Joint user grouping and power control using whale optimization algorithm for NOMA uplink systems

Joint user grouping and power control using whale optimization algorithm for NOMA uplink systems Bilal ur Rehman1 , Mohammad Inayatullah Babar1 , Arbab Waheed Ahmad2 , Muhammad Amir1 , Waleed Shahjehan1 , Ali Safaa Sadiq3 , Seyedali Mirjalili4 ,6 and Amin Abdollahi Dehkordi5 1 Department of Electrical Engineering, University of Engineering and Technology, Peshawar, Pakistan Department of Electrical and Computer Engineering, PAF-IAST, Haripur, Pakistan 3 School of Mathematics and Computer Science, University of Wolverhampton, Wulfruna Street Wolverhampton, WV1 1LY, United Kingdom 4 Centre of Artificial Intelligence Research and Optimisation, Torrens University, Brisbane, Australia 5 Computer Engineering Faculty, Najafabad Branch, Islamic Azad University, Najafabad, Iran 6 Yonsei Frontier Lab, Yonsei University, Seoul, South Korea 2 ABSTRACT Submitted 4 August 2021 Accepted 20 January 2022 Published 11 March 2022 Corresponding authors Bilal ur Rehman, Ali Safaa Sadiq, The non-orthogonal multiple access (NOMA) scheme has proven to be a potential candidate to enhance spectral potency and massive connectivity for 5G wireless networks. To achieve effective system performance, user grouping, power control, and decoding order are considered to be fundamental factors. In this regard, a joint combinatorial problem consisting of user grouping and power control is considered, to obtain high spectral-efficiency for NOMA uplink system with lower computational complexity. To solve the joint problem of power control and user grouping, for Uplink NOMA, we have used a newly developed meta-heuristicnature-inspired optimization algorithm i.e., whale optimization algorithm (WOA), for the first time. Furthermore, for comparison, a recently initiated grey wolf optimizer (GWO) and the well-known particle swarm optimization (PSO) algorithms were applied for the same joint issue. To attain optimal and sub-optimal solutions, a NOMA-based model was used to evaluate the potential of the proposed algorithm. Numerical results validate that proposed WOA outperforms GWO, PSO and existing literature reported for NOMA uplink systems interms of spectral performance. In addition, WOA attains improved results in terms of joint user grouping and power control with lower system-complexity when compared to GWO and PSO algorithms. The proposed work is a novel enhancement for 5G uplink applications of NOMA systems. Academic editor Ayaz Ahmad Additional Information and Declarations can be found on page 21 Subjects Artificial Intelligence, Computer Networks and Communications Keywords Whale optimization algorithm, Grey wolf optimization, Particle swarm optimization, Wireless communication, Uplink, NOMA, 5G DOI 10.7717/peerj-cs.882 Copyright 2022 Rehman et al. Distributed under Creative Commons CC-BY 4.0 OPEN ACCESS INTRODUCTION Multiple access approaches are increasingly gaining importance in modern mobile communication systems, primarily due to the overwhelming increase in the communication demands at both the user and device level. Over past few years, non-orthogonal multiple access (NOMA) (Ding et al., 2017a; Ding et al., 2014; Ding et al., 2017b; Benjebbovu et al., How to cite this article Rehman B, Babar MI, Ahmad AW, Amir M, Shahjehan W, Sadiq AS, Mirjalili S, Dehkordi AA. 2022. Joint user grouping and power control using whale optimization algorithm for NOMA uplink systems. PeerJ Comput. Sci. 8:e882 http://doi.org/10.7717/peerj-cs.882 2013) schemes have earned significant attention for supporting the huge connectivity in contemporary wireless communication systems. The NOMA schemes are currently considered to be the most promising contender for the 5G and beyond 5G (B5G) wireless communications, which are capable of accessing massive user connections and attaining high spectrum performance. Moreover, a report has been published recently regarding the Third Generation Partnership Project for determining the effectiveness of NOMA schemes for several applications or development scenarios, particularly for ultra-reliable low latency communications (URLLC), enhanced mobile broadband (eMBB), and massive machine type communications (mMTC) (Benjebbour et al., 2013). Contrary to the classic orthogonal multiple access (OMA) approaches, the NOMA schemes can offer services to multiple users in the same space/code/frequency/time resource block (RB). The NOMA schemes are also capable of differentiating the users that have distinct channel settings. These schemes are mainly inclined at strengthening connectivity and facilitating users with an efficient broad-spectrum (Islam et al., 2016; Dai et al., 2015). Some recent studies (Chen, Wang & Zhang, 2018; Wang et al., 2019; Shahini & Ansari, 2019) have discussed the effective use of the NOMA approach in standard frameworks for Internet of Things (IoT) systems and Vehicle-to-Everything (V2X) networks. The successive interference cancellation (SIC) technique, which is pertinent for multi-user detection and decoding is implemented for the NOMA scheme at the receiver end. The SIC technique operates differently for the downlink and uplink scenarios. In the downlink NOMA scenario, SIC is applied at the receiver end, where high energy is consumed during processing when a lot of users are considered in the NOMA group. For that reason, two users are typically considered in a group for optimum grouping/pairing of users in the case of the downlink NOMA system (Al-Abbasi & So, 2016; He, Tang & Che, 2016). Whereas in the uplink NOMA systems, it is possible to employ SIC at the base station (BS) that has a higher processing capacity. Moreover, in uplink NOMA, multiple users are allowed to transmit in a grant-free approach that leads to a significantly reduced latency rate. From a practical perspective, the user-pairing/grouping and power control schemes in uplink/downlink NOMA systems are critically required to achieve an appropriate trade-off between the performance of the NOMA system and the computational complexity of the SIC technique. Over the past few years, several studies have discussed different prospects regarding the maximization of sum rate (Zhang et al., 2016a; Ding, Fan & Poor, 2015; Ali, Tabassum & Hossain, 2016), the transmission power control approaches (Wei et al., 2017), and fairness (Liu, Mähönen & Petrova, 2015; Liu et al., 2016) for user pairing/grouping NOMA systems. Regarding the maximization of sum rate, a two-user grouping scheme based on a unique channel gain is demonstrated in Ding, Fan & Poor (2015) whereas another study (Ali, Tabassum & Hossain, 2016) presented a novel framework for pertinent user-pairing/grouping approaches to assign the same resource block to multiple users. In reference to the user pairing schemes (Sedaghat & Müller, 2018) used the Hungarian algorithm with a modified cost function to investigate optimum allocation for three distinct cases in the uplink NOMA system. Furthermore, several matching game-based (Liang et al., 201 (...truncated)