Optimal Power Allocation Method Research Articles

Optimal Power Allocation for OTFS With Frequency-Domain Linear Equalizers

Orthogonal time frequency space (OTFS) is a promising candidate for high-mobility communications that has the potential to overcome the challenges brought by severe Doppler effects. In this letter, we investigate the optimal power allocation (OPA) for OTFS transmissions employing frequency-domain linear equalizers, including frequency-domain zero-forcing (FD-ZF) and/or minimum mean squared error (FD-MMSE) equalizers. More specifically, for FD-ZF, we derive a closed-form expression for the received signal-to-noise ratio (SNR). Leveraging this, we develop the OPA method under using FD-ZF by applying the Lagrange multipliers to solve the optimization problem of maximizing the received SNR. Similarly, for FD-MMSE, we give a closed-form expression of its signal-to-signal-plus-interference-plus-noise ratio (SSINR), and obtain the OPA to maximize the SSINR. Our analytical results show that, more transmit power will be allocated to the poorer subchannels in time frequency (TF) domain of OTFS, which is contrary to the water-filling (WF) method for orthogonal frequency division multiplexing (OFDM).

Optimal power allocation for a wireless cooperative network with UAV.

The main objective of this work was to investigate the optimal power allocation strategy in the UAV cooperative wireless Decode and Forward (DF) relay network. Firstly, the outage probability of the system with and without diversity gain was derived. Two optimization problems were studied for different application scenarios. One of the optimization problems sought to determine an optimal power allocation strategy in certain total power constraint to minimize the system outage probability. Since the optimization problem we established is convex, the Lagrange multiplier method was adopted. For the system without diversity, the explicit expression of the optimal power allocation was derived. The relationship between UAV transmission power and source node transmit power was obtained for the diversity gain system and then the Newton iterative method was used to obtain the optimal power allocation method. The simulation results show that the optimal power allocation strategy can reduce the outage probability of the system under the same conditions, and the reliability of the system was improved. Another optimization problem aimed to use the lowest power to ensure that the outage probability within a certain specific threshold for saving energy resources. Because the optimization problem is non-convex, we proposed an effective method to solve the optimal power allocation strategy. Similarly, we derived the closed-form solution of the power allocation strategy for the system without diversity. Finally, the simulation results verify the correctness of the proposed algorithm.

Size Optimization and Power Allocation Optimization of a Hybrid Energy Storage System for Grid Enhanced Frequency Response Service

Aiming at the scenario where the energy storage system participates in the grid enhanced frequency response auxiliary service, this paper first establishes a frequency response model to provide power requirements for the ESS. A two-layer optimization approach is proposed to solve the size optimization problem. On the bottom layer, a mixed-integer linear programming technique is investigated to optimally allocate the power of the HESS. On the top layer, a size optimization framework is proposed to optimize the configuration of the ESS. The size optimization results show that comparing with the BESS, the capacity of the HESS was reduced by 64%, the battery aging cost was reduced by 52.5%, and the total cost was reduced by 35.1%. Based on the feature of the optimal power allocation result, a novel adaptive online power allocation method is proposed. Simulation results show that the adaptive power allocation method can fully utilize the advantages of batteries and supercapacitors. Finally, the case of a HESS participating in long-term enhanced frequency response is studied. Based on the optimal configuration and adaptive power allocation method, each energy storage unit works within the set power and capacity range, and the fluctuation of the battery power is significantly reduced.

Spectrum-Energy Efficiency Tradeoff in Decode-and-Forward Two-Way Multi-Relay Networks

Owing to its high spectrum efficiency (SE), two-way relaying has aroused tremendous research interests. In this paper, the spectrum-energy efficiency (SE-EE) trade-off in decode-and-forward (DF) two-way multi-relay networks is studied by considering non-ideal power amplifiers and non-negligible circuit. Firstly, we consider the scenario of several relay nodes. To achieve better performance, the relay node with the highest energy efficiency (EE) is selected as the optimal one. Secondly, we design the optimal power allocation method to allocate each node with the optimal transmission power to enhance EE and SE. Finally, we evaluate the performance of our method and additionally analyze how the change of relay nodes’ relative position influences the EE and SE. Simulation results show that: 1) the proposed method can achieve higher SE than optimal relay equal power allocation, random relay equal power allocation, and optimal power allocation only; 2) the proposed method can achieve higher EE than optimal relay equal power allocation, random relay equal power allocation, and optimal power allocation only; and 3) EE and SE increase at first and then decrease when relay nodes move from the middle of the source node and destination node to both ends.

