Multi-cell Non-orthogonal Multiple Access Research Articles

Energy efficiency optimization for 6G multi-IRS multi-cell NOMA vehicle-to-infrastructure communication networks

Intelligent Reflecting Surfaces (IRS), software-controlled metasurfaces, have emerged as an upcoming sixth-generation (6G) wireless communication technology. IRS intelligently manipulates and optimizes signal propagation using a large-scale array of intelligent elements, enhancing signal coverage, increasing capacity, mitigating path loss, and combating multipath fading This work provides a new energy-efficiency model for multi-IRS-assisted multi-cell non-orthogonal multiple access (NOMA) vehicular to infrastructure communication networks. The objective is the joint optimization of the total power budget at the roadside unit (RSU), NOMA power allocation for the user equipment, and designing phase shifts for IRS in each cell to maximize the achievable energy efficiency of the system. Due to non-convexity, the original non-convex problem is first decoupled and transformed using block coordinate descent and successive convex approximation methods. Then, an efficient solution is achieved using Gradient-based and interior-point methods. We also consider two benchmark schemes: (1) NOMA power optimization at RSU with random phase shift design at IRS and (2) orthogonal multiple access power allocation with optimal phase shift design at IRS. Numerical results show the superiority of the proposed solution compared to the benchmark schemes. The proposed solution outperforms the benchmarks, demonstrating a 59.57% and 151.21% improvement over the NOMA and orthogonal schemes, respectively, at pct=2 dBm. Additionally, it shows up to a 10.43% better performance than OMA at 10 IRS elements.

An optimization framework for RIS-based energy-efficient multi-cell NOMA systems

Non-orthogonal multiple access (NOMA) is a highly promising multiple access strategy for wideband communication systems due to its high spectral efficiency. However, in multi-cell multi-band systems, interference issues can arise from resource sharing among multiple users, which limits the potential of NOMA. To tackle these issues, in this paper, we study a NOMA system where reconfigurable intelligent surfaces (RIS) are employed across multiple cells with multiple users clusters. Specifically, we propose an optimization framework to maximize the system energy efficiency (EE) through jointly designing the transmission beamformer at each base station, the RIS phase shifts and the corresponding binary selection matrix indicating which elements of the RIS should be used to serve a specific cell. Our optimization framework takes into account the minimum rate requirements of users, the successive interference cancellation (SIC) decoding-based rate constraint, fairness among users as well as the maximum allowed transmission power. The resulting non-convex problem is solved by using an alternating optimization algorithm, wherein semidefinite programming (SDP), successive convex approximation (SCA), and penalty-based difference-of-convex (DC) programming are used to reach a solution. Simulation results show that the proposed system outperforms conventional orthogonal access in terms of EE performance, the achievable rate, and power consumption. Also, the results revealed the critical transmission power level for NOMA beyond which the EE starts decaying. Moreover, the proposed NOMA system shows a limited EE performance compared to the conventional orthogonal access as the number of clusters exceeds a certain limit.

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.

Joint User-Slice Pairing and Association Framework Based on H-NOMA in RAN Slicing.

Multiservice cellular in Radio Access Network (RAN) Slicing has recently attained huge interest in enhancing isolation and flexibility. However, RAN slicing in heterogeneous networks (HetNet) architecture is not adequately explored. This study proposes a pairing-network slicing (NS) approach for Multiservice RAN that cares about quality of service (QoS), baseband resources, capacities of wireless fronthaul and backhaul links, and isolation. This intriguing approach helps address the increased need for mobile network traffic produced by a range of devices with various QoS requirements, including improved dependability, ultra-reliability low-latency communications (uRLLC), and enhanced broadband Mobile Services (eMBB). Our study displays a unique RAN slicing framework for user equipment (UE) for joint user-association. Multicell non-orthogonal multiple access (NOMA)-based resource allocation across 5G HetNet under successive interference cancelation (SIC) is seen to achieve the best performance. Joint user-slice pairing and association are optimization problems to maximize eMBB UE data rates while fulfilling uRLLC latency and reliability criteria. This is accomplished by guaranteeing the inter- and intra-isolation property of slicing to eliminate interferences between eMBB and uRLLC slices. We presented the UE-slice association (U-S. A) algorithm as a one-to-many matching game to create a stable connection between UE and one of the base stations (BSs). Next, we use the UE-slice pairing (U-S. P) algorithm to find stable uRLLC-eMBB pairs that coexist on the same spectrum. Numerical findings and performance analyses of the submitted association and pairing technique show they can all be RAN slicing criteria. We prove that the proposed algorithm optimizes system throughput while decreasing uRLLC latency by associating and pairing every uRLLC user in mini slots.

