Proposed Power Allocation Method Research Articles

Maximizing the Downlink Data Rates in Massive Multiple Input Multiple Output with Frequency Division Duplex Transmission Mode Using Power Allocation Optimization Method with Limited Coherence Time

The expected development of the future generation of wireless communications systems such as 6G aims to achieve an ultrareliable and low-latency communications (URLLCs) while maximizing the data rates. These requirements push research into developing new advanced technologies. To this end, massive multiple input multiple output (MMIMO) is introduced as a promising transmission approach to fulfill these requirements. However, maximizing the downlink-achievable sum rate (DASR) in MMIMO with a frequency division duplex (FDD) transmission mode and limited coherence time (LCT) is very challenging. To address this challenge, this paper proposes a DASR maximization approach using a feasible power allocation optimization method. The proposed approach is based on smartly allocating the total transmit power between the data transmission and training sequence transmission for channel estimation. This can be achieved by allocating more energy to the training signal than the data transmission during the channel estimation process to improve the quality of channel estimation without compromising more training sequence length, thus maximizing the DASR. Additionally, the theory of random matrix approach is exploited to derive an asymptotic closed-form expression for the DASR with a regularized zero-forcing precoder (RZFP), which allows the power optimization process to be achieved without the need for computationally complex Monte Carlo simulations. The results provided in this paper indicate that a considerable enhancement in the DASR performance is achieved using the proposed power allocation method in comparison with the conventional uniform power allocation method.

Performance Analysis of Uplink Non-Orthogonal Multiple Access in the Presence of Co-Channel Interference

In sixth generation (6 G) networks, a massive number of users and devices must be connected, necessitating flexible resource allocation. In this context, non-orthogonal multiple access (NOMA) has been proposed as a promising technique to enable mass connectivity. This study presents a performance analysis for the impact of co-channel interference (CCI) on uplink NOMA networks. More specifically, it is considered that CCI is introduced by randomly deployed terminals within the cellular coverage area, affecting the reception of the base station (BS) in the uplink. In this network, fading conditions follow the Rayleigh distribution and two cases are examined for the CCI statistics, i.e. independent and identically distributed, and independent but not identically distributed. A thorough performance analysis is conducted to derive the outage probability, ergodic rate, error probability, achievable sum-rate, and throughput expressions, highlighting the adverse effects of CCI on the uplink NOMA network. Furthermore, an asymptotic analysis is provided, shedding light on the derived analytical results. Towards improving the performance of uplink NOMA, power allocation is formulated as an optimization problem, and solved to derive the power allocation coefficient of the users. Our analytical and asymptotic derivations are verified through Monte-Carlo-based computer simulations and it is revealed that the proposed power allocation method achieves significant performance gains, facilitating uplink NOMA.

Generalized Relays Subsets Selection Algorithm in Cloud-Based 6G Large-Scale Relays Network

In this article, in order to substantially improve outage probability (OP), we propose a generalized optimal relays subsets selection algorithm in a cloud-based 6G large-scale relays network. We derive OP based on relays subsets selection for first hop and second hop, respectively. In addition, with the aid of the proposed power allocation method, we put forward optimal relays subsets paring algorithm. The generalized model can be converted into various relays selection algorithms, such as best relay selection, <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">${N}$ </tex-math></inline-formula> th best relay selection, partial relays selection, various relays subsets selection, and so on. Simulation results show that the proposed multiple relays selection algorithm has 2–6 orders of magnitude advantage than existing selection algorithms on OP.

Power allocation method of battery energy storage system considering state balance in smoothing photovoltaic power fluctuations

Aiming at the imbalances of SOC (state of charge, SOC) and SOH (state of health, SOH) for battery energy storage system (BESS) in smoothing photovoltaic power fluctuations, a power allocation method of BESS is proposed. Firstly, the hierarchical structure of the power allocation method is given, including acquisition of the grid-connected photovoltaic power reference and double-layer power allocation strategy for BESS. Secondly, a swing door trend algorithm optimized by the improved Aquila optimizer is devised and used to deal with the raw photovoltaic power to obtain the grid-connected signal. Next, the dynamic grouping principle considering the SOC and SOH of battery units is devised, and the double-layer power allocation method of BESS is designed in terms of the dynamic grouping results of battery units. Finally, the proposed power allocation method is simulated through actual data, and the results compared with other methods show that it can smooth photovoltaic power fluctuations more effectively, and the SOC and SOH can be balanced more quickly and accurately, which verifies its effectiveness.

