In this paper, facilitated via the flexible software defined structure of the radio access units in 5G, we propose a novel dynamic multiple access technology selection among orthogonal multiple access (OMA) and non-orthogonal multiple access (NOMA) techniques for each subcarrier. For this setup, we formulate a joint resource allocation problem where a new set of access technology selection parameters along with power and subcarrier are allocated for each user based on each user's channel state information. Here, we define a novel utility function taking into account the rate and costs of access technologies. This cost reflects both the complexity of performing successive interference cancellation and the complexity incurred to guarantee a desired bit error rate. This utility function can inherently demonstrate the trade-off between OMA and NOMA. Due to non-convexity of our proposed resource allocation problem, we resort to successive convex approximation where a two-step iterative algorithm is applied in which a problem of the first step, called access technology selection, is transformed into a linear integer programming problem, and the nonconvex problem of the second step, referred to power allocation problem, is solved via the difference-of-convex-functions (DC) programming. Moreover, the closed-form solution for power allocation in the second step is derived. For diverse network performance criteria such as rate, simulation results show that the proposed new dynamic access technology selection outperforms single-technology OMA or NOMA multiple access solutions.
@cite_22: Orthogonal Frequency Division Multiplexing Access (OFDMA) has been increasingly deployed in various emerging and evolving cellular systems to reduce interference and improve overall system performance. However, in these systems Inter-Cell Interference (ICI) still poses a real challenge that limits the system performance, especially for users located at the cell edge. Inter-cell interference coordination (ICIC) has been investigated as an approach to alleviate the impact of interference and improve performance in OFDMA-based systems. A common ICIC technique is interference avoidance in which the allocation of the various system resources (e.g., time, frequency, and power) to users is controlled to ensure that the ICI remains within acceptable limits. This paper surveys the various ICIC avoidance schemes in the downlink of OFDMA-based cellular networks. In particular, the paper introduces new parameterized classifications and makes use of these classifications to categorize and review various static (frequency reuse-based) and dynamic (cell coordination-based) ICIC schemes.
@cite_28: 
@cite_41: Non-orthogonal multiple access (NOMA) enables power-domain multiplexing via successive interference cancellation (SIC) and has been viewed as a promising technology for 5G communication. The full benefit of NOMA depends on resource allocation, including power allocation and channel assignment, for all users, which, however, leads to mixed integer programs. In the literature, the optimal power allocation has only been found in some special cases, while the joint optimization of power allocation and channel assignment generally requires exhaustive search. In this paper, we investigate resource allocation in downlink NOMA systems. As the main contribution, we analytically characterize the optimal power allocation with given channel assignment over multiple channels under different performance criteria. Specifically, we consider the maximin fairness, weighted sum rate maximization, sum rate maximization with quality of service (QoS) constraints, and energy efficiency maximization with weights or QoS constraints in NOMA systems. We also take explicitly into account the order constraints on the powers of the users on each channel, which are often ignored in the existing works, and show that they have a significant impact on SIC in NOMA systems. Then, we provide the optimal power allocation for the considered criteria in closed or semi-closed form. We also propose a low-complexity efficient method to jointly optimize channel assignment and power allocation in NOMA systems by incorporating the matching algorithm with the optimal power allocation. Simulation results show that the joint resource optimization using our optimal power allocation yields better performance than the existing schemes.
@cite_9: A promising multi-user access scheme, non-orthogonal multiple access (NOMA) with successive interference cancellation (SIC), is currently under consideration for 5G systems. NOMA allows more than one user to simultaneously access the same frequency-time resource and separates multi-user signals by SIC. These render resource optimization in NOMA different from orthogonal multiple access. We provide theoretical insights and algorithmic solutions to jointly optimize power and channel allocation in NOMA. We mathematically formulate NOMA resource allocation problems, and characterize and analyze the problems’ tractability under a range of constraints and utility functions. For tractable cases, we provide polynomial-time solutions for global optimality. For intractable cases, we prove the NP-hardness and propose an algorithmic framework combining Lagrangian duality and dynamic programming to deliver near-optimal solutions. To gauge the performance of the solutions, we also provide optimality bounds on the global optimum. Numerical results demonstrate that the proposed algorithmic solution can significantly improve the system performance in both throughput and fairness over orthogonal multiple access as well as over a previous NOMA resource allocation scheme.
@cite_39: Non-orthogonal multiple access (NOMA) is a candidate technology for the 5th generation cellular networks to reduce the big gap between network capacity and fast growing traffic. It applies superposition coding in transmitters and successive interference cancellation at the receivers to cancel intra-cell interference. The same frequency resource can be allocated simultaneously to multiple intra-cell users, holding large potentials on improving network performance. A major technical challenge of NOMA is on user pairing and power allocation (UPPA). Most of existing UPPA algorithms are based on exhaustive search with extensive computation. A new algorithm, which has the lowest computation complexity achievable for NOMA UPPA is proposed. The main idea is to pair the first users having the highest proportional fairness priority coefficient with potential second users having the highest channel conditions. A fixed power allocation strategy is adopted. The proposed algorithm is significantly faster than existing algorithms without sacrificing NOMA throughput gain.
