Source Power Allocation Research Articles

Optimal Cooperative Power Allocation for Energy-Harvesting-Enabled Relay Networks

In this paper, we present a new power allocation scheme for a decode-and-forward (DF) relaying-enhanced cooperative wireless system. While both source and relay nodes may have limited traditional brown power supply or fixed green energy storage, the hybrid source node can also draw power from the surrounding radio frequency (RF) signals. In particular, we assume a deterministic RF energy harvesting (EH) model under which the signals transmitted by the relay serve as the renewable energy source for the source node. The amount of harvested energy is known for a given transmission power of the forwarding signal and channel condition between the source and relay nodes. To maximize the overall throughput while meeting the constraints imposed by the non-sustainable energy sources and the renewable energy source, an optimization problem is formulated and solved. Based on different harvesting efficiency and channel condition, closed form solutions are derived to obtain the optimal source and relay power allocation jointly. It is shown that instead of demanding high on-grid power supply or high green energy availability, the system can achieve compatible or higher throughput by utilizing the harvested energy.

Optimal Resource Allocation for Buffer-Aided Relaying With Statistical QoS Constraint

We consider a three-node buffer-aided relaying network with statistical quality-of-service (QoS) constraint in terms of maximum acceptable end-to-end queue-length bound outage probability. In particular, we study the adaptive link selection relaying problem that aims to maximize the constant supportable arrival rate $\mu$ to the source (i.e., the effective capacity). Fixed and adaptive source and relay power allocation are investigated. By employing asymptotic delay analysis, we first convert the QoS constraint into minimum QoS exponent constraints at the source and relay queues. We then derive the link selection and power allocation solutions as functions of the instantaneous link conditions and QoS exponents using Lagrangian approach. Solutions for various special cases of link conditions and QoS constraints are presented. Moreover, we compare the effective capacities of the proposed relaying schemes and other existing schemes under different link conditions and QoS constraints. Illustrative results indicate that the proposed schemes offer substantial performance gains, and power adaption outperforms fixed power allocation at low signal-to-noise power ratio (SNR) region or under loose QoS constraints.

Power Allocation for Buffer-Aided Full-Duplex Relaying With Imperfect Self-Interference Cancelation and Statistical Delay Constraint

This paper considers source and relay power allocation for buffer-aided full-duplex (B-FD) relaying network, assuming constant data rate arrivals at the source buffer. Statistical delay constraint is imposed, where the end-to-end queue length is allowed to exceed a pre-defined queue-length threshold with a maximum acceptable queue-length-outage probability. We assume imperfect self-interference (SI) cancelation, where the non-zero residual SI power is modeled to be proportional to the relay transmit power. We investigate two power allocation problems for source arrival rate maximization: 1) B-FD relaying with adaptive power allocation (B-FD-APA) when the instantaneous channel state information at the transmitters (CSIT) is available and 2) B-FD relaying with static power allocation (B-FD-SPA) when only the statistical CSIT is available. To solve the problems, we first employ asymptotic delay analysis to transform the statistical delay constraint into more tractable constraints. Then, the optimal solutions are derived using Lagrangian approach. In addition, solutions for various special cases of residual SI and delay constraint are presented. With B-FD-APA, the relay can opportunistically switch between half-duplex (HD) and FD operation modes according to the channel conditions. With B-FD-SPA, the relay always employs FD mode. Numerical results are performed to compare the capacities of the proposed B-FD, non-buffer FD, and buffer-aided HD relaying schemes, as well as direct transmission (DT) under various settings, demonstrating the effectiveness of B-FD relaying to support delay-constrained communications.

Achieving High Energy Efficiency and Physical-Layer Security in AF Relaying

For transmitting data in a secret and energy-efficient manner in collaborative amplify-and-forward relay networks, the secure energy efficiency (EE) defined as the secret bits transferred with unit energy is maximized to satisfy each node power constraint and target secrecy rate requirement, based on physical security framework. The secure EE is maximized by joint source and relay power allocation, which is a nonconvex optimization problem. To cope with this difficulty, a solution scheme and corresponding algorithms are developed by jointly applying fractional programming, exact penalty, alternate search, and difference of convex functions programming. The key idea of the scheme is to convert the primal problem into simple subproblems step by step, such that related methods are adopted. It is verified that, compared with secrecy rate maximization, the proposed scheme improves the secure EE significantly yet with a certain loss of the secrecy rate due to the tradeoff between secure EE and secrecy rate. Furthermore, the proposed scheme achieves higher secure EE and secrecy rate than total transmission power minimization does, while with a certain increase of power consumption. These results indicate that a reasonable balance among secure EE, secrecy rate, and power consumption can be reached by the proposed scheme.