Optimal SIC Ordering and Power Allocation in Downlink Multi-Cell NOMA Systems

In this work, we propose a globally optimal joint successive interference cancellation (SIC) ordering and power allocation (JSPA) algorithm for the sum-rate maximization problem in downlink multi-cell non-orthogonal multiple access (NOMA) systems. The proposed algorithm is based on the exploration of base stations (BSs) power consumption, and closed-form of optimal powers obtained for each cell. Although the optimal JSPA algorithm scales well with larger number of users, it is still exponential in the number of cells. For any suboptimal decoding order, we propose a low-complexity near-optimal joint rate and power allocation (JRPA) strategy in which the complete rate region of users is exploited. Furthermore, we design a near-optimal semi-centralized JSPA framework for a two-tier heterogeneous network such that it scales well with larger number of small-BSs and users. Numerical results show that JRPA highly outperforms the case that the users are enforced to achieve their channel capacity by imposing the well-known SIC necessary condition on power allocation. Moreover, the proposed semi-centralized JSPA framework significantly outperforms the fully distributed framework, where all the BSs operate in their maximum power budget. Therefore, the centralized JRPA and semi-centralized JSPA algorithms with near-optimal performances are good choices for larger number of cells and users.

User scheduling and power allocation for downlink multi-cell multi-carrier NOMA systems

In Non-Orthogonal Multiple Access (NOMA), the best way to fully exploit the benefits of the system is the efficient resource allocation. For the NOMA power domain, the allocation of power and spectrum require solving the mixed-integer nonlinear programming NP-hard problem. In this paper, we investigate user scheduling and power allocation in Multi-Cell Multi-Carrier NOMA (MCMC-NOMA) networks. To achieve that, we consider Weighted Sum Rate Maximization (WSRM) and Weighted Sum Energy Efficiency Maximization (WSEEM) problems. First, we tackle the problem of user scheduling for fixed power using Fractional Programming (FP), the Lagrange dual method, and the decomposition method. Then, we consider Successive Pseudo-Convex Approximation (SPCA) to deal with the WSRM problem. Finally, for the WSEEM problem, SPCA is utilized to convert the problem into separable scalar problems, which can be parallelly solved. Thus, the Dinkelbach algorithm and constraints relaxation are used to characterize the closed-form solution for power allocation. Extensive simulations have been implemented to show the efficiency of the proposed framework and its superiority over other existing schemes.

QoS-Aware User Grouping Strategy for Downlink Multi-Cell NOMA Systems

In multi-cell non-orthogonal multiple access (NOMA) systems, designing an appropriate user grouping strategy is an open problem due to diverse quality of service (QoS) requirements and inter-cell interference. In this paper, we exploit both game theory and graph theory to study QoS-aware user grouping strategies, aiming at minimizing power consumption in downlink multi-cell NOMA systems. Under different QoS requirements, we derive the optimal successive interference cancellation (SIC) decoding order with inter-cell interference, which is different from existing SIC decoding order of increasing channel gains, and obtain the corresponding power allocation strategy. Based on this, the exact potential game model of the user grouping strategies adopted by multiple cells is formulated. We prove that, in this game, the problem for each player to find a grouping strategy can be converted into the problem of searching for specific negative loops in the graph composed of users. Bellman-Ford algorithm is expanded to find these negative loops. Furthermore, we design a greedy based suboptimal strategy to approach the optimal solution with polynomial time. Extensive simulations confirm the effectiveness of grouping users with consideration of QoS and inter-cell interference, and show that the proposed strategies can considerably reduce total power consumption comparing with reference strategies.

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.

