The substance of the digital filter design is a multi-parameter optimisation problem. This paper presents a joint objective function to design finite impulse response (FIR) digital filters and infinite impulse response (IIR) digital filters, and a cultural firework (CF) algorithm is proposed to implement filter designs. The design of the filter is transformed into the constrained optimisation problem, and the cultural firework algorithm is used to search optimal value of filter design parameters in the parameter space with parallel search. The proposed cultural firework algorithm is a multi-dimensional search algorithm for optimisation of real numbers, which uses mechanisms of cultural evolution to update the locations of cultural sparks. Computer simulations have showed that FIR and IIR digital filters based on the CF algorithm are superior to previous filters based on particle swarm optimisation (PSO), quantum-behaved particle swarm optimisation (QPSO) and adaptive quantum-behaved particle swarm optimisation (AQPSO) in the convergence speed and optimisation results. The effectiveness and superiority of the CF are also demonstrated by computer simulations.

In this paper, we propose a novel best cooperative mechanism (BCM) for wireless energy harvesting and spectrum sharing in 5G networks. Data transfer and energy harvesting are finished in the designed timeslot mode. In the proposed BCM, secondary users (SUs) harvest energy from both ambient signals and primary user's (PU's) signals. In addition, the SU's can act as relay for PUs and harvest energy from PU signals simultaneously. The proposed mechanism allows optimal time duration for data transfer within the timeslot. We formulate an optimization problem based on the proposed BCM with an objective to maximize throughput of PUs and SUs with constraints on data rate and energy harvest save ratios. The effectiveness of the proposed cooperative mechanism is verified by simulations, and it is considered as an important stepping stone for future research in this domain.

The device-to-device (D2D) communication is viewed as an attractive technique to increase the spectrum efficiency and the data transmission rate in the wireless network. In this paper, we investigate the joint resource allocation and power control problem for cooperative D2D users (DUs) which multiplex cellular users (CUs) in downlink cooperative D2D heterogeneous networks. The studied resource allocation problem contains the spectrum resource block allocation and the selection of an idle user which works as a relay to assist the D2D links communication, while the power control aims to reduce the interference between users and improve the communication quality of service (QoS). To efficiently maximize the total throughput of all the DU links and the CU links on the premise of guaranteeing the communication QoS for CUs, we propose a quantum coral reefs optimization algorithm (QCROA) to obtain the optimal joint resource allocation and power control scheme. The simulation results demonstrate that the proposed QCROA achieves an excellent performance for different network communication scenarios.

We design a co-time co-frequency full-duplex (CCFD) massive multiple-input multiple-output (MIMO) network to improve the utilization of time-frequency resources and physical layer security. Simultaneous information transmissions of the base station and the users are regarded as same-frequency interference against interception by eavesdroppers. To promote energy conservation and improve utilization of system resources, we propose a joint antenna selection and power allocation (JASPA) strategy for CCFD massive MIMO networks. Considering the trade-off between secrecy performance and system communications quality, we formulate optimization functions based on JASPA for two security concerns. We design a quantum-inspired backtracking search algorithm (QBSA) to obtain the optimal JASPA scheme. Simulation results show that the performance of the proposed QBSA is superior to previous intelligent algorithms in CCFD massive MIMO systems. The effectiveness of the proposed JASPA scheme is demonstrated under various communications scenarios, and can be considered a cornerstone for future research in wireless communications domain.

In this study, we propose a method for direction of arrival (DOA) estimation of mixed circular and noncircular coherently distributed (CD) sources under impulsive noise. The existing methods estimate the angular parameters of circular and noncircular CD sources simultaneously under Gaussian noise, but they encounter issues such as low resolution at small angular separation and performance degradation under impulsive noise. To overcome these challenges, we first construct an augmented norm covariance to mitigate the effects of impulsive noise, and then we present a high-resolution DOA estimation approach that handles circular, general noncircular, and rectilinear CD sources separately by analyzing the constraints satisfied by the generalized steering vector. We evaluate the superior performance of our proposed method through numerical simulations and compare it with the derived Cramér-Rao bound for the considered scenarios.

FIR and IIR digital filters design involve multi-parameter optimization, on which some existing intelligent algorithms don't work efficiently. This paper focuses on employing the proposed differential cultural (DC) algorithm to design FIR and IIR digital filters. DC is a global stochastic searching technique that can find out the global optima of the problem more rapidly. After describing the theory and method of DC, we present how to use it in FIR and IIR digital filters design. It has been proved by simulation experiments that DC outperforms the particle swarm optimization (PSO), quantum particle swarm optimization (QPSO) and adaptive quantum particle swarm optimization (AQPSO) for the problem of filter design.