Smart Home Energy Management Including Renewable Sources: A QoE-driven Approach

Smart home energy management (SHEM) systems can introduce adjustments in the working period and operations of home appliances to allow for energy cost savings, which can however affect the quality of experience (QoE) perceived by the user. This paper analyses this issue and proposes a QoE-aware SHEM system, which relies on the knowledge of the annoyance suffered by users when the operations of appliances are changed with respect to the ideal user’s preferences. Accordingly, a number of profiles describing different usages are created in the design phase. At the deployment stage, users behavior and annoyance are registered to assign one of these profiles per appliance. The assigned profile is then exploited by the QoE-aware cost saving appliance scheduling and the QoE-aware renewable source power allocation algorithms. The former is aimed at scheduling controlled loads based on users profile preferences and electricity prices. The latter re-allocates appliances’ operations whenever a surplus of energy is available by renewable energy sources. Experimental results demonstrate that the annoyance perceived by users is severely diminished with respect to a QoE-unaware strategy, at the expenses of only a limited reduction in energy saving.

Centralized and Game Theoretical Solutions of Joint Source and Relay Power Allocation for AF Relay Based Network

Relaying is an emerging technique for 3G/4G high bandwidth networks in order to improve the capacity of edge nodes. As the deployment cost is high, there might be a few number of relay nodes in the cell which can help the edge nodes to transmit their data. From this perspective, one of the key problems in a relay equipped node is to make decision which edge nodes to be helped and how much power need to be disseminated among them in order to maximize the system capacity. This problem is formulated as an optimization problem given individual node and total available power constraints. The objective function of the formulated problem is non-convex, and we solve this using geometric programming (GP)-based method. Since the solution of this problem is computationally expensive, we propose a low complexity suboptimal solution. Having noticed the selfless nature of the sources in the centralized solution, we also provide a game theoretical solution. Two separate Stackelberg games are required to solve this power allocation problem. Moreover, given the total power constraint, a centralized entity is necessary to connect these two games. For assigning power among the sources, the centralized entity plays the buyer level game, whereas the sources act as power sellers. On the other hand, to disseminate relay power among the sources, roles of the players are just interchanged. Besides, before staring the game, the centralized entity determines, of total power, how much is for the transmit operation of the sources and how much is for their relay operation. We show that there is a unique Stackelberg Equilibrium (SE) for both games under certain convergence condition. Finally, the proposed game theoretical solution can achieve comparable performance in terms of resource allocation with the centralized optimal one.

Sum-Rate Maximization for Active Channels With Unequal Subchannel Noise Powers

In this paper, an active channel, between a source and a destination, refers to a parallel channel where the source transmits power over different subchannels as well as the powers of the subchannels can be adjusted. We herein study the sum-rate maximization for an active channel subject to two constraints, one on the source total transmit power and one on the total channel power. Although this maximization is not convex, we use Karush-Kuhn-Tucker (KKT) conditions to develop a computationally efficient algorithm for optimal source and channel power allocation. To do so, we first show how KKT conditions can be used to determine the number of subchannels that can be active in order for the source power constraint to be feasible. Indeed, we show that not all subchannels but only a subset of them may receive transmit power from the source. Then, for any feasible number of active subchannels, we obtain the optimal source power allocation. In fact, we prove that for any feasible number of active subchannels, there is only one or two solutions for the optimal source power allocation. As such, the optimal solution can be obtained by comparing a finite number of points in the feasible set and by introducing the point, which yields the best sum-rate performance, as the optimal solution. Our analysis and simulation results show that active channels can offer a significantly higher sum-rate compared to their passive counterparts, which rely on water-filling scheme for source power allocation across subchannels.

