Power Allocation Policy Research Articles

Energy-Efficient RSSI-Based Localization for Wireless Sensor Networks

Sensor positioning is a fundamental block in many location-dependent applications of wireless sensor networks. Although the main objective in localization is primarily enhancing the positioning accuracy, the importance of energy consumption and localization accuracy poses new challenges. The localization is usually assisted with some self-known position sensors called anchor nodes. In this letter, optimal power allocation for the anchor nodes in a sense of minimizing the energy consumption considering estimation errors is investigated. To have a better estimation of the relative distance between the anchor and unknown nodes using received signal strength indicator (RSSI), average energy of the received beacon is introduced as a new decision metric. Based on this, a squared position error bound as an accuracy parameter is derived, and an optimization problem is proposed to maximize the localization performance. More specifically, the optimal power allocation policy is first derived for the case that the anchor nodes estimate their own locations with no error. Since there are unavoidable errors in the positions of the anchor nodes, the optimization problem is then modified by including uncertainty in the positions of the anchor nodes. The results show that a substantial reduction in power consumption can be achieved by optimal allocation of the transmission power.

Performance analysis of an opportunistic multi‐user cognitive network with multiple primary users

AbstractConsider a multi‐user underlay cognitive network where multiple cognitive users concurrently share the spectrum with a primary network with multiple users. The channel between the secondary network is assumed to have independent but not identical Nakagami‐m fading. The interference channel between the secondary users (SUs) and the primary users is assumed to have Rayleigh fading. A power allocation based on the instantaneous channel state information is derived when a peak interference power constraint is imposed on the secondary network in addition to the limited peak transmit power of each SU. The uplink scenario is considered where a single SU is selected for transmission. This opportunistic selection depends on the transmission channel power gain and the interference channel power gain as well as the power allocation policy adopted at the users. Exact closed form expressions for the moment‐generating function, outage performance, symbol error rate performance, and the ergodic capacity are derived. Numerical results corroborate the derived analytical results. The performance is also studied in the asymptotic regimes, and the generalized diversity gain of this scheduling scheme is derived. It is shown that when the interference channel is deeply faded and the peak transmit power constraint is relaxed, the scheduling scheme achieves full diversity and that increasing the number of primary users does not impact the diversity order. Copyright © 2014 John Wiley & Sons, Ltd.

Energy efficiency enhancement of two-way amplifier forward relaying with channel estimation error

In order to save energy consumption of two-way amplifier forward (AF) relaying with channel estimation error, an energy efficiency enhancement scheme is proposed in this work. Firstly, through the analysis of two-way AF relaying mode with channel estimation error, the resultant instantaneous SNRs at end nodes is obtained. Then, by using a high SNR approximation, outage possibility is acquired and its simple closed-form expression is represented. Specially, for using the energy resource more efficiently, a low-complexity power allocation and transmission mode selection policy is proposed to enhance the energy efficiency of two-way AF relay system. Finally, relay priority region is identified in which cooperative diversity energy gain can be achieved. The computer simulations are presented to verify our analytical results, indicating that the proposed policy outperforms direct transmission by an energy gain of 3 dB at the relative channel estimation error less than 0.001. The results also show that the two-way AF relaying transmission loses the two-way AF relaying transmission loses its superiority to direct transmission in terms of energy efficiency when channel estimation error reaches 0.03.

New algorithm for joint subchannel and power allocation in multi‐cell OFDMA‐based cognitive radio networks

In this study, the authors propose an efficient resource allocation algorithm in downlink of an orthogonal frequency division multiple access (OFDMA)-based multi-cell underlay cognitive radio network. A more realistic model in which multiple secondary users and primary users coexist in a multi-cell environment has been considered. The main challenge of this model is inter-cell as well as intra-cell interference. The proposed algorithm tackles the challenges by adaptively subchannel and power allocation in cognitive radio network. Firstly, based on initial power allocation and with taking throughput of secondary users and signal-to-interference plus noise ratio constraint of the primary users into account, subchannel allocation is done by Hungarian method. Then, an iterative water-filling is implemented to enhance the initialised power allocation. Simulation results demonstrate the strength of the authors proposed scheme compared with some other suboptimal algorithms. The proposed scheme provides significant improvement over the traditional fixed subchannel allocation scheme in terms of spectral efficiency. In addition, it has been shown that the proposed water-filling policy loads more power into secondary user's band compared with an equal power allocation policy in order to achieve higher throughput.

Amplify‐and‐forward‐based cooperative jamming strategy with power allocation for secure communication

SummaryThis paper deals with the use of jamming transmission for secure amplify‐and‐forward‐based relay networks with total power constraints. An approach that the source and the relay use some of their available power to transmit jamming signals in order to create interference at the eavesdropper is investigated. Assume that the relay and destination have an a priori knowledge of the jamming signals. A power allocation policy that defines how the available power is distributed between the message signal and that of the jamming signal is presented. The results show that the proposed approach can increase the secrecy level and that a positive secrecy rate can be achieved even when the eavesdropper may be near the source. Copyright © 2014 John Wiley & Sons, Ltd.

