In this paper, we investigate the spectrum resource and power allocation problem for the tradeoff between maximizing the sum rate and minimum rate requirements of users in non-orthogonal multiple access (NOMA) system. First, we formulate the NOMA techniques, basic principles, and double-objective optimization (DOO) problem. Then, the non-convexity of the DOO problem is converted into a single-objective optimization (SOO) problem by power discretization method. Global optimal search (GOS) algorithm is applied to solve the user-subchannel matching and power allocation problem. Due to its high complexity and unfairness among users, it is only suitable for determining the upper bound of users throughput performance. Finally, yet importantly, a spectrum resource and power allocation algorithm with adaptive proportional fair (APF) user pairing is proposed to convert the original optimization problem into user pairing, sub-channel, and power allocation. The users paired on the sub-channel are determined by the scheduling priority which is based on the equivalent channel gain. The BS dynamically adjusts the forgetting factor in the APF algorithm based on the variance of all the users' scheduling priorities so as to influence the update of users' scheduling weights. The power allocation stage proposes three power allocation schemes to ensure the users' minimum data rate requirements under the condition that effectively guarantees the correct execution of successive interference cancellation (SIC). The simulation results demonstrate that it can not only approach the throughput performance compared with the global optimal search and the classical water-filling (WF) power allocation using matching theory but also can improve the fairness of the users.INDEX TERMS Non-orthogonal multiple access (NOMA), spectrum resource and power allocation, global optimal search (GOS), adaptive proportional fair (APF) user pairing, fairness.

This paper focus on the two-tier downlink heterogeneous networks (HetNets) with nonorthogonal multiple access (NOMA). The aim is to jointly optimize user scheduling and power allocation to solve the problem of maximizing the energy efficiency (EE) of the NOMA HetNets. We formulate the basic principle of NOMA and develop the EE model of joint user scheduling, optimal power allocation factor among users on the same subchannel and power allocation across subchannels. Firstly, considering that the problem of formulation is a multi-objective optimization (MOO) problem, which is non-convex and NP-hard, we decouple the MOO problem into two single-objective optimization (SOO) problems: 1) joint the optimal power allocation factor of maximizing the EE among users on the same subchannel to solves the subchannel matching, and 2) the power allocation across subchannels. For subchannel matching, non-cooperative game and global optimal search (GOS) are respectively used to solve the power allocation factor among users on the same subchannel and user scheduling. For the power allocation factor among users on the same subchannel, the existence of Nash equilibrium (NE) is proved by introducing super-modular game. Besides, the Nash equilibrium point (NEP) of the game can be obtained by using the proposed algorithm. Then, for the correlation between users-subchannels, this paper proposes a non-cooperative game based user-subchannel global optimal search matching algorithm (NCG-US-GOSMA) with low-complexity. Finally, according to the obtained subchannel matching, the non-convex problem of power allocation across subchannels is converted into convex problem by successive convex approximation (SCA), and then solve it by iteration. Simulation results verify the effectiveness of the proposed scheme; in addition, the EE performance is better than the existing resource allocation algorithm and OFDMA scheme. INDEX TERMS HetNets, NOMA, user scheduling, power allocation, non-cooperative game.

Non-orthogonal multiple access (NOMA) is one innovative technology that provides low latency, high system capacity, high spectrum efficiency, and massive connectivity to solve several challenges suffered by a fifth generation (5G) mobile communication system. NOMA on the uplink with superior research value was widely mentioned at Mobile World Congress and has been released in the latest technical report by the Third Generation Partnership Project (3GPP). However, how to decode all users' signals on the uplink NOMA precisely and in parallel and achieve the separation of the superimposed users' signals is the major challenge. Therefore, an improved uplink NOMA scheme through adaptively weighted factors aided parallel interference cancellation (PIC) algorithm and multiple access (MA) signature is proposed to solve the problem. In this paper, we first briefly discuss the research status of the MA signatures used to separate superimposed users' signals. In addition, we review the existing interference cancellation algorithms used by receivers to decode message signals, which mainly include a successive interference cancellation (SIC) algorithm and the PIC algorithm. And the research value of the PIC algorithm on uplink NOMA is highlighted. Then, we briefly formulate the effect of the bias in decision statistics and adaptive weighted factors aided PIC algorithm is proposed to reduce the biased estimation. Finally, yet important, we comprehensively evaluate the performance of the proposed improving PIC algorithm in terms of bit error rate (BER), computational complexity, sum data rate, and delay estimation errors.

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