Joint Source-Relay Precoding and Power Allocation for Secure Amplify-and-Forward MIMO Relay Networks

In this paper, we investigate the security issue of a two-hop amplify-and-forward multiple-input multiple-output wireless relay network in the existence of a multiantenna eavesdropper. The optimal scheme to achieve the secrecy capacity involves a nonconvex optimization and is still an open problem. Aiming to find an efficient way to enhance the secrecy rate with a tractable complexity, we propose a suboptimal joint source and relay linear precoding and power allocation scheme. In the scheme, the source node adopts a generalized singular value decomposition (SVD)-based precoding to transmit the signal in the first phase, and the relay node forwards the received signal based on the SVD precoding in the null-space of the wiretap channel in the second phase. Power allocations in both phases are optimized to maximize the secrecy rate by an alternating iterative optimization algorithm. Each iteration involves two subproblems. One has a water-filling solution and the other has a closed-form solution or a water-filling-like solution as well, both of which are computationally very efficient. The iteration converges fast and we prove that it guarantees to find a stationary optimum. Furthermore, we show that when the eavesdropper has equal or more antennas than the source does, the secrecy rate is a quasi-concave function of the source power so that allocating all the source power is generally not optimal. Numerical evaluation results are provided to show the effectiveness of the iterative algorithm and the proposed secrecy scheme.

Sequential Optimization for Subcarrier Pairing and Power Allocation in CP-SC Cognitive Relay Systems

A sequential optimization algorithm (SOA) for resource allocation in a cyclic-prefixed single-carrier cognitive relay system is proposed in this study. Both subcarrier pairing (SP) and power allocation are performed subject to a primary user interference constraint to minimize the mean squared error of frequency-domain equalization at the secondary destination receiver. Under uniform power allocation at the secondary source and optimal power allocation at the secondary relay, the ordered SP is proven to be asymptotically optimal in maximizing the matched filter bound on the signal-to-interference-plus-noise ratio. SOA implements the ordered SP before power allocation optimization by decoupling the ordered SP from the power allocation. Simulation results show that SOA can optimize resource allocation efficiently by significantly reducing complexity.

A Dual-Phase Power Allocation Scheme for Multicarrier Relay System With Direct Link

We present optimization algorithms for source and relay power allocations in a multicarrier relay system with direct link, where the source power is allowed to transmit in both phases in a two-phase relay scheme. We show that there is a significant benefit to the system capacity by allowing the source power to be distributed over both phases. Specifically, we consider the joint optimization of source and relay power to minimize a general cost function. The joint optimization problem is non-convex and the complexity of finding the optimal solution is extremely high. Using the alternating optimization (AO) method, the joint problem is decomposed into a convex source power allocation problem and a non-convex relay power allocation problem. By exploiting the specific structure of the problem, we present efficient algorithms that yield the exact optimal solutions for both source and (non-convex) relay power allocation problems. Then we show that the overall AO algorithm converges to a stationary point of the joint problem. Moreover, the proposed AO algorithm is asymptotically optimal for large relay transmit power or large source-relay channel gain. Finally, simulations show that the proposed AO algorithm achieves significant gain over various baselines.

Joint Source Power Allocation and Distributed Relay Beamforming Design in Cognitive Two-Way Relay Networks

Joint Source Power Allocation and Distributed Relay Beamforming Design in Cognitive Two-Way Relay Networks

Filter-and-Forward Transparent Relay Design for OFDM Systems

In this paper, the filter-and-forward (FF) relay design for orthogonal frequency-division multiplexing (OFDM) transmission systems is considered for improving system performance over simple amplify-and-forward (AF) relaying. Unlike conventional OFDM relays performing OFDM demodulation and remodulation, to reduce processing complexity, the proposed FF relay directly filters the incoming signal in the time domain with a finite impulse response (FIR) and forwards the filtered signal to the destination. Three design criteria are considered for optimizing the relay filter. The first criterion is the minimization of the relay transmit power subject to per-subcarrier signal-to-noise ratio (SNR) constraints, the second criterion is the maximization of the worst subcarrier channel SNR subject to source and relay transmit power constraints, and the third criterion is the maximization of the data rate subject to source and relay transmit power constraints. It is shown that the first problem reduces to a semi-definite programming (SDP) problem by semi-definite relaxation (SDR), and the solution to the relaxed SDP problem has rank one under a mild condition. For the latter two problems, the problem of joint source power allocation and relay filter design is considered, and an efficient algorithm is proposed for each problem based on alternating optimization and the projected gradient method (PGM). Numerical results show that the proposed FF relay significantly outperforms simple AF relays with an insignificant increase in complexity. Thus, the proposed FF relay provides a practical alternative to the AF relaying scheme for OFDM transmission.