Effective Capacity of Statistical Delay QoS Guarantees with Imperfect Channel Information in Spectrum-Sharing Networks

This paper considers a spectrum-sharing cognitive network in which a secondary user shares spectrum with an existing primary user as long as the interference caused by the secondary user to the primary user is below permissible levels. We investigate the delay quality-of-service (QoS) guaranteed capacity gains with imperfect channel state information (CSI) between the secondary transmitter and the primary receiver in Rayleigh fading environments. In particular, we quantify the relation between the secondary link effective capacity and the interference inflicted on the primary user. The impacts of channel estimation error on the performance of the secondary link are studied. We further evaluate and compare the capacity gains using proposed power allocation policies and truncated channel inversion with fixed rate (TIFR) transmission policies under different constraint conditions. Our results indicate channel estimation errors, especially in the smaller value range, lead to considerably degradation of capacity gains for the looser delay QoS requirements. Numerical simulations are conducted to corroborate our theoretical analysis. 

Distributed orthogonal space–time block coding in wireless relay networks

In this study, the authors consider distributed orthogonal space–time block coding for relay-based channel state information-assisted amplify-and-forward networks. Specifically, they show that opportunistic relaying (OR) is an optimal solution in terms of instantaneous signal-to-noise ratio (SNR), that is, it provides the maximum instantaneous SNR under the constraint of fixed transmit power for the relays. In particular, instead of allocating the given transmit power to all relays, letting the best relay transmit with this power is an optimal solution for maximising the received SNR. To exhibit this benefit, Monte Carlo simulations are presented showing superior performance of the OR scheme compared to equal power allocation policy for the considered relay networks. For the considered optimal scenario, the authors further derive analytical expressions for the outage probability and symbol error rate (SER) over quasi-static independent, not necessarily identically distributed Nakagami-m fading channels. They further present asymptotically tight approximations for the outage probability and SER in the high SNR regime, rendering insights into the cooperative diversity behaviour. Finally, numerical results are provided to examine the effect of network parameters on the system performance of the considered network.

Optimal Power Allocation in an "Off" Spectrum Sensing Interval for Cognitive Radio

Most of the current works about cognitive radio favor a constant power allocation policy during an off spectrum sensing interval, which is the time between two spectrum sensing activities when the outcome of the first spectrum sensing indicates off. However, according to our work, this policy becomes suboptimal with respect to bit error rate minimization, when the traffics of primary user follow an alternating renewal process. Therefore, under this scenario, we suggest the optimal power allocation policy, by solving a convex optimization problem on power allocation of secondary user. Our results provide meaningful insight into the design of transmitting schemes for cognitive radio.

Energy-Efficient Cognitive Radio Sensor Networks: Parametric and Convex Transformations

Designing energy-efficient cognitive radio sensor networks is important to intelligently use battery energy and to maximize the sensor network life. In this paper, the problem of determining the power allocation that maximizes the energy-efficiency of cognitive radio-based wireless sensor networks is formed as a constrained optimization problem, where the objective function is the ratio of network throughput and the network power. The proposed constrained optimization problem belongs to a class of nonlinear fractional programming problems. Charnes-Cooper Transformation is used to transform the nonlinear fractional problem into an equivalent concave optimization problem. The structure of the power allocation policy for the transformed concave problem is found to be of a water-filling type. The problem is also transformed into a parametric form for which a ε-optimal iterative solution exists. The convergence of the iterative algorithms is proven, and numerical solutions are presented. The iterative solutions are compared with the optimal solution obtained from the transformed concave problem, and the effects of different system parameters (interference threshold level, the number of primary users and secondary sensor nodes) on the performance of the proposed algorithms are investigated.

Energy-Efficient Relaying over Multiple Slots with Causal CSI

In many communication scenarios, such as in cellular systems, the energy cost is substantial and should be conserved, yet there is a growing need to support many real-time applications that require timely data delivery. To model such a scenario, in this paper we consider the problem of minimizing the expected sum energy of delivering a message of a given size from a source to a destination subject to a deadline constraint. A relay is present and can assist after it has decoded the message. Causal channel state information (CSI), in the form of present and past SNRs of all links, is available for determining the optimal power allocation for the source and relay. We obtain the optimal power allocation policy by dynamic programming and explore its structure. We also obtain conditions for which the minimum expected sum energy is bounded given a general channel distribution. In particular, we show that for Rayleigh and Rician fading channels, relaying is necessary for the minimum expected sum energy to be bounded. This illustrates the fundamental advantage of relaying from the perspective of energy efficient communications when only causal CSI is available. Numerical results are obtained which show the reduction in the expected sum energy under different communication scenarios.