A Deep Q-Learning Bisection Approach for Power Allocation in Downlink NOMA Systems

In this work, we study the weighted sum-rate maximization problem for a downlink non-orthogonal multiple access (NOMA) system. With power and data-rate constraints, this problem is generally non-convex. Therefore, a novel solution based on the deep reinforcement learning (DRL) framework is proposed for the power allocation problem. While previous work based on DRL restrict the solution to a limited set of possible power levels, the proposed DRL framework is specifically designed to find a solution with a much larger granularity, emulating a continuous power allocation. Simulation results show that the proposed power allocation method outperforms two baseline algorithms. Moreover, it achieves almost 85% of the weighted sum-rate obtained by a far more complex genetic algorithm that approaches exhaustive search in terms of performance.

Power allocation and temporal fair user group scheduling for downlink NOMA

Non-Orthogonal Multiple Access (NOMA) has been proposed as a new radio access technique for cellular networks as an alternative to OMA (Orthogonal Multiple Access) in which the users of a group (pairs or triples of users in a group are considered in this paper) are allowed to use the wireless channel simultaneously. In this paper, for downlink single-input single-output SISO-NOMA, a heuristic power allocation algorithm within a group is first proposed which attempts to ensure that the users of a group benefit from simultaneous transmission equally in terms of achievable throughput. Moreover, a user group scheduling algorithm is proposed for downlink NOMA systems by which a user group is to be dynamically selected for transmission while satisfying long term temporal fairness among the individual contending users. The effectiveness of the proposed power allocation method along with the temporal fair scheduling algorithm for downlink NOMA is validated with simulations and the performance impact of the transmit power and the coverage radius of the base station as well as the number of users are thoroughly studied.

QoS-Oriented Dynamic Power Allocation in NOMA-Based Wireless Caching Networks

Non-orthogonal multiple access (NOMA) based wireless caching network (WCN) is considered as a promising technology for next-generation wireless communications since it can significantly improve the spectral efficiency. In this letter, we propose a quality of service (QoS)-oriented dynamic power allocation strategy for NOMA-WCN. In content placement phase, base station (BS) sends multiple files to helpers by allocating different powers according to the different QoS targets of files, for ensuring that all helpers can successfully decode the two most popular files. In content delivery phase, helpers serve two users at the same time by allocating the minimum power to far user according to the QoS requirement, and then all the remaining power is allocated to near user. Hence, our proposed method is able to increase the hit probability and drop the outage probability compared with conventional methods. Simulation results confirm that the proposed power allocation method can significantly improve the caching hit probability and reduce the user outage probability.

Energy efficiency optimization for amplify and forward relay networks with channel estimation errors

Due to the rapidly increasing energy consumption of the wireless communication systems, designing an energy-efficient system has become an important challenge. One can consider cooperative communication as a promising solution to reduce energy consumed by wireless networks. Hence, in this paper, we study the problem of maximizing energy efficiency by optimally allocating power in three cooperative channel scenarios. Unlike the previous works, imperfect channel state information is considered for all channels. Therefore, energy efficiency functions are derived considering channel estimation errors, and the following optimization problems are formulated to maximize the energy efficiency under the maximum transmission power and the minimum spectral efficiency constraints. Regarding the energy efficiency function behavior, an alternating optimization algorithm is used to find pilot and data transmission power at the source node. It also optimizes the power amplification gain of pilot and data at the relay node. Simulation results demonstrate that the imperfect channel state information condition can degrade the energy efficiency performance significantly. However, using the proposed power allocation method can improve the performance and compensate for the negative effect of channel estimation error. Moreover, the effect of circuit power on the optimal energy efficiency is investigated. It is shown that for a lower range of spectral efficiency, the negative effect of circuit power is greater than the channel estimation error’s negative effect, while for the higher values, the estimation error dominates the circuit power. We also observe that the results obtained from the proposed power allocation algorithms are close to the results of the global search method.