Spectral–energy efficiency tradeoff in decode‐and‐forward full‐duplex relay system

In this study, the spectral efficiency (SE) and energy efficiency (EE) tradeoff in full-duplex (FD) two-hop decode-and-forward (DF) relaying system is studied by considering the influence of residual self-interference. In order to increase the SE of the traditional DF relaying system, firstly, an optimal power allocation (OPA) method is proposed, and the SE and EE analyses of the system are obtained. Secondly, by applying an unified SE–EE tradeoff metric, the multi-object joint SE and EE maximisation problem is formulated as a single-objective joint maximisation problem for SE and EE. Furthermore, the optimal total transmission power of the single-objective joint SE and EE maximisation problem is obtained according to the tradeoff factors. Theoretical analysis and numerical results show that the proposed OPA method significantly improve the system's SE and EE. At the same time, it reveals that the tradeoff between the SE and EE can be flexible by setting the tradeoff factors.

Fair Energy-Efficient Resource Allocation for Downlink NOMA Heterogeneous Networks

The increasing in energy consumptions of the current wireless networks, leads towards designing energy-efficient 5G networks. The application of non-orthogonal multiple access (NOMA) in the heterogeneous networks (HetNets) improves the spectrum utilization with the cost of efficient resource allocation. Hence, this article proposes optimal user-pairing and power allocation solutions towards achieving fair energy-efficient resource allocation in downlink femtocell NOMA-HetNets. In the proposed optimization process, the considered constraints are the user's transmission rate, transmit power budget at the base station (BS), and the interference. The energy consumption of both the transmitter and the receiver are considered to simulate the real system design. The Greedy Algorithm (GA) is used to achieve a low-complex optimal solution during the user-pairing process. Simultaneously, the max-min energy efficiency optimization approach is employed to maximize the minimum energy efficiency of the femtocell users to achieve the optimal power allocation solution. The mathematical formulation of the max-min energy efficiency is a non-convex fractional programming problem and is intractable. Thus, the fractional programming theory is adopted to transform the problem into a sequence of subtractive form, followed by the Sequential Convex Programming (SCP) approach to determine the optimal solution. Simulation results show that the proposed NOMA with optimal power allocation method using SCP and GA (NOMA-SCP-GA) achieves fair energy efficiency performance with lower complexity compared to the benchmark methods. Moreover, the minimum energy efficiency of the femtocell user is 38.22% higher than NOMA with Difference of Convex programming (NOMA-DC). The NOMA-SCP-GA method can assure 5G capability demands.

Feasibility and Optimization of 1-TTI-Based Full-Duplex Two-Way Relay System

Maximizing system capacity is one of the major concerns in inband full-duplex (IFD) two-way relay (TWR) system using analog network coding (ANC). This paper compares 1-transmission-time-interval (TTI)-based ANC (1TA) TWR, in which each node operates in IFD mode, with 2-TTI-based ANC (2TA) TWR operating in inband half-duplex mode. System capacity of the 1TA TWR is derived with adverse factor such as direct link interference (DLI). Also, this work proposes an iterative optimal power allocation (OPA) method to maximize the system capacity, which is based on golden section search under total power constraint. Numerical results elucidate that the 1TA TWR based on the OPA outperforms the 2TA TWR in all cases of relay position and DLI.

Performance Evaluation of In-Band Full-Duplex System Using One-Time-Slot Two-Way Relay

In-band full-duplex (IFD) two-way relay (TWR) system becomes one among the major concern for maximizing system capacity in wireless network, where one relay node and two source nodes using analog network coding (ANC) are deployed. This paper compares one-time-slot ANC (1TA) TWR, in which each node operates in IFD mode, with two-time-slot ANC (2TA) TWR, where each node is in in-band half-duplex mode. In addition, achievable sum rate of the 1TA-TWR is derived with adverse factors such as direct link interference as well as self-interference (SI), which is induced by IFD signaling. This paper proposes an iterative optimal power allocation (OPA) method to maximize the derived end-to-end sum rate, which is based on Lagrangian and Newton–Raphson algorithm under total power constraint. Numerical results elucidate the efficiency of the 1TA-TWR over the 2TA-TWR as the following: the 1TA-TWR based on the OPA becomes more and more viable than the 2TA-TWR based on existing OPA, as the relay node goes into the center of two source nodes, the link channel gain of mutual source nodes increases, and the SI channel gain approaches noise floor level.