Distributed Dual Optimization for the Uplink of Multi-Cell NOMA

This paper studies distributed power control for the uplink of multi-cell non-orthogonal multiple access (NOMA) systems. Within a cell, the transmissions of different users are modeled as a Gaussian multiple access channel, treating inter-cell interference as additive Gaussian noise. By analyzing the geometry of the feasible power region, using successive interference cancellation at each base station is proved to be optimal in minimizing the total transmission power of all users under rate constraints. The decoding order at each base station, however, remains to be determined. If the decoding order is decided without base station cooperation, the overall control algorithm is fully distributed but is suboptimal in general. To achieve optimality, a partially distributed algorithm is designed, which requires base stations to exchange control messages. Given any feasible instance, the algorithm is proved to converge to the optimal solution. The performance of the fully distributed and partially distributed power control algorithms is compared by computer simulations. The fully distributed algorithm is nearly optimal in terms of outage probability. When a high data rate is required, the partially distributed algorithm is able to reduce the total power consumption by about 20%.

Energy Efficiency Maximization for Multi-Cell Multi-Carrier NOMA Networks.

As energy efficiency (EE) is a key performance indicator for the future wireless network, it has become a significant research field in communication networks. In this paper, we consider multi-cell multi-carrier non-orthogonal multiple access (MCMC-NOMA) networks and investigate the EE maximization problem. As the EE maximization is a mixed-integer nonlinear programming NP-hard problem, it is difficult to solve directly by traditional optimization such as convex optimization. To handle the EE maximization problem, we decouple it into two subproblems. The first subproblem is user association, where we design a matching-based framework to perform the user association and the subcarriers’ assignment. The second subproblem is the power allocation problem for each user to maximize the EE of the systems. Since the EE maximization problem is still non-convex with respect to the power domain, we propose a two stage quadratic transform with both a single ratio quadratic and multidimensional quadratic transform to convert it into an equivalent convex optimization problem. The power allocation is obtained by iteratively solving the convex problem. Finally, the numerical results demonstrate that the proposed method could achieve better EE compared to existing approaches for non-orthogonal multiple access (NOMA) and considerably outperforms the fractional transmit power control (FTPC) scheme for orthogonal multiple access (OMA).

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.

Performance of Multi-Cell mmWave NOMA Networks With Base Station Cooperation

Coordinated multipoint transmission is applied to multi-cell millimeter wave (mmWave) non-orthogonal multiple access (NOMA) networks in downlink transmission in this letter. Multiple cooperative base stations (BSs) jointly transmit same signal to a cell-edge user as a far user. And each BS individually serves a near user at the same beamwidth with NOMA. Subsequently, the outage probability, outage sum rate and energy efficiency are derived. Further, simulation results are provided to verify the correctness of analytical derivation and demonstrate the cell-edge user's performance improvement as well as the superiority of BS cooperation in multi-cell mmWave NOMA networks.

A Note on Decoding Order in User Grouping and Power Optimization for Multi-Cell NOMA With Load Coupling

In this technical note, we present a new theoretical result for multi-cell non-orthogonal multiple access (NOMA). For multi-cell scenarios, a so-called load-coupling model has been proposed earlier to characterize the presence of mutual interference for NOMA, and the optimization process relies on the use of fixed-point iterations across cells. One difficulty here is that the order of decoding for successive interference cancellation (SIC) in NOMA is generally not known a priori. This is because the decoding order in one cell depends on interference, which, in turn, is governed by resource usage in other cells, and vice versa. To achieve convergence, previous works have used workarounds that pose restrictions to NOMA, such that the SIC decoding order remains throughout the fixed-point iterations. As a comment to the previous works, we derive and prove the following result: The convergence is guaranteed, even if the order changes over the iterations. The result not only waives the need of previous workarounds, but also implies that a wide class of optimization problems for multi-cell NOMA is tractable, as long as that for single cell is.

