Abstract The co‐channel interference and frequent handoff are two important issues that have a great impact on the spectrum and energy efficiency in the non‐orthogonal multiple access (NOMA) with successive interference cancellation (SIC) in the small cell networks (SCN). This paper investigates the performance of SIC decoding order based on the users’ channel state information (CSI) and random SIC decoding order under the perfect and imperfect conditions for the handoff optimization in SCNs with NOMA. The effect of SIC decoding order in the joint base station association and power control problem is studied by considering the motion of mobile users (MUs). Two optimization problems are formulated using the number of associated MUs, the number of handoffs, and the transmit power of all MUs, under the maximum allowable transmit power and minimum average‐rate constraints. Two objectives are combined into a single‐stage optimization problem through the weighted sum method. The formulated problem is solved using a game theory‐based algorithm and primal decomposition theory. The simulation results show that changing the SIC decoding order can lead to performance improvement in the uplink NOMA‐ based SCNs. Also, it is shown that the proposed algorithm can significantly reduce the frequent handoffs in small cell networks.

Nonorthogonal multiple access (NOMA) has been recently proposed as an enabling technique for future cellular networks. The main purpose of NOMA is assigning every resource block (RB), such as a time slot, subcarrier, or spreading code to multiple users. Increasing the number of supported users for each RB makes NOMA an efficient technique for sixth-generation (6G) and Internet of Things (IoT) networks. It also can lead to a higher total network rate, spectrum efficiency (SE), and fairness compared to orthogonal multiple access (OMA) networks. In this article, optimizing fairness and power by satisfying the new user priority approach in NOMA networks is investigated. The user priority approach guarantees the independent Quality of Service (QoS) and makes the problem more practical for applications such as IoT. In this article, theoretical and simulation results support the optimum solutions under both ideal and nonideal scenarios.

Spectrum auctions are one of the best‐known solutions to improve the efficiency of spectrum use. However, there can be many challenges in the design of a practical spectrum auction. Heterogeneity is one of the most major challenges. Unfortunately, most of the existing auction designs either do not take into account the various aspects of heterogeneity or assume only the scenario where each seller supplies one distinct channel and each buyer wishes to buy merely one channel. The authors propose a spectrum auction mechanism which considers the various aspects of heterogeneity as well as multi‐channel purchasing. They prove that the auction design preserves three important economic aspects including truthfulness, budget balance and individual‐rationality. Moreover, most of the existing works only provide the bidders a simple demand format. Their auction mechanism enables bidders to use diverse demand formats. Furthermore, they propose some novel adaptive grouping algorithms to improve the auction's performance. The simulation results demonstrate good performance of the proposed algorithms on various auction metrics.

Artificial neural networks are extremely used for detection of spread-spectrum signals in multiple-access environments. In this paper we suggest the use of generalized regression neural networks (GRNN) on multiuser detectors in DS/CDMA systems. The network is trained by applying the estimated joint probability density function. After training, the network can obtain the required timing without knowing the signature waveforms and the received signal amplitudes. The simulation results demonstrate that the proposed receiver has higher performance in comparison to detectors which have more knowledge of system parameters.

In cognitive radio (CR) networks, the secondary users (SUs) try to communicate opportunistically in the frequency band originally allocated to a primary network. This communication should be in a manner that the quality of service (QoS) is satisfied for both primary and secondary networks. In this paper, the considered system consists of a primary broadcasting network with one transmitter and M receivers, and a relay-assisted secondary network with one transmitter and one receiver. In this scheme, if the direct link between the cognitive transmitter and receiver is not maintained the target signal to interference plus noise ratio (SINR), the relaying process, begins where N relays assist the transmitter to transmit its data to the receiver. This relaying process continues until the target SINR is met at the cognitive receiver. This scheme employs joint power allocation and beamforming (BF) at the relay nodes and defines two optimization problems in a way that the objective in the first problem is minimization of the total transmission power of the relays. If there is not any feasible solution for the first problem, the second problem is proposed with the objective of maximizing the receive rate at the destination node. Genetic algorithm (GA) is applied to both defined problems to find optimum transmission power values and beamforming weight in the relay nodes. Simulation results show that applying beamforming scheme results in a considerable reduction in the total transmission power of the relay nodes, while satisfying the QoS in both primary and secondary networks.

In this article, we study the power control (PC) process in wireless cellular code division-multiple access systems under flat fading and propose a novel approach to find an optimum step size for closed-loop power control algorithms. In this approach, an optimum step size will be computed from a proposed function. This function depends on system parameters such as, the number of co-channel users, processing gain, the period of PC, Doppler frequency, channel attenuation and the order of diversity. Based on this computation, the mobile station (MS) adjusts its transmit power optimally to decrease interference for other co-channel users. Simulation results for different sets of system parameters show that the proposed algorithm decreases the bit error rate, the outage probability at the base station (BS), and increases the battery life of the MS compared with other values of the step size. The performance of the proposed algorithm is compared with the fixed-step-size power control algorithm and superiority of its performance is confirmed by simulation results. Moreover, the upper and lower bounds of the outage probability and the received signal-to-interference ratio for the proposed algorithm at the BS will be calculated.

In this paper, we propose smart step closed-loop power control (SSPC) algorithm in a direct sequence-code division multiple access (DS-CDMA) receiver in the presence of frequency-selective Rayleigh fading. This receiver consists of three stages. In the first stage, with conjugate gradient (CG) adaptive beamforming algorithm, the desired users' signal in an arbitrary path is passed and the inter-path interference is canceled in other paths in each RAKE finger. Also in this stage, the multiple access interference (MAI) from other users is reduced. Thus, the matched filter (MF) can be used for the MAI reduction in each RAKE finger in the second stage. Also in the third stage, the output signals from the matched filters are combined according to the conventional maximal ratio combining (MRC) principle and then are fed into the decision circuit of the desired user. The simulation results indicate that the convergence speed of the SSPC algorithm is faster than other algorithms. Also, we observe that significant saving in total transmit power (TTP) are possible with our proposed algorithm.

We will present an algorithm for a high resolution spectral estimation based on central solution of Nevanlinna-Pick interpolation. The approach is very well suited to short data records and shows superior performance, compared to traditional approaches, especially in detecting and resolving spectral lines buried in colored non-Gaussian noise.