than PIC, PPIC and PDPIC in terms of Bit Error Rate (BER) versus normalized signal amplitude ( i.e., E b / N 0 ), but computational complexity slightly more than PDPIC in fading environment.

scholarly journals Rate-Splitting Multiple Access for Intelligent Reflecting Surface aided Multi-User Communications

2021 ◽  
Author(s):  
Ankur Bansal ◽  
Keshav Singh ◽  
Bruno Clerckx ◽  
Chih-Peng Li ◽  
Mohamed-Slim Alouini
Keyword(s):  
Interference Cancellation ◽  
Multiple Access ◽  
Base Station ◽  
Control Technique ◽  
Decode And Forward ◽  
Cell Edge ◽  
Single Antenna ◽  
Rate Splitting ◽  
Reflecting Surface ◽  
The Impact

Intelligent reflecting surface (IRS) has recently emerged as a promising technology for 6G wireless systems, due to its capability to reconfigure the wireless propagation environment. In this paper, we investigate a Rate-Splitting Multiple Access (RSMA) for IRS-assisted downlink system, where the base station (BS) communicates with single-antenna users with the help of an IRS. RSMA relies on rate-splitting (RS) at the BS and successive interference cancellation (SIC) at the users and provides a generalized multiple access framework. We derive a new architecture called IRS-RS that leverages the interplay between RS and IRS. For performance analysis, we utilize an \textit{on-off control technique} to control the passive beamforming vector of the IRS-RS and derive the closed-form expressions for outage probability of cell-edge users and near users. Moreover, we also analyze the outage behavior of cell-edge users for a sufficiently large number of reflecting elements. Additionally, we also analyze the outage performance of cooperative RS based decode-and-forward (DF)-assisted framework called DF-RS. Through simulation results, it is shown that the proposed framework outperforms the corresponding DF-RS, RS without IRS and IRS-assisted conventional non-orthogonal multiple access (NOMA) schemes. Furthermore, the impact of various system's parameters such as the number of IRS reflecting elements and the number of users on the system performance is revealed.

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.

Design of novel approach for emerging power-domain superposition coding (SC)-using hybrid NOMA-OFDM for 5G communications

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Y.K. Shobha ◽  
H.G. Rangaraju
Keyword(s):  
Interference Cancellation ◽  
Multiple Access ◽  
Mimo System ◽  
Minimum Mean Square Error ◽  
Research Work ◽  
Base Station ◽  
Superposition Coding ◽  
Content Type ◽  
Minimum Mean Squared Error ◽  
Power Domain

PurposeThe suggested work examines the latest developments such as the techniques employed for allocation of power, browser techniques, modern analysis and bandwidth efficiency of nonorthogonal multiple accesses (NOMA) in the network of 5G. Furthermore, the proposed work also illustrates the performance of NOMA when it is combined with various techniques of wireless communication namely network coding, multiple-input multiple-output (MIMO), space-time coding, collective communications, as well as many more. In the case of the MIMO system, the proposed research work specifically deals with a less complex recursive linear minimum mean square error (LMMSE) multiuser detector along with NOMA (MIMO-NOMA); here the multiple-antenna base station (BS) and multiple single-antenna users interact with each other instantaneously. Although LMMSE is a linear detector with a low intricacy, it performs poorly in multiuser identification because of the incompatibility between LMMSE identification and multiuser decoding. Thus, to obtain a desirable iterative identification rate, the proposed research work presents matching constraints among the decoders and identifiers of MIMO-NOMA.Design/methodology/approachTo improve the performance in 5G technologies as well as in cellular communication, the NOMA technique is employed and contemplated as one of the best methodologies for accessing radio. The above-stated technique offers several advantages such as enhanced spectrum performance in contrast to the high-capacity orthogonal multiple access (OMA) approach that is also known as orthogonal frequency division multiple access (OFDMA). Code and power domain are some of the categories of the NOMA technique. The suggested research work mainly concentrates on the technique of NOMA, which is based on the power domain. This approach correspondingly makes use of superposition coding (SC) as well as successive interference cancellation (SIC) at source and recipient. For the fifth-generation applications, the network-level, as well as user-experienced data rate prerequisites, are successfully illustrated by various researchers.FindingsThe suggested combined methodology such as MIMO-NOMA demonstrates a synchronized iterative LMMSE system that can accomplish the optimized efficiency of symmetric MIMO NOMA with several users. To transmit the information from sender to the receiver, hybrid methodologies are confined to 2 × 2 as well as 4 × 4 antenna arrays, and thereby parameters such as PAPR, BER, SNR are analyzed and efficiency for various modulation strategies such as BPSK and QAMj (j should vary from 8,16,32,64) are computed.Originality/valueThe proposed hybrid MIMO-NOMA methodologies are synchronized in terms of iterative process for optimization of LMMSE that can accomplish the optimized efficiency of symmetric for several users under different noisy conditions. From the obtained simulated results, it is found, there are 18%, 23% 16%, and 8% improvement in terms of Bit Error Rate (BER), Least Minimum Mean Squared Error (LMMSE), Peak to Average Power Ratio (PAPR), and capacity of channel respectively for Binary Phase Shift Key (BPSK) and Quadrature Amplitude Modulation (QAM) modulation techniques.

Application of Variable Step Size LMS Algorithm in Multiple Access Interference Cancellation

2014 ◽  
Vol 602-605 ◽  
pp. 3474-3477
Author(s):  
Hui Zhi Zou
Keyword(s):  
Computational Complexity ◽  
Spread Spectrum ◽  
Interference Cancellation ◽  
Multiple Access ◽  
Multiple Access Interference ◽  
Lms Algorithm ◽  
Variable Step Size ◽  
Step Size ◽  
Traditional Algorithm ◽  
Variable Step

MAI influence, using a low computational complexity variable step size LMS algorithm based on the traditional algorithm to find the optimal weight on, and make estimates for the magnitude, thereby offsetting the presence of MAI and estimates for spread spectrum communication system struck a balance between the consideration to be paid for MAI. The improved algorithm reduces the computational complexity of each level, the simulation results also show that the method has better performance.

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