Data-Driven Simultaneous Multibeam Power Allocation: When Multiple Targets Tracking Meets Deep Reinforcement Learning

In this article, we aim to study radar power allocation problem in multiple maneuvering targets tracking from a new perspective by deep learning, to develop a data-driven approach, which enables radar to learn a good (hopefully the best) power allocation policy from data. In order to enhance the utilization effectiveness of radar power resource, we present a cognitive design based on control framework incorporating an actor-critic variation of deep reinforcement learning called deep deterministic policy gradient. Specifically, at each tracking interval, the transmit power is allocated with control framework based on prior information, which is represented by the Fisher information matrix (FIM) of prior information of target's state computed using target's dynamic models. However, as targets are maneuvering, the dynamic models are always unavailable. Thanks to the sequential manner of target tracking, we consider to integrate a memory based on recurrent neutral network into the control framework for the estimation of FIM of prior information by characterizing the output as parameters for a high-dimensional Gaussian distribution of target's state instead of a deterministic state. Theoretical analysis has established that the derived covariance matrix is essentially the inverse of the FIM of prior information. Simulation results have shown the effectiveness of the proposed power allocation method.

Energy Efficient Power Allocation Using Salp Particle Swarm Optimization Model in MIMO–NOMA Systems

Non-orthogonal multiple access (NOMA) acts as one of the promising multiple access technology for fifth generation communication systems, and has the capability of improving the performance of the system. It can be extended with multiple input multiple output (MIMO) systems with multi-users to produce considerable gains. The energy efficiency (EE) of MIMO–NOMA systems needs to be improved, for which the optimization method, termed as Salp Particle Swarm optimization for Power allocation (SPPA) model is proposed. The SPPA optimization model is obtained from the integration of Particle Swarm Optimization and Salp Swarm Algorithm and the proposed SPPA model schedules the user on the basis of EE and spectral efficiency in such a way that it offers an effective platform to provide the energy efficient power allocation. The scheduling is performed using the SPPA algorithm that prioritizes the users in an optimal way based on the objective function. The experimentation is performed using the evaluation metrics, such as Bit error ratio (BER), spectral power, achievable rate, and energy. The effectiveness of the proposed power allocation method is revealed through lower BER of 0.0004 and higher spectral power, achievable rate, and energy of 180.0013, 99.8578, and 19.6683, respectively.

Distance-Aware Power Allocation for Multi-user MIMO-NOMA Systems Based on Grouped Zero-Forcing Beamforming

Abstract Non-orthogonal multiple access (NOMA) and multiple-input multiple-output (MIMO) technologies are considered to be an integral part of 5G systems. These technologies can provide larger spectral efficiency without adding additional system bandwidth by power domain reuse. It meets the growing demand for higher connectivity and data rates for emerging wireless applications. However, in the MIMO-NOMA system, multiple user informations are non-orthogonal superposition transmission, which causes a strong inter-user interference and damages the achievable sum rate of the whole network. In this paper, we proposed power allocation methods for the multi-user MIMO-NOMA system to improve the achievable sum rate of the network. Specifically, we first divided users into strong user groups and weak user groups, then pairing two users according to channel correlation and channel gain difference. After grouping, the inter-group interference is eliminated thorough zero-forcing beam-forming (ZFBF). In order to further reduce intra-group interference and increase the sum rate of the system, we propose an intra-group power allocation method in which the allocated power is proportional to the distance from the user to the base station. This method can obtain a closed solution, so it has low complexity. It can improve the achievable sum rate. Simulations show the distance-based power allocation algorithm can further improve total capacity for MIMO-NOMA systems.