@cite_0: In this paper, we study the resource allocation and user scheduling problem for a downlink non-orthogonal multiple access network where the base station allocates spectrum and power resources to a set of users. We aim to jointly optimize the sub-channel assignment and power allocation to maximize the weighted total sum-rate while taking into account user fairness. We formulate the sub-channel allocation problem as equivalent to a many-to-many two-sided user-subchannel matching game in which the set of users and sub-channels are considered as two sets of players pursuing their own interests. We then propose a matching algorithm, which converges to a two-side exchange stable matching after a limited number of iterations. A joint solution is thus provided to solve the sub-channel assignment and power allocation problems iteratively. Simulation results show that the proposed algorithm greatly outperforms the orthogonal multiple access scheme and a previous non-orthogonal multiple access scheme.
@cite_19: In the past decade, cognitive radio and cooperative communication techniques have been proposed in the literature for efficiently utilizing the radio resources. Cognitive radio is an emerging technology intended to enhance the utilization of the radio frequency spectrum. The cooperative communication system, with the same total power and bandwidth of legacy wireless communication systems, can increase the data rate of the future wireless communication system. A combination of cognitive radio with cooperative communication can further improve the future wireless network performance. Efficient resource allocation in cooperative cognitive radio network (CRN) is essential in order to meet the challenges of future wireless networks. In this article, a survey of resource allocation in cooperative CRN is presented. We discuss the taxonomy of objectives and protocols used in the literature for resource allocation in cooperative CRN. This paper also highlights the use of power control, cooperation types, network configurations and decision types used in cooperative CRN. Finally, directions for future research are outlined.
@cite_40: Multiuser orthogonal frequency division multiplexing (OFDM) with adaptive multiuser subcarrier allocation and adaptive modulation is considered. Assuming knowledge of the instantaneous channel gains for all users, we propose a multiuser OFDM subcarrier, bit, and power allocation algorithm to minimize the total transmit power. This is done by assigning each user a set of subcarriers and by determining the number of bits and the transmit power level for each subcarrier. We obtain the performance of our proposed algorithm in a multiuser frequency selective fading environment for various time delay spread values and various numbers of users. The results show that our proposed algorithm outperforms multiuser OFDM systems with static time-division multiple access (TDMA) or frequency-division multiple access (FDMA) techniques which employ fixed and predetermined time-slot or subcarrier allocation schemes. We have also quantified the improvement in terms of the overall required transmit power, the bit-error rate (BER), or the area of coverage for a given outage probability.
@cite_16: This article surveys different resource allocation algorithms developed for the downlink of multiuser OFDM wireless communication systems. Dynamic resource allocation algorithms are categorized into two major classes: margin adaptive (MA) and rate adaptive (RA). The objective of the first class is to minimize the total transmit power with the constraint on users' data rates whereas in the second class, the objective is to maximize the total throughput with the constraints on the total transmit power as well as users' data rates. The overall performance of the algorithms are evaluated in terms of spectral efficiency and fairness. Considering the trade-off between these two features of the system, some algorithms attempt to reach the highest possible spectral efficiency while maintaining acceptable fairness in the system. Furthermore, a large number of RA algorithms considers rate proportionality among the users and hence, are categorized as RA with constrained-fairness. Following the problem formulation in each category, the discussed algorithms are described along with their simplifying assumptions that attempt to keep the performance close to optimum but significantly reduce the complexity of the problem. It is noted that no matter which optimization method is used, in both classes, the overall performance is improved with the increase in the number of users, due to multiuser diversity. Some on-going research areas are briefly discussed throughout the article.
@cite_13: Multicasting is emerging as an enabling technology for multimedia transmissions over wireless networks to support several groups of users with flexible quality of service (QoS) requirements. Although multicast has huge potential to push the limits of next generation communication systems; it is however one of the most challenging issues currently being addressed. In this survey, we explain multicast group formation and various forms of group rate determination approaches. We also provide a systematic review of recent channel-aware multicast scheduling and resource allocation (MSRA) techniques proposed for downlink multicast services in OFDMA based systems. We study these enabling algorithms, evaluate their core characteristics, limitations and classify them using multidimensional matrix. We cohesively review the algorithms in terms of their throughput maximization, fairness considerations, performance complexities, multi-antenna support, optimality and simplifying assumptions. We discuss existing standards employing multicasting and further highlight some potential research opportunities in multicast systems.
There exists a large body of works that addressed the resource allocation problems for OFDMA @cite_16 @cite_22 @cite_19 @cite_13 and NOMA @cite_9 @cite_0 @cite_28 @cite_41 @cite_39 techniques in 5G. In OFDMA setup, the proposed resource allocation problems are consisting of subcarrier and power allocation. Meanwhile, in NOMA, one needs to optimize user pairing along with power and sub-carrier allocation @cite_0 . For both NOMA and OFDMA, network optimization is often posed using non-deterministic polynomial-time (NP)-hard problems @cite_9 @cite_40 .