Multiuser Space–Time Line Code With Optimal and Suboptimal Power Allocation Methods

In this paper, a multiuser space-time line code (STLC) system is proposed. In the proposed multiuser STLC system, a zero-forcing (ZF)-based precoder decomposes multiuser multiple-input multiple-output (MIMO) channels into multiple single-user MIMO channels, and the STLC is performed with the effective single user MIMO channel independently for each user. Here, to maximize the sum rate, an optimal power allocation method is designed based on a water-filling strategy. Also, a simple suboptimal method called fairness-aware per-user (FAPU) power allocation is devised. It is analytically and numerically verified that each user of the proposed ZF-based STLC system asymptotically achieves the maximum of single-user achievable rate as the number of transmit antennas increases. The numerical results of rigorous simulation justify that the proposed ZF-based STLC with FAPU power allocation provides near optimal performance and outperforms the existing ZF-based maximum Eigen beamforming scheme and conventional multiuser STLC schemes. Furthermore, two simple search algorithms to find the optimal number of users that maximizes sum rate are devised. Numerical results verify that the proposed algorithms can effectively find the optimal number of users by reducing the search interval.

Optimal power allocation for parallel grid-connected inverters based on lagrangian function method

Two parallel grid-connected inverters can increase system capacitance effectively. In order to exert maximum efficiency of parallel grid-connected inverters, an optimal power allocation (OPA) method is proposed. Firstly, the power model of every inverter is established. Compared with the equal power allocation (EPA) method, theoretically, higher overall system efficiency can be achieved with the OPA method. Secondly, the overall system efficiency can be calculated with easily measurable electric parameters, and the online optimization realized by adopting an existing method, such as the hill-climbing method. Lastly, the feasibility of the OPA method is verified by simulation and experimentation.

Interference and throughput aware resource allocation for multi‐class D2D in 5G networks

This study examines subcarrier and optimal power allocation in orthogonal frequency division multiple access based 5G device-to-device (D2D) networks. To improve spectrum efficiency, D2D users share same subcarriers with the legacy users using underlay approach. In this approach, it is challenging to design an efficient subcarrier and power allocation method for D2D networks which guarantees the quality of service requirements of legacy users. Therefore, the key constraint is to check the interference condition among D2D and legacy users while allocating the same resources to D2D users. In this study, the authors propose a throughput efficient subcarrier allocation (TESA) and geometric water-filling based optimal power allocation (GWFOPA) method for multi-class cellular D2D systems. First, the TESA method selects subcarriers and allocates power equally for D2D users according to their service classes while maintaining interference and data rate constraints. Then, the GWFOPA method is applied to optimise power in a computationally effective way. The objective of TESA and GWFOPA method is to maximise the data rate of each class while maintaining interference constraint and fairness among the D2D users. Finally, the authors present simulation results to evaluate performance of TESA and GWFOPA in terms of throughput, user data rate, and fairness.

Performance Analysis of Efficient Power Allocation Techniques with Different Modulation for 4X4 V-BLAST MIMO-OFDM System