Power Minimization for Multi-Cell Uplink NOMA With Imperfect SIC

In this letter, we investigate a multi-cell uplink non-orthogonal multiple access (NOMA) system with imperfect successive interference cancellation (SIC). The objective of the formulated optimization problem is to minimize the total power consumption under users’ quality-of-service constraints. The considered problem is first transformed into a linear programming problem, upon which centralized and distributed optimal solutions are proposed. Numerical results are presented to verify the performance of the proposed solutions and evaluate the impact of imperfect SIC on the system performance.

An Analysis on Secure Millimeter Wave NOMA Communications in Cognitive Radio Networks

In this paper, an easy analysis framework is developed to evaluate the reliability and security of the secondary receivers (SU-Rxs) in millimeter wave (mmWave) non-orthogonal multiple access (NOMA) aided cognitive radio (CR) networks, where secondary transmitters (SU-Txs) transmit confidential messages to SU-Rxs belonging to different regions under the interference temperature constraint of the primary receiver (PU-Rx). Considering that randomly located eavesdroppers and primary user may be in the signal beam emitted by the SU-Txs, information leakage and interference to the primary network will be inevitable issues. Motivated by these challenges, combining the key features of multi-cell mmWave networks and NOMA communications, the closed-form expressions of three key performance metrics of connection outage probability (COP), secrecy outage probability (SOP), and secrecy throughput (ST) are derived by using the sector eavesdropper-exclusion zone, and the reliability and secrecy performance of the secondary networks are measured by different system parameters. The obtained performance evaluation results have demonstrated that the interference temperature constraint of the PU-Rx can be used to balance the security and reliability of the secondary networks. The reliability and security of paired NOMA users can be improved by using reasonable power allocation factor and sector eavesdropper-exclusion zone. Meanwhile, the connection performance of paired NOMA users is better than orthogonal multiple access (OMA). Furthermore, various system parameters can be reasonably set in conjunction with blockage and inter-cell interference to achieve optimal network’s performance.

Non-Orthogonal Multiple Access (NOMA) in Uplink Poisson Cellular Networks With Power Control

This paper develops an analytical framework for multi-cell uplink NOMA systems based on stochastic geometry. We propose two scenarios for the clustering of NOMA UEs and derive the Laplace transform of the inter-cell interference taking into account uplink power control. We utilize two different ordering techniques, namely mean signal power- (MSP-) and instantaneous signal-to-intercell-interference-and-noise-ratio- (ISĨNR-) based, for the successive interference cancellation process at the BSs. For each technique, we present a signal-to-interference-and-noise-ratio (SINR) analysis and derive the transmission success probabilities for the NOMA UEs. We show that uplink power control, which generally reduces the signal power disparity between UEs, does not necessarily degrade the NOMA performance. We discuss how UE clustering and the power control exponent impact this finding. ISĨNR-based ordering, which jointly considers path loss, fading, inter-cell interference, and noise, is generally superior to MSP-based ordering. Moreover, we show that the advantage of NOMA vanishes when the target SINR exceeds a certain threshold. A comparison of the two UE clustering scenarios indicates that excluding the UEs which are relatively far from the serving BS may improve the NOMA performance.

Load Coupling and Energy Optimization in Multi-Cell and Multi-Carrier NOMA Networks

In this paper, we investigate energy optimization in multi-cell and multi-carrier non-orthogonal multiple access (NOMA) networks. We apply a load-coupling model for NOMA networks to capture the coupling relation of mutual interference among cells. With this analytical tool, we formulate an energy minimization problem in a NOMA-based load-coupled system, where optimizing load-rate-power allocation, and determining decoding order and user grouping are the key aspects. Theoretically, we prove that the minimum consumed energy can be achieved by using all the time-frequency resources in each cell to deliver users’ demand, and allowing all the users to share resource units. From a practical perspective, we consider three types of NOMA grouping schemes, i.e., all-user grouping, partitioned and non-partitioned grouping. We develop tailored solutions for each grouping scheme to enable efficient load-rate-power optimization. These three algorithmic components are embedded into a power-adjustment framework to provide energy-efficient solutions for NOMA networks. Numerical results demonstrate promising energy-saving gains of NOMA over orthogonal multiple access in large-scale cellular networks, in particular for high-demand and resource-limited scenarios. The results also show fast convergence of the proposed algorithms and demonstrate the effectiveness of the solutions.

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.