On Optimal Power Allocation for Downlink Non-Orthogonal Multiple Access Systems (1707.06350v1)

Abstract: 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, 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 theexisting 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.

• The paper provides analytical solutions for optimal power allocation, ensuring maximin fairness and efficient resource utilization in multi-channel NOMA systems.
• It introduces SIC-Stability and a joint optimization framework with dynamic matching to significantly reduce computational complexity.
• Simulation results show that the proposed strategy outperforms traditional methods in fairness, energy efficiency, and scalability for 5G applications.

Optimal Power Allocation for Downlink Non-Orthogonal Multiple Access Systems

The paper addresses the problem of optimal resource allocation within downlink Non-Orthogonal Multiple Access (NOMA) systems, an essential component of modern 5G networks. The focus is specifically on determining optimal power allocation across different users and channels, a complex issue due to its representation as a mixed integer programming problem. Although previous studies have explored optimal allocation in limited scenarios, such as single channels or small user groups, this paper extends these works by delivering a comprehensive solution applicable to multiple channels and user configurations, grounded in a variety of performance criteria.

Key Contributions

The authors of this paper have managed to formulate solutions for resource optimization under realistic performance conditions, including maximin fairness, weighted sum rate maximization, and energy efficiency, while incorporating Quality of Service (QoS) constraints. Here are notable contributions:

1. Analytical Solutions: The paper provides closed or semi-closed forms for the optimal power allocation criteria—something unprecedented for the NOMA system under diverse performance measures in multiple channels. For instance, under maximin fairness, the system achieves absolute fairness, with the optimal resource allocation ensuring equal rates for users on the same channel.
2. SIC-Stability: An interesting addition to their framework is the introduction of SIC-Stability, referring to the strict ordering required in power allocation to ensure stability and effectiveness of successive interference cancellation (SIC). The system is evaluated for stability conditions across different metrics.
3. Joint Optimization Framework: Beyond solving the power allocation challenge, the paper also proposes an efficient algorithm that integrates a dynamic matching algorithm to assign channels, iterating between channel preference matchings and the derived optimal power allocations. This method significantly lowers computational complexity compared to exhaustive search strategies.

Numerical Insights

The simulation results are depicted comprehensively, where the proposed joint resource allocation (JRA) strategy is benchmarked against existing methods like DC programming and conventional user pairing (CUP). Numerical outcomes highlight the JRA's superior performance across criteria:

• Fairness & Efficiency: JRA consistently achieves higher minimum user rates and better energy efficiency. It outperforms certain traditional algorithms by effectively utilizing the optimal power allocation procedures.
• Scalability: The solution's scalability is evidenced by a seamless adjustment to increasing network sizes without significant performance drops, unlike the comparative methods.

Implications and Future Prospects

This paper paves the way for enhancements in deploying flexible and efficient NOMA systems in practical 5G applications. The methodology potentially generalizes to forthcoming mobile technology generations beyond 5G, where system complexity and user density are expected to surge. The solution offers a promising path for leveraging advanced NOMA features efficiently, which could foster more sophisticated wireless systems integrating with emerging technologies, such as massive MIMO and millimeter-wave communication.

As developments in wireless communication continue, further investigation might explore adapting and expanding the optimization framework to other access scenarios, like uplink NOMA, and different network architectures, ensuring consistent power optimization across broader heterogeneous networks and varied user equipment profiles in future cellular deployments.