Objectives: To propose an optimal power allocation method for high-speed V-BLAST MIMO-OFDM system for better performance in terms of SNR and BER than the traditional methods. Materials and Methods: To study and evaluate the performance of two linear channel estimators, the Least Square Error (LS) and Linear Minimum Mean Square Error (LMMSE) are used for 4 × 4 VBLAST Multiple input, multiple output-orthogonal frequency division multiplexing (MIMOOFDM) system with different modulation-4 QAM,16QAM and 64 QAM. For power allocation, optimal power is determined by the Greedy Power Allocation and the Cuckoo Search algorithm depending on the condition of the carriers measured from the channel estimation. Findings: Based on the detection method, Vertical Bell Labs Layered Space-Time (V-BLAST) MIMO-OFDM is found to be the high-speed system. Here, the proposed optimal power allocation method for high-speed V-BLAST MIMO-OFDM system showed a better performance in terms of Signal to Noise Ratio (SNR) and BER than the traditional methods. This thesis work has been evaluated based on different channel estimation with different modulation techniques for V-BLAST MMSE MIMO-OFDM System. The test program has been implemented in the latest technology system in Matlab R2013a. The experimental results show that our proposed method achieves better performance in terms of Bit Error Rate (BER) and SNR compared with the existing methods used for improving the performance of the MIMOOFDM. Linear MMSE proved efficient channel estimation technique over LS. MMSE -OSIC achieves very good performance with respect to other detectors in VBLAST MIMO-OFDM environment for 4× 4 MIMO-OFDM systems. Application: This result would be useful to make efficient Adaptive MIMO-OFDM system. It would be also useful in adaptive modulation and power allocation concept for making better wireless communication system. This performance analysis can perform for different channel models.

Performance of dual‐hop DF relaying systems with QAM schemes over mixed η‐μ and κ‐μ fading channels

AbstractPerformance of a dual‐hop decode‐and‐forward relaying system that uses quadrature amplitude modulation (QAM) scheme is analyzed over mixed η‐μ and κ‐μ fading channels. Closed‐form expressions are derived for the average symbol error rate (ASER) for rectangular QAM and cross QAM schemes using moment‐generating function‐based approach. The obtained ASER expressions accommodate other mixed fading channels addressed in the literature, as special cases. Further, a simple expression for the asymptotic ASER has been obtained, useful to determine the system performance at high signal‐to‐noise‐ratio values. The obtained asymptotic ASER results reveal that the diversity order is determined by the most severely faded link while the coding gain is affected by the total power of the system. Additionally, we analyze the optimal power allocation method, which provides a practical design rule to optimally distribute the total transmission power between the source and the relay to minimize the ASER. Extensive numerical and computer simulation results are presented that confirm the accuracy of presented mathematical analysis.

Optimal Design and Energy Efficient Binary Resource Allocation of Interference-Limited Cellular Relay-Aided Systems With Consideration of Queue Stability

The topic of subcarrier and power allocation in the downlink of an orthogonal frequency division multiple access decode-and-forward relaying system is presented with the objective of encompassing system stability and interference limitations in one inclusive problem. The introduced model is designed to maximize the overall throughput of the cell-edge users that are served by relay stations. We analyze the stability requirement of buffers in the base station and the corresponding relay stations, and define the rate constraints in order to guarantee queue stability without requiring a priori knowledge of arrival traffic’s statistics. The explained model results in a nonconvex optimization problem, and therefore, we employ a time-shared technique to achieve the closed form solution, which is only applicable when subcarriers can be shared by the users during one time-slot. In the case where the subcarriers are not allowed to be time-shared, we introduce a computationally efficient optimal binary subcarrier and power allocation method, in addition to a power conservative allocation mechanism. Using geometric-programming and monomial approximation techniques, we show that the proposed conservative approach, although nonconvex, can be solved in polynomial time. We also study the impact of adjustable time-slot division and interference-tolerance parameters on improving system performance. The extensive simulation results demonstrate the success of the proposed methods in terms of stabilizing the queues, improving the throughput by 30% and energy efficiency gain by 90%, in comparison with the existing similar models in the literature.

Secret key generation scheme based on MIMO received signal spaces}{Secret key generation scheme based on MIMO received signal spaces

Conventional secret key generation scheme cannot achieve high key generation rate when the channel characteristics change slowly. To solve this problem, a secret key generation model based on the MIMO received signal space is investigated in this paper. In this model, the legitimate transmitter and receiver distill secret keys from the received signal space, and improve the randomness of the received signals by controlling the variance of the transmitted signals, so that the update of the secret key is independent of the time variance of the wireless channel. Then a specific key generation scheme is proposed, in which the legitimate nodes can obtain the same received signal space, from which common vectors can be selected to distill the keys. In addition, an optimal power allocation method to maximize the key rate is presented. The results of the simulation confirm the effectiveness of this scheme.