Source Power Allocation and Relaying Design for Two-Hop Interference Networks with Relay Conferencing

In this paper, we consider a two-hop interference network, which consists of two source-destination pairs and two relay nodes connected with signal-to-noise ratio (SNR) limited out-of-band conferencing links. Assuming that the amplify-and-forward (AF) relaying scheme is adopted, this network is shown to be equivalent to a two-user interference channel (IC). By deploying two IC decoding schemes, i.e., single-user decoding and joint decoding, respectively, we characterize the achievable rate regions with a two-stage iterative optimization method: First, we fix the source power pair and maximize the sum rate over the relay combining vector; second, we fix the relay combining vector and optimize the source power pair. Specifically, for single-user decoding, we design a new routine to compute the optimal solution for the first subproblem, which is more efficient than the existing scheme; and for the second subproblem, we develop an iterative algorithm, with the closed-form solution for each iteration. Furthermore, it is revealed that the AF scheme with relay conferencing achieves the full degree-of-freedom (DoF), which outperforms the case without relay conferencing. Finally, simulation results show that relay conferencing can significantly improve the system performance under certain channel conditions.

Joint Optimization of Source Power Allocation and Cooperative Beamforming for SC-FDMA Multi-User Multi-Relay Networks

This paper is concerned with design problems of joint source power allocation and relay beamforming in multi-user multi-relay networks that use single-carrier frequency division multiple access (SC-FDMA) and amplify-and-forward relaying. Examined are the joint programs of (i) maximizing the minimum signal-to-interference-plus-noise ratio (SINR) under various transmitted power constraints, and (ii) minimizing the total transmitted power subject to prescribed SINR thresholds of users. Although these optimization problems are highly nonconvex and have large dimensions, by exploiting their partial convexities and making elegant nonlinear variable changes, they are recast as d.c. (difference of two convex) programs. Efficient d.c. iterative procedures are then developed to find the solutions. Simplified joint programs under the two cases of equal source power and equal relay beamforming weights, respectively, are also considered. Branch-and-bound algorithms of deterministic global optimization are then proposed for solving the simplified joint programs. Simulation results confirm the excellent performance and computational efficiency of all the proposed solutions.

Joint Optimization of Source Power Allocation and Distributed Relay Beamforming in Multiuser Peer-to-Peer Relay Networks

In this paper, we consider the joint optimization of the source power allocation and relay beamforming weights in distributed multiuser peer-to-peer (MUP2P) relay networks applying the amplify-and-forward (AF) protocol. We adopt a quality-of-service (QoS) based approach, in which the total power transmitted from all sources and relays is minimized while guaranteeing the prescribed QoS requirement of each source-destination pair. The QoS is modeled as a function of the receive signal-to-interference-plus-noise ratio (SINR) at the destinations. Unlike the existing contributions, the transmitted powers of the sources and the beamforming weights of the relays are optimized jointly in this paper. Introducing an appropriate transformation of variables, the QoS based source power allocation and distributed relay beamforming (PADB) problem can be equivalently transformed into a difference of convex (DC) program, which can be efficiently solved with local optimality using the constrained concave convex procedure (CCCP). Based on this procedure, we also propose an iterative feasibility search algorithm (IFSA) to find an initial feasible point of the DC program. The analytic study of the proposed solution confirms that it converges to a local optimum of the PADB problem. Numerical results show that our solution outperforms (in terms of the total transmitted power) the alternating optimization procedure and the exact penalty based DC algorithm. In addition, the proposed IFSA outperforms the alternating optimization algorithm in finding feasible points of the DC program (i.e., the equivalence of the PADB problem).

Throughput Maximization for the Gaussian Relay Channel with Energy Harvesting Constraints

This paper considers the use of energy harvesters, instead of conventional time-invariant energy sources, in wireless cooperative communication. For the purpose of exposition, we study the classic three-node Gaussian relay channel with decode-and-forward (DF) relaying, in which the source and relay nodes transmit with power drawn from energy-harvesting (EH) sources. Assuming a deterministic EH model under which the energy arrival time and the harvested amount are known prior to transmission, the throughput maximization problem over a finite horizon of N transmission blocks is investigated. In particular, two types of data traffic with different delay constraints are considered: delay-constrained (DC) traffic (for which only one-block decoding delay is allowed at the destination) and no-delay-constrained (NDC) traffic (for which arbitrary decoding delay up to N blocks is allowed). For the DC case, we show that the joint source and relay power allocation over time is necessary to achieve the maximum throughput, and propose an efficient algorithm to compute the optimal power profiles. For the NDC case, although the throughput maximization problem is non-convex, we prove the optimality of a separation principle for the source and relay power allocation problems, based upon which a two-stage power allocation algorithm is developed to obtain the optimal source and relay power profiles separately. Furthermore, we compare the DC and NDC cases, and obtain the sufficient and necessary conditions under which the NDC case performs strictly better than the DC case. It is shown that NDC transmission is able to exploit a new form of diversity arising from the independent source and relay energy availability over time in cooperative communication, termed "energy diversity", even with time-invariant channels.

