Multi-cell Non-orthogonal Multiple Access Networks Research Articles

Ambient BackCom in beyond 5G NOMA networks: A multi-cell resource allocation framework

The research of Non-Orthogonal Multiple Access (NOMA) is extensively used to improve the capacity of networks beyond the fifth-generation. The recent merger of NOMA with ambient Backscatter Communication (BackCom), though opening new possibilities for massive connectivity, poses several challenges in dense wireless networks. One such challenge is the performance degradation of ambient BackCom in multi-cell NOMA networks under the effect of inter-cell interference. Driven by providing an efficient solution to the issue, this article proposes a new resource allocation framework that uses a duality theory approach. Specifically, the sum rate of the multi-cell network with backscatter tags and NOMA user equipment is maximized by formulating a joint optimization problem. To find the efficient base station transmit power and backscatter reflection coefficient in each cell, the original problem is first divided into two subproblems, and then the closed form solution is derived. A comparison with the Orthogonal Multiple Access (OMA) ambient BackCom and pure NOMA transmission has been provided. Simulation results of the proposed NOMA ambient BackCom indicate a significant improvement over the OMA ambient BackCom and pure NOMA in terms of sum-rate gains.

Resource Allocation for Multi-Cell IRS-Aided NOMA Networks

This article proposes a novel framework of resource allocation in multi-cell intelligent reflecting surface (IRS) aided non-orthogonal multiple access (NOMA) networks, where an IRS is deployed to enhance the wireless service. The problem of joint user association, subchannel assignment, power allocation, phase shifts design, and decoding order determination is formulated for maximizing the achievable sum rate. The challenging mixed-integer non-linear problem is decomposed into an optimization subproblem (P1) with continuous variables and a matching subproblem (P2) with integer variables. In an effort to tackle the non-convex optimization problem (P1), iterative algorithms are proposed for allocating transmission power, designing reflection matrix, and determining decoding order by invoking relaxation methods such as convex upper bound substitution, successive convex approximation, and semidefinite relaxation. In terms of the combinational problem (P2), swap matching-based algorithms are developed for achieving a two-sided exchange-stable state among users, BSs and subchannels. Numerical results demonstrate that: i) the sum rate of multi-cell NOMA networks is capable of being increased by 35% with the aid of the IRS; ii) the proposed algorithms for multi-cell IRS-aided NOMA networks can enjoy 22% higher energy efficiency than conventional NOMA counterparts; iii) the trade-off between spectrum efficiency and coverage area can be tuned by judiciously selecting the location of the IRS.

Secure Non-Orthogonal Multiple Access: An Interference Engineering Perspective

Non-orthogonal multiple access (NOMA) is an efficient approach that can improve spectrum utilization and support massive connectivity for next-generation wireless networks. However, over a wireless channel, the superimposed NOMA signals are highly susceptible to eavesdropping, potentially leading to severe leakage of confidential information. In this article, we unleash the potential of network interference and exploit it constructively to enhance physi-cal-layer security in NOMA networks. In particular, three different types of network interference, including artificial noise, specifically-designed jamming signals, and inter-user interference, are well engineered to intentionally reduce information leakage while mitigating the effect on signal reception quality of legitimate users, thereby significantly enhancing the transmission security of NOMA. Furthermore, we propose interference engineering strategies for more advanced full-duplex NOMA, intelligent reflecting surface NOMA, cognitive radio NOMA, and multi-cell NOMA networks, and discuss several open research problems and challenges, which could inspire innovative interference engineering designs for secure NOMA communications.