Energy-Efficient Distributed Power Allocation With Multiple Relays and Antenna Selection

This paper proposes an iterative power allocation algorithm that maximizes the energy efficiency of a multiple-relay cooperative multiple antenna (MIMO) network. Energy efficiency is defined as the achievable spectral efficiency normalized by the total power consumption, which also accounts for the RF circuitry consumption, modeled in a wireless sensor network. Moreover, relay selection is performed using the distributed opportunistic selection protocol, while we derive closed-form expressions for outage probability and energy efficiency for a single antenna (SISO) and two MIMO scenarios: 1) based on antenna selection (AS) and 2) based on single value decomposition (SVD) beamforming. In order to evaluate the performance of the proposed algorithm, we compare it to an exhaustive search optimal power allocation method. Results show that the proposed algorithm performs very close to an exhaustive search approach and that, although MIMO SVD has the best outage performance, AS has the best energy efficiency for low and moderate source-destination distances and spectral efficiencies.

Performance for device-to-device communication with three-time-slot two-way amplify-and-forward relay protocol

Multi-hop device-to-device (D2D) communication can significantly improve the system performance. This paper studied the outage performance of D2D communication assisted by another D2D user using three-timeslot two-way amplify-and-forward relaying protocol over Rayleigh fading channels. Considering the co-channel interference from cellular user at the D2D node, the approximate expression for the overall outage probability was derived. Furthermore, a power allocation optimum method to minimize the outage probability was developed, and the closed form expression for the optimal power allocation coefficient at the relay was derived. Simulation results demonstrate accuracy of the derived outage probability expressions. Simulation results also demonstrate that the outage performance can be improved using the proposed optimal power allocation method.

A QoE-based Joint Bandwidth and Power Allocation Method for Multiple RATs in HetNets

In this letter, we propose an optimal joint bandwidth and power allocation method for heterogeneous wireless networks (HetNets) by maximizing the users’ quality of experience (QoE), which is a widely used subjective metric reflecting the users’ satisfaction of the multimedia service. By taking two factors into consideration simultaneously: Rate Factor (RF) and Energy Factor (EF), we can measure the QoE of end-users effectively. An optimal QoE-driven allocation algorithm is further developed for maximizing the end-users’ QoE utility subject to the constraints of transmit bandwidth, power and data rate. The simulation results demonstrate the theoretical analysis.

Efficient transceiver design for large-scale antenna systems

We present linear transceiver design strategies for large-scale multiple-input multiple-output downlink systems when the user nodes have multiple receive antennas, and they receive multiple streams. First, we propose a matched-filtering-based optimal power allocation method using the sum-rate maximization criterion and utilizing the favorable propagation property of large-scale antenna systems. In uncorrelated transmit antennas, we observe that the effective channel can be represented by the receive antenna correlation matrix. Motivated by this observation, we also propose a suboptimal two-step power allocation method in which each user node is equipped with two receive antennas to reduce the computational complexity of the optimum power allocation method. Compared with the optimum power allocation method, the proposed two-step method reduces the dimensions of the bisection search space while achieving essentially the same level of sum rate.

Optimal Power Allocation Scheme for Energy Efficiency Maximization in Distributed Antenna Systems

In this paper, we present a power allocation method for a distributed antenna system (DAS) to maximize energy efficiency (EE), which is defined as the ratio of the transmission rate to the total consumed power. Different from conventional EE maximization schemes that require iterative numerical methods, we derive the optimal solution as a closed form by solving Karush-Kuhn-Tucker conditions. The obtained closed-form expression is applicable to DAS with an arbitrary number of distributed antenna (DA) ports and general per-DA port power constraints and is also guaranteed to be globally optimum. Then, we provide several interesting observations on the proposed EE maximizing power allocation scheme. Based on these results, we propose a simplified practical power allocation method that employs the DA port selection and computes the power level in a distributed manner. Through Monte Carlo simulations, we show that the proposed optimal power allocation method produces the EE identical to exhaustive search with significantly reduced computational complexity. In addition, it is shown that the proposed simplified power allocation method based on the DA port selection exhibits little performance loss compared to the optimal algorithm with a remarkable reduction in the system overhead.