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In this paper, we evaluate the performance of multiple-input multiple-output (MIMO) communication systems applied with a non-orthogonal multiple access (NOMA)-based indoor visible light communication (VLC). We present two efficient user-pairing algorithms for NOMA in VLC, aiming to enhance achievable data rates effectively. Our investigation involves the application of three low-complexity power allocation techniques. Comparative analysis reveals performance enhancements when employing the proposed schemes, especially when contrasted with NOMA without user pairing and orthogonal frequency division multiple access (OFDMA). Additionally, we explore the performance of both algorithms in scenarios with both even and odd numbers of users. Simulation results demonstrate the superiority of NOMA in comparison to OFDMA.

In recent years, the demand for maritime wireless communication has been increasing, particularly in areas such as ship operations management, marine resource utilization, and safety assurance. However, due to the difficulty of deploying base stations(BSs), maritime communication still faces challenges in terms of limited coverage and unreliable communication quality. As the number of users on ships and offshore platforms increases, along with the growing demand for mobile communication at sea, conventional terrestrial base stations struggle to provide stable connectivity. Therefore, existing maritime communication primarily relies on satellite communication and long-range Wi-Fi. However, these solutions still have limitations in terms of cost, stability, and communication efficiency. Satellite communication solutions, such as Starlink and Iridium, provide global coverage and high reliability, making them essential for deep-sea and offshore communication. However, these systems have high operational costs and limited bandwidth per user, making them impractical for cost-sensitive nearshore communication. Additionally, geostationary satellites suffer from high latency, while low Earth orbit (LEO) satellite networks require specialized and expensive terminals, increasing hardware costs and limiting compatibility with existing maritime communication systems. On the other hand, 5G-based maritime communication offers high data rates and low latency, but its infrastructure deployment is demanding, requiring offshore base stations, relay networks, and high-frequency mmWave (millimeter-wave) technology. The high costs of deployment and maintenance restrict the feasibility of 5G networks for large-scale nearshore environments. Furthermore, in dynamic maritime environments, maintaining stable backhaul connections presents a significant challenge. To address these issues, this paper proposes a low-cost nearshore wireless communication solution utilizing tethered balloons as coastal base stations. Unlike satellite communication, which relies on expensive global infrastructure, or 5G networks, which require extensive offshore base station deployment, the proposed method provides a more economical and flexible nearshore communication alternative. The tethered balloon is physically connected to the coast, ensuring stable power supply and data backhaul while providing wide-area coverage to support communication for ships and offshore platforms. Compared to short-range communication solutions, this method reduces operational costs while significantly improving communication efficiency, making it suitable for scenarios where global satellite coverage is unnecessary and 5G infrastructure is impractical. Additionally, conventional uniform power allocation or channel-gain-based amplification methods often fail to meet the communication demands of dynamic maritime environments. This paper introduces a nonlinear dynamic power allocation method based on channel gain information to maximize downlink communication efficiency. Simulation results demonstrate that, compared to conventional methods, the proposed approach significantly improves downlink communication performance, verifying its feasibility in achieving efficient and stable communication in nearshore environments.

For simultaneous wireless information and power transfer (SWIPT), secure transmission is an important issue. The power allocation problem is investigated to maximise the achievable secrecy rate in a downlink orthogonal frequency division multiple access system with a power splitting SWIPT scheme. Unlike the traditional wireless communication systems, it is assumed that the legitimate receivers have no energy storage capability. The legitimate receivers harvest the energy from the received signals by using a power splitting scheme to meet the circuit-power constraint for information decoding. The problem is formulated as a power allocation optimisation problem under the transmit power constraint and the energy harvesting constraint which is solvable. It is shown from simulations that the proposed optimal power allocation scheme outperforms the conventional uniform power allocation scheme.

Visible light communication (VLC), in recent times, has drawn the attention of researchers owing to the availability of unlicensed spectrum, high bandwidth and low power consumption. Various approaches for allocation of power are already developed for the MIMO-NOMA-based radio frequency systems namely signal alignment, post detection, and hybrid precoding. However, these traditional techniques result into high computational complexity and cannot be directly applied to a VLC system, and hence, an effective power allocation approach with less computational complexity is an essential requirement of VLC system. In this paper, an effective power allocation scheme is presented which employs channel weighted optimal coefficients utilized in GRPA and NGDPA schemes. The optimal values of the weighted coefficients are estimated using the proposed MBCO algorithm. This MBCO algorithm is outlined by integrating the MOA (magnetic optimization algorithm) with border collie optimization (BCO) method, respectively. The performance obtained by the proposed W-GRPA-based MBCO and W-NGDPA-based MBCO in terms of achievable rate is 34.916Mbit/s and 83.811Mbit/s and in terms of sum rate is 197.63Mbit/s and 200.98Mbit/s, respectively. Simulation results clearly depict that when compared with the existing state-of-the-art schemes, the proposed power allocation method outperforms the existing popular GRPA and NGDPA schemes.