Minimization of Secrecy Outage Probability With Artificial-Noise-Aided Beamforming for MISO Wiretap Channels

The problem of optimal power allocation between the information-bearing signal and the artificial noise (AN) signal is addressed in this letter to enhance the physical layer security of the multiple-input-single-output wiretap channel. Differing from the existing works concerning the secrecy rate maximization, this letter studies the problem of minimizing the secrecy outage probability given the secrecy rate, where the channel state information concerning the eavesdropper is modeled as quasi-static Rayleigh fading and only known statistically. After formulating the problem as an optimization problem of power allocation, we prove that the optimal solution can be conveniently obtained by using the method of bi-section search. Simulation results show that the proposed power allocation method is efficient and can enhance the physical layer security by reducing the secrecy outage probability.

Power and Time Slot Allocation Method for Secured Satellite Transmission Based on Weighted Fractional Data Carrying Artificial Noise

In this paper, a power and time slot allocation method is proposed for the weighted fractional data carrying artificial noise (DCAN) to secure satellite transmission. We first introduce a data carrying artificial noise based on weighted fractional Fourier transform (WFRFT) to achieve physical layer security in satellite transmission which outperforms the traditional artificial noise method when the channel state information (CSI) is not precise at the transmitter. Then, we formulate an optimization problem to optimize the power allocation among the main signal and the weighted fractional DCANs in three steps by adopting the fractional programming, the alternative research, and difference of convex functions (DC) programming, respectively. We further divide the transmission time into different time slots and assign them to the main signals by solving a maximum weighted sum problem to ensure the transmission security with limited transmission power. Simulation results show that the proposed power and time allocation method outperforms the DCAN based on WFRFT with average power allocation when the number of the transmitted signals increases. Meanwhile, the proposed power allocation method is superior to the method based on perfect CSI or the assumption of massive transmission antennas, which may be not possible at the satellite.

A Novel Physical Layer Security Scheme in OFDM-Based Cognitive Radio Networks

In this paper, a physical-layer-security scheme for an underlay relay-based cognitive radio network (CRN) that uses orthogonal frequency-division multiplexing (OFDM) as the medium access technique is proposed. Resource allocation in relay-aided CRNs becomes a hard problem especially if it is under security threat. Different from conventional relay-based OFDM schemes, in the paper, we consider the relay network which has two dedicated relay nodes; one relay which is capable of subcarrier mapping forward the received signal to the destination and the other sends a jamming signal to add noise to the signal received by the eavesdropper. Optimization is performed under a unified framework where power allocation at the source node, power allocation, and subcarrier mapping in the relay network are optimized to maximize the secrecy rate of the CRN while satisfying the maximum transmission power constraints and the interference threshold of the PU. The power allocation problem at the forwarding relaying node is a non-convex optimization problem. Therefore, at first, the optimization problem is simplified and a closed-form solution is obtained which satisfies the maximum PU interference constraint. Afterward, the optimization problem is solved for satisfying the maximum transmission power constraint. An algorithm is also proposed for subcarrier mapping at the forwarding relaying node. The proposed power allocation method and a subcarrier mapping scheme have low complexity, compared with the baseline schemes. Finally, simulation results are provided for different parameters to show the performance improvement of the proposed scheme in terms of secrecy rate.

Comparison of daily operation strategies for a fuel cell/battery tram

This paper focuses on describing the daily operation strategy of a tram powered by a hybrid system based on fuel cell stack and a battery pack. The daily operation strategy focusses on the hydrogen refueling and battery recharging timing in one-day operation of 18 h, combined with serval driving cycles and three operation modes. The battery state of charge balanced (SOC-) strategy and the dynamic programming (DP-) strategy are two proposed power allocation methods. For one-cycle operation, the latter save 6.6% hydrogen consumption than the former. As for one-day operation, a simplified DP-strategy is deduced to replace the DP-strategy and accelerate the calculation. It shares equivalent hydrogen consumption with the SOC-strategy but guarantees the durability of the fuel cell and prolongs the driving mileage.