Joint source and relay power allocation in amplify-and-forward relay networks: a unified geometric programming framework

This study presents some joint source and relay power allocation algorithms in the amplify-and-forward (AF) relay networks using the efficacious geometric programming (GP). According to the constraints, approximate expressions of the received signal-to-noise ratio are first obtained. Thereafter, the problems are cast into appropriate GP forms according to the constraints. The power allocated to the source(s) and to the relays is then determined iteratively via the single condensation method. The new GP approach is shown to be applicable to a variety of constraints by using all of the relays for assistance and is amenable to asymmetric channels in both the single-user and multi-user AF relay networks. Conducted simulations show that the proposed power allocation schemes can attain superior performance compared with the previous works under various constraints in miscellaneous scenarios.

Joint Optimization of Source Power Allocation and Relay Beamforming in Multiuser Cooperative Wireless Networks

Relay beamforming techniques have been shown to significantly enhance the sum capacity of a multiuser cooperative wireless network through the optimization of the relay weights, where concurrent communications of multiple source-destination pairs are achieved via spatial multiplexing. Further optimization of the transmit power allocation over the source nodes is expected to improve the network throughput as well. In this paper, we maximize the sum capacity of a multiuser cooperative wireless network through the joint optimization of power allocation among source nodes and relay beamforming weights across the relay nodes. We consider a two-hop cooperative wireless network, consisting of single-antenna nodes, in which multiple concurrent links are relayed by a number of cooperative nodes. When a large number of relay nodes are available, the channels of different source-destination pairs can be orthogonalized, yielding enhanced sum network capacity. Such cooperative advantage is particularly significant in high signal-to-noise ratio (SNR) regime, in which the capacity follows a logarithm law with the SNR, whereas exploiting spatial multiplexing of multiple links yields capacity increment linear to the number of users. However, the capacity performance is compromised when the input SNR is low and/or when the number of relay nodes is limited. Joint optimization of source power allocation and relay beamforming is important when the input SNR and/or the number of relay nodes are moderate or the wireless channels experience different channel variances. In these cases, joint optimization of source power and distributed beamforming weights achieves significant capacity increment over both source selection and equal source power spatial multiplexing schemes. With consideration of the needs to deliver data from each source node, we further examine the optimization of global sum capacity in the presence of individual capacity requirements by maximizing sum capacity of the network subject to a minimum capacity constraint over each individual user.

Unified Exact Performance Analysis of Two-Hop Amplify-and-Forward Relaying in Nakagami Fading

We present a general two-parameter received signal-to-noise ratio (SNR) model for two-hop amplify-and-forward (AF) relaying. It encompasses AF schemes that select the relay gain as the reciprocal of a linear combination of the channel gain and the noise power of the incoming link, including all channel-noise-assisted, channel-assisted, and blind relay schemes. Moreover, the model is flexible enough to represent independent source and relay power allocations. A unified performance analysis is then developed for AF relaying over independent but nonidentically distributed Nakagami- <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">m</i> faded links, where <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">m</i> is an integer. Exact analytical expressions are derived for the cumulative-distribution function (cdf), probability density function (pdf), and moment-generating function (mgf) of the received SNR. Monte Carlo simulation results are provided to verify the results.

A Joint Source and Relay Power Allocation Scheme for a Class of MIMO Relay Systems

A joint power allocation (PA) scheme for a class of MIMO relay systems is presented in this paper. Based on the maximization of the capacity or minimization of the mean-square error (MSE), two joint PA optimization problems are first formulated. Since the cost functions thus obtained are in general not convex, a tight lower bound of the capacity and a similar upper bound of the MSE are derived, and employed to modify the two cost functions so as to obtain a convex optimization problem. It is confirmed through computer simulations that the proposed PA scheme outperforms the existing method in terms of both the capacity and the MSE of MIMO relay systems.