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author:

Zhang, J. (Zhang, J..) [1] | Zheng, H. (Zheng, H..) [2] | Chen, Z. (Chen, Z..) [3] (Scholars:陈哲毅) | Chen, X. (Chen, X..) [4] (Scholars:陈星) | Min, G. (Min, G..) [5]

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Scopus

Abstract:

In the era of the Internet of Things (IoT), it is a promising way to improve system energy utility and better meet users’ requirements for quality of service (QoS) via integrating non-orthogonal multiple access (NOMA) and mobile edge computing (MEC) technologies. In light of this idea, we investigate device access, sub-channel division, and transmission power allocation for NOMA-enabled IoT systems. To maximize the energy utility of IoT systems while satisfying the minimum demands of IoT devices (IoTDs) on achievable uplink data rate, a joint optimization problem is formulated with the consideration of device access, sub-channel division, and transmission power allocation. Due to the non-convexity of this problem, we propose an alternating optimization algorithm aiming to find the optimal solution. The proposed algorithm first decomposes the joint optimization problem into three sub-problems through the block coordinate descent (BCD), and then obtains the near-optimal solution by solving the decomposed sub-problems alternately. Extensive simulations validate our analysis for the convergence of the proposed algorithm. The numerical results demonstrate that the proposed algorithm significantly outperforms the benchmark algorithms in terms of improving system energy utility. IEEE

Keyword:

Bandwidth device access Energy efficiency Internet of Things Mobile edge computing NOMA non-orthogonal multiple access Optimization Resource management sub-channel division transmission power allocation Wireless communication

Community:

  • [ 1 ] [Zhang J.]College of Computer and Control Engineering, Minjiang University, Fuzhou, China
  • [ 2 ] [Zheng H.]Fujian Key Laboratory of Network Computing and Intelligent Information Processing, Fuzhou, China
  • [ 3 ] [Chen Z.]Fujian Key Laboratory of Network Computing and Intelligent Information Processing, Fuzhou, China
  • [ 4 ] [Chen X.]Fujian Key Laboratory of Network Computing and Intelligent Information Processing, Fuzhou, China
  • [ 5 ] [Min G.]Department of Computer Science, College of Engineering, Mathematics, and Physical Sciences, University of Exeter, Exeter, U.K

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Source :

IEEE Internet of Things Journal

ISSN: 2327-4662

Year: 2023

Issue: 19

Volume: 10

Page: 1-1

8 . 2

JCR@2023

8 . 2 0 0

JCR@2023

ESI HC Threshold:32

JCR Journal Grade:1

CAS Journal Grade:1

Cited Count:

WoS CC Cited Count:

SCOPUS Cited Count: 3

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 0

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