Recently, due to its higher spectral efficiency and enhanced user experience, non-orthogonal multiple access (NOMA) has been widely studied in visible light communication (VLC) systems. As a main concern in NOMA-VLC systems, the power allocation scheme greatly affects the tradeoff between the total achievable data rate and user fairness. In this context, our main aim in this work was to find a more balanced power allocation scheme. To this end, an adaptive power allocation scheme based on multi-attribute decision making (MADM), which flexibly chooses between conventional power allocation or inverse power allocation (IPA) and the optimal power allocation factor, has been proposed. The concept of IPA is put forward for the first time and proves to be beneficial to achieving a higher total achievable data rate at the cost of user fairness. Moreover, considering users’ mobility along certain trajectories, we derived a fitting model of the optimal power allocation factor. The feasibility of the proposed adaptive scheme was verified through simulation and the fitting model was approximated to be the sum of three Gaussian functions.

During normal operation, the doubly-fed induction generator (DFIG) generates certain range of reactive power. The DFIG based wind farm can participate in reactive power control of grid as a reactive power supply. In order to get a more stable input wind speed of the DFIG, wavelet multi-resolution analysis method is used. This paper proposes a kind of power dispatch model which considers a learning mechanism of minimum copper loss of all DFIGs in wind farm as an objective function. An active power and reactive power allocation optimization model is established. This power dispatch model makes the working condition of DFIGs and the PCC running in the optimum state. The active power and reactive power generated by wind farm satisfy the power gird requirements of both active power and reactive power. The advantage of the proposed method is verified by a case study which successfully demonstrates the learning mechanism.

In this study, the problem of determining the power allocation that maximises the energy efficiency of cognitive radio network is investigated as a constrained fractional programming problem. The energy-efficient fractional objective is defined in terms of bits per Joule per Hertz. The proposed constrained fractional programming problem is a non-linear non-convex optimisation problem. The authors first transform the energy-efficient maximisation problem into a parametric optimisation problem and then propose an iterative power allocation algorithm that guarantees ε-optimal solution. A proof of convergence is also given for the ε-optimal algorithm. The proposed ε-optimal algorithm provide a practical solution for power allocation in energy-efficient cognitive radio networks. In simulation results, the effect of different system parameters (interference threshold level, number of primary users and number of secondary users) on the performance of the proposed algorithms are investigated.

Radio frequency (RF) energy harvesting systems are enabling new evolution towards charging low energy wireless devices, especially wireless sensor networks (WSN). This evolution is sparked by the development of low-energy micro-controller units (MCU). This article presents a practical multiple input multiple output (MIMO) RF energy-harvesting platform for WSN. The RF energy is sourced from a dedicated access point (AP). The sensor node is equipped with multiple antennas with diverse frequency responses. Moreover, the platform allows for simultaneous information and energy transfer without sacrificing system duplexity, unlike time-switching RF harvesting systems where data is transmitted only for a portion of the total transmission duty cycle, or power-splitting systems where the power difference between the information signal (IS) and energy signal (ES) is neglected. The proposed platform addresses the gap between those two. Furthermore, system simulation and two energy scheduling methods between AP and sensor node (SN) are presented, namely, Continuous power stream (CPS) and intermittent power stream (IPS).

A novel approach for ensuring confidential wireless communication is proposed and analysed from a geometrical perspective. In this method, both the legitimate receiver and transmitter generate artificial noise (AN) to impair the eavesdropper's channel. The authors use the concept of insecure region to characterise the security performance when the eavesdropper's channel is unknown. The insecure region is defined as the region where the eavesdropper may decode the secret message. With the aim of minimising the size of the insecure region, an optimum power allocation strategy between the information bearing signal and the AN is proposed. Simulation results show that the proposed method achieves a good performance.

In conventional multicast scheme (CMS), the total throughput of multicast group is constrained by the user with the worst channel quality. In order to overcome this problem of limited throughput, the authors introduce a resource allocation algorithm by exploiting layered coding combined with erasure correction coding for multicast services in the downlink of orthogonal frequency-division multiple access-based multi-antenna system. To reduce the feedback overhead of uplink, the authors design a novel transmission scheme with limited feedback. Then, the joint subcarrier and power allocation problem for the data of base layer and enhancement layers are formulated, which is shown to be non-deterministic polynomial- hard. Hence, in order to reduce the computational complexity, they propose a three-phase suboptimal algorithm. The algorithm is designed to maximise the system throughput, whereas at the same time guarantee the quality of services (QoS) requirements of all multicast groups. It is composed of precoding scheme, proportional fairness subcarrier allocation algorithm and modified water-filling power allocation algorithm with QoS guarantees (MWF-Q). To further decrease the complexity of MWF-Q, a power allocation algorithm with increased fixed power allocation algorithm with QoS guarantees is introduced. Simulation results show that the proposed algorithms based on limited feedback scheme significantly outperform CMS and any other existing algorithm with full feedback. Moreover, the proposed scheme can efficiently reduce 50% of the full feedback overhead.