User Association and Power Allocation for Multi-Cell Non-Orthogonal Multiple Access Networks

In this paper, user association and power allocation are investigated in a non-orthogonal multiple access (NOMA)-based multi-cell network. In order to perform successive interference cancellation (SIC) techniques for removing the intra-base station (BS) interference, the optimal decoding order is derived for all users associated with the same BS. In an effort to improve the system, a sum rate maximization problem is formulated by jointly designing user association and power allocation. Two game theory based algorithms are proposed to obtain the stable user structure by dividing users into different BSs’ clusters, where the sub-optimal and global optimal solutions can be achieved. The properties of the proposed algorithms, including complexity, convergence, stability and optimality, are analyzed. Based on the quality-of-service (QoS) constraint, the closed-from solutions for power allocation are derived, and thus the expressions for the sum rate of all users in each cluster is obtained. Moreover, the case that the QoS threshold cannot be achieved by all users in each cluster is considered. Simulation results demonstrate that: i) the proposed user association algorithms and the closed-form solutions for power allocation can significantly enhance the sum rate and outage probability; and ii) the proposed NOMA-based system is capable of achieving promising gains over the conventional orthogonal multiple access (OMA)-based framework in the multi-cell scenario.

Joint D2D Group Association and Channel Assignment in Uplink Multi-Cell NOMA Networks: A Matching-Theoretic Approach

This paper studies joint device-to-device (D2D) group association and channel assignment in uplink multi-cell non-orthogonal multiple-access (NOMA) networks. Particularly, the goal is to assign D2D groups to cellular user channels at each base-station, while accounting for negative network externality due to the interference caused by pairing a user with a D2D group. To that end, a multi-objective signal-to-interference-plus-noise ratio (SINR)-maximizing power allocation solution procedure is proposed to determine the optimal power allocation for each (D2D group, user) pair, while meeting quality-of-service (QoS) requirements. After that, the joint D2D group association and channel assignment problem is modeled as a student-project allocation with preferences over (student, project) pairs matching problem. More specifically, two polynomial-time complexity stable matching algorithms are proposed to pair D2D groups with users, and associate them with base-stations. Simulation results are presented to evaluate the proposed matching algorithms when combined with the devised solution procedure, and compare them to a joint D2D group association, channel assignment and power allocation (J-GA-CA-PA) scheme. More importantly, the proposed algorithms are shown to efficiently yield comparable SINR-per user and D2D receiver-to the J-GA-CA-PA scheme, while maintaining QoS requirements.

User association and channel assignment in downlink multi-cell NOMA networks: A matching-theoretic approach

This paper studies the problem of stable user association and channel assignment in downlink multi-cell non-orthogonal multiple-access (NOMA) networks. To be specific, the goal is to assign network users to the channels at each base station, while accounting for inter-user interference and maintaining quality of service (QoS) per user. To that end, a low-complexity iterative solution procedure is devised to obtain the optimal power allocation for proportional fairness signal-to-interference-plus-noise ratio (SINR)-based maximization, which is then utilized to determine the preferences of network users over the channels available at each base station and the preferences of base stations over the network users. In turn, a many-to-one matching-theoretic model based on the student-project allocation problem is applied. Particularly, two polynomial-time complexity stable matching algorithms are proposed to associate users with base stations and perform channel assignment, such that no user or base station would deviate and change its association or channel assignment unilaterally. To validate the efficacy of the proposed solution procedure and stable matching algorithms, extensive simulation results are presented to compare them to a centralized joint user association, channel assignment, and power allocation (C-J-UA-CA-PA) scheme. It is demonstrated that the proposed algorithms efficiently associate users with base stations and assign them to channels as well as efficiently yielding comparable SINR per user to the C-J-UA-CA-PA scheme, while maximizing proportional fairness and satisfying QoS constraints.

Suppressing Interference and Power Allocation Over the Multi-Cell MIMO-NOMA Networks

Non-orthogonal multiple access (NOMA) can dramatically improves the spectral efficiency, while the cell-edge user’s performance will be fiercely degraded due to inter-cell interference in the multi-cell NOMA networks. In this letter, we invoke interference alignment (IA) to resist the performance loss of the cell-edge users and propose a cooperative transmission scheme for the multi-cell NOMA networks. Then, we formulate an optimization problem in terms of joint multi-cell power allocation to seek an optimal transmission scheme. To solve the challenging nonconvex problem, the tight lower bound function and the logarithmic change of the variables are employed to convert the prime problem into a convex optimization problem, consequently obtaining a suboptimal solution through iteratively updating the lower bound. Finally, we demonstrate the efficacy of the proposed scheme through the numerical simulations.