Joint Computing Resource, Power, and Channel Allocations for D2D-Assisted and NOMA-Based Mobile Edge Computing

Abstract

Mobile edge computing (MEC) and non-orthogonal multiple access (NOMA) have been considered as the promising techniques to address the explosively growing computation-intensive applications and accomplish the requirement of massive connectivity in the fifth-generation networks. Moreover, since the computing resources of the edge server are limited, the computing load of the edge server needs to be effectively alleviated. In this paper, by exploiting device-to-device (D2D) communication for enabling user collaboration and reducing the edge server's load, we investigate the D2D-assisted and NOMA-based MEC system. In order to minimize the weighted sum of the energy consumption and delay of all users, we jointly optimize the computing resource, power, and channel allocations. Regarding the computing resource allocation, we propose an adaptive algorithm to find the optimal solution. Regarding the power allocation, we present a novel power allocation algorithm based on the particle swarm optimization (PSO) for the single NOMA group comprised of multiple cellular users. Then, for the matching group comprised of a NOMA group and D2D pairs, we theoretically derive the interval of optimal power allocation and propose a PSO-based algorithm to solve it. Regarding the channel allocation, we propose a one-to-one matching algorithm based on the Pareto improvement and swapping operations and extend the one-to-one matching algorithm to a many-to-one matching scenario. Finally, we propose a scheduling-based joint computing resource, power, and channel allocations algorithm to achieve the joint optimization. The simulation results show that the proposed solution can effectively reduce the weighted sum of the energy consumption and delay of all users. INDEX TERMSMobile edge computing (MEC), non-orthogonal multiple access (NOMA), device-to-device (D2D) communications, power allocation, and channel allocation.

Optimal Task Partition and Power Allocation for Mobile Edge Computing with NOMA

“…Even though MEC and NOMA have been widely studied in recent years, only handful research works have been carried to study the combination of NOMA and multiuser MEC networks [6,[23][24][25][26][27][28][29]. To further enhance the spectrum efficiency and the performance of multiuser MEC networks, NOMA uplink transmission and downlink transmission were proposed to be applied to MEC [23].…”

“…Besides, resource allocation research works have been carried out to enhance the NOMA enable MEC system performance [6,25,26]. Among these research works, the energy consumption minimization was investigated for a multiuser NOMA-MEC system [24,28]. In [24], an efficient algorithm of optimizing offloading tasks and offloading power levels of each user was proposed to minimize the system energy consumption for NOMA based MEC system [24] and D2D-assisted and NOMA-based MEC system [28], respectively.…”

“…Among these research works, the energy consumption minimization was investigated for a multiuser NOMA-MEC system [24,28]. In [24], an efficient algorithm of optimizing offloading tasks and offloading power levels of each user was proposed to minimize the system energy consumption for NOMA based MEC system [24] and D2D-assisted and NOMA-based MEC system [28], respectively. Different from OMA-MEC and pure NOMA-MEC systems proposed in [23,24], a hybrid NOMA scheme was proposed in [25], where a user can first offload parts of its task within the time slot allocated to another user and then April 30, 2019 DRAFT offload the remaining task during the time slot solely occupied by itself.…”

A Novel Access Control and Energy-Saving Resource Allocation Scheme for D2D Communication in 5G Networks

“…However, scheduling and resource allocation were considered individually. By exploiting D2D communication for enabling user collaboration and reducing the edge server's load, the D2D-assisted and nonorthogonal multiple access based mobile edge computing system was investigated by Diao et al [17], which just considered power, channel allocation, and computing resources without taking D2D access control problem into account. e resource allocation problem for uplink multicarrier nonorthogonal multiple access in D2D underlay cellular networks was investigated by Zheng et al [18], which did not consider D2D access control and energy minimization.…”

Two policies for wireless non‐orthogonal multiple access systems: System model and performance enhancement of far user

“…Particularly, NOMA scheme is invoked to support more downlink users in the same time, and D2D‐enabled multihop transmission is required. Diao et al 29 examined D2D scheme for enabling user collaboration and reducing the edge server's load. They introduced new paradigm, namely, D2D‐assisted and NOMA‐based mobile edge computing networks.…”