This article presents a low-complexity and high-accuracy algorithm using message-passing approach to reduce the computational load of the traditional tracking algorithm for location estimation. In the proposed tracking scheme, a state space model for the location-estimation problem can be divided into many mutual-interaction local constraints based on the inherent message-passing features of factor graphs. During each iteration cycle, the message with reliability information is passed efficiently with an adaptive weighted technique and the error propagation law, and then the message-passing approach based on prediction-correction recursion is to simplify the implementation of the Bayesian filtering approach for location-estimation and tracking systems. As compared with a traditional tracking scheme based on Kalman filtering (KF) algorithms derived from Bayesian dynamic model, the analytic result and the numerical simulations show that the proposed forward and one-step backward tracking approach not only can achieve an accurate location very close to the traditional KF tracking scheme, but also has a lower computational complexity.

In this paper, we propose user grouping, subcarrier allocation, and bit allocation schemes in multicarrier nonorthogonal multiple access (NOMA) systems on downlink beamforming to reduce the total transmit power while considering the data-rate and the error-rate constraints of practical modulation types. Power control is also considered. In this system, each subcarrier can be assigned to multiple users for data transmission. Each subcarrier is allocated to a cluster that contains groups of two users for data transmission. A subset of subcarriers is assigned to the same cluster for sharing. The system is based on orthogonal frequency division multiple access (OFDMA), in which a primary user (PU) is more important than a secondary user, and we ensure that all assigned subcarriers transmit data to the PU in the system. In the proposed schemes, the user-grouping operation is performed first and the subcarrier allocation along with the bit loading and power assignment are performed subsequently based on the user-grouping results. The simulation results obtained using the proposed schemes in conjunction with the nonorthogonal multiple access to allocate bits, subcarriers, and transmit power show that the proposed schemes outperform the conventional OFDMA system in terms of transmit power. INDEX TERMS 5G cellular, nonorthogonal multiple access (NOMA), orthogonal frequency division multiple access (OFDMA), successive interference cancellation (SIC), resource allocation, zero-forcing beamforming.

In order to resolve the co-channel inter-cell interference problem in heterogeneous networks (HetNet), the feature of almost blank subframes (ABS) in the time domain of the enhanced inter-cell interference coordination (eICIC) is utilized. In this paper, an ABS configuration design is developed on downlink in HetNet and the associated resource allocation problem for maximizing the system performance with fairness among user equipments (UEs) is considered. Compared to conventional problems, the resource assignment problems include the configuration of ABS pattern and the resource allocation for macro UEs and pico UEs, which aims to maximize the downlink throughput and balance the traffic offloading in intra-frequency HetNet deployments. First, this paper introduces an ABS pattern design by using the channel condition, which is developed in terms of the time domain resource. Subframes are categorized as protected or normal subframes for reducing interference impact to pico UEs. Based on the configuration of the ABS pattern, we develop a grouping strategy to determine which pico UEs use either protected or normal subframes. Besides, the assignment of resource blocks with respect to the resource in the frequency domain is developed along with the fairness among UEs. The proposed joint allocation scheme takes the system throughput and the fairness into account, and has better performance than the existing schemes. Simulation results also reveal that the performance of the proposed joint allocation scheme approximates the optimal solution with the full search scheme.

This study presents an efficient location tracking algorithm to reduce the computational complexity of the conventional Kalman filtering algorithm. In the proposed location estimation and tracking approach, using the inherent message-passing nature of factor graphs, the data information is passed efficiently between the variable nodes and the factor nodes by taking weights based on the message reliability, thus simplifying implementation of the Bayesian filtering approach for location tracking. Numerical simulations and experimental results show that the proposed location tracking scheme not only can achieve the location accuracy close to that of the Kalman filtering scheme, but also has lower computational complexity with decoupling approach.