Energy efficient power allocation for relay-aided D2D communications in 5G networks

As one of the key technologies for the fifth generation (5G) wireless networks, device-to-device (D2D) communications allow user equipment (UE) in close proximity to communicate with each other directly. Forwarded by a relay, the relay-aided D2D (RA-D2D) communications can not only be applied to communications in much longer distance but also achieve a high quality of service (QoS). In this paper, we first propose a two-layer system model allowing RA-D2D links to underlay traditional cellular uplinks. Then we maximize the energy efficiency of the RA-D2D link while satisfying the minimum data-rate of the cellular link. The optimal transmit power at both D2D transmitter and D2D relay sides is obtained by transforming the nonlinear fractional programming into a nonlinear parameter programming. Simulation results show that our proposed power allocation method is more energy efficient than the existing works, and the proposed RA-D2D scheme outperformed direct D2D scheme when the distance between two D2D users is longer.

On HARQ-IR for Downlink NOMA Systems

Non-orthogonal multiple access (NOMA) can exploit the power difference between the users to achieve a higher spectral efficiency. Thus, the power allocation plays a crucial role in NOMA. In this paper, we study the power allocation for hybrid automatic repeat request (HARQ) in NOMA with two users. For the power allocation, we consider the error exponents of the outage probabilities in HARQ with incremental redundancy (IR) and derive them based on large deviations. While a closed-form expression for the error exponent (or rate function) without interference is available, there is no closed-form expression for the error exponent with interference. Thus, we focus on the derivation of a lower bound on the error exponent in this paper. Based on the error exponents, we formulate a power allocation problem for HARQ-IR in NOMA to guarantee a certain low outage probability for a given maximum number of retransmissions. From the simulation results, we can confirm that it is possible to guarantee a certain outage probability by the proposed power allocation method.

Transceiver Design for Multi-User Cellular Two-Way Relay Networks

In this paper, we consider a general cellular two-way relay network, where a common multi-antenna relay station (RS) helps multiple base stations (BSs) to exchange messages with their served users simultaneously. This network model includes the thoroughly studied two-way relay (TWR) networks, multi-pair TWR networks and multi-user TWR cellular networks as special cases. We first develop a transceiver design for such a network under interference free constraints. The power allocation at the RS, BSs and users is then investigated to maximize the system sum rate. The performance of the proposed algorithm is evaluated through numerical examples. The results show that the proposed design outperforms the existing ones for those special TWR networks, and the sum rate is improved significantly through the proposed power allocation method compared to equal power allocation.

Power allocation and mode selection methods for cooperative communication in the rectangular tunnel

For the multipath fading on electromagnetic waves of wireless communication in the confined areas, the rectangular tunnel cooperative communication system was established based on the multimode channel model and the channel capacity formula derivation was obtained. On the optimal criterion of the channel capacity, the power allocation methods of both amplifying and forwarding (AF) and decoding and forwarding (DF) cooperative communication systems were proposed in the limitation of the total power to maximize the channel capacity. The mode selection methods of single input single output (SISO) and single input multiple output (SIMO) models in the rectangular tunnel, through which the higher channel capacity can be obtained, were put forward as well. The theoretical analysis and simulation comparison show that, channel capacity of the wireless communication system in the rectangular tunnel can be effectively enhanced through the cooperative technology; channel capacity of the rectangular tunnel under complicated conditions is maximized through the proposed power allocation methods, and the optimal cooperative mode of the channel capacity can be chosen according to the cooperative mode selection methods given in the paper.

On Power Allocation for Incremental Redundancy Hybrid ARQ

We study the power allocation for incremental redundancy (IR) hybrid automatic repeat request (HARQ) in block fading channel where causal channel state information is known at both the transmitter and the receiver. In IR-HARQ, the traffic is assigned into consecutive transmission rounds, and at each round, the instantaneous mutual information that is required for successful decoding is upper bounded by the data rate that is to be delivered. We propose an HARQ power allocation method that maximizes the average of incremental mutual information at each round, and its throughput quickly converges to the ergodic capacity as the number of retransmissions increases. The numerical results show that the proposed power allocation method achieves almost the full channel capacity with moderate average transmission delay and that it maintains good throughput under stringent delay requirement.