Cognitive Proactive and Reactive DF Relaying Schemes under Joint Outage and Peak Transmit Power Constraints

In this letter, outage performance of cognitive cooperative radio networks using two decode-and-forward (DF) schemes is investigated. Subject to the joint outage constraint of the primary user and the peak transmit power constraint of the secondary user, adaptive power allocation policies for the secondary transmitter and secondary relays are studied. Based on these strategies, expressions for the outage probability of proactive and reactive DF schemes are obtained. Interestingly, our results show that an increase in the transmit power of the primary transmitter (PU-Tx) does not always degrade the performance of the secondary network. In fact, the PU-Tx transmit power is a substantial parameter that the secondary users can adapt to in order to improve the system performance. The numerical results additionally show that the performance of the reactive DF scheme outperforms the proactive DF scheme if the outage threshold in the first hop of the reactive DF scheme is less than that of the proactive scheme.

Optimal Power Allocation for Energy Harvesting and Power Grid Coexisting Wireless Communication Systems

This paper considers the power allocation of a single-link wireless communication with joint energy harvesting and grid power supply. We formulate the problem as minimizing the grid power consumption with random energy and data arrival in fading channel, and analyze the structure of the optimal power allocation policy in some special cases. For the case that all the packets are arrived before transmission, it is a dual problem of throughput maximization, and the optimal solution is found by the two-stage water filling (WF) policy, which allocates the harvested energy in the first stage, and then allocates the power grid energy in the second stage. For the random data arrival case, we first assume grid energy or harvested energy supply only, and then combine the results to obtain the optimal structure of the coexisting system. Specifically, the reverse multi-stage WF policy is proposed to achieve the optimal power allocation when the battery capacity is infinite. Finally, some heuristic online schemes are proposed, of which the performance is evaluated by numerical simulations.

Optimal transmission policy for cooperative transmission with energy harvesting and battery operated sensor nodes

In this paper, we consider a scenario where one energy harvesting and one battery operated sensor cooperatively transmit a common message to a distant base station. The goal is to find the jointly optimal transmission (power allocation) policy which maximizes the total throughput for a given deadline. Initially, we address the case in which the storage capacity of the energy harvesting sensor is infinite. In this context, we identify the necessary conditions for such optimal transmission policy. On their basis, we first show that the problem is convex. Then we go one step beyond and prove that (i) the optimal power allocation for the energy harvesting sensor can be computed independently; and (ii) it unequivocally determines (and allows to compute) that of the battery operated one. Finally, we generalize the analysis for the case of finite storage capacity. Performance is assessed by means of computer simulations. Particular attention is paid to the impact of finite storage capacity and long-term battery degradation on the achievable throughput.

Outage probability analysis for superposition coded symmetric relaying

Superposition coded symmetric relaying is a bandwidth-efficient cooperative scheme where each source node simultaneously transmits both its own “local” packet and “relay” packet that originated at its partner by adding the modulated local and relay signals in Euclidean space. This paper investigates the power allocation and outage probability of a superposition coded symmetric relaying system with finite-constellation signaling. We first derive the mutual information (MI) metrics for the system. The derived MI metrics consist of two parts: one represents the MI conveyed by the modulated signal corresponding to its own data, and the other represents the MI conveyed by the modulated signal corresponding to its partner’s data. Using MI based effective signal-to-noise ratio mapping technique, we attain expressions for the outage probability. Furthermore, we discuss power allocation policies that minimize the outage probability. Simulation results are presented to verify the correctness of the outage probability analysis and the benefits of the power allocation.

Equilibria of channel selection games in parallel multiple access channels

In this article, the parallel multiple access channel is studied under the assumption that transmitters maximize their individual spectral efficiency by selfishly tuning their power allocation policy. Two particular scenarios are studied: (a) transmitters are allowed to use all the available channels; and (b) transmitters are constrained to use a single channel. Both scenarios are modeled by one-shot games and the corresponding sets of Nash equilibria (NE) are fully characterized under the assumption that the receiver treads the multiple access interference as noise. In both cases, the set of NE is non-empty. In the case in which transmitters use a single channel, an upper bound of the cardinality of the NE set is provided in terms of the number of transmitters and number of channels. In particular, it is shown that in fully loaded networks, the sum spectral efficiency at the NE in scenario (a) is at most equal to the sum spectral efficiency at the NE in scenario (b). A formal proof of this observation, known in general as a Braess paradox, is provided in the case of two transmitters and two channels. In general scenarios, we conjecture that the same effect holds as long as the network is kept fully loaded, as shown by numerical examples. Moreover, the price of anarchy and the price of stability in both games are also studied. Interestingly, under certain conditions on the channel gains, Pareto optimality can be achieved at some NE if and only if the number of channels equals or exceeds the number of transmitters. Finally, simulations are presented to verify the theoretical results.

Diversity Fairness in Tomlinson–Harashima Precoded Multiuser MIMO Through Retransmission

We study the diversity unfairness associated with the conventional Tomlinson–Harashima precoding (THP) in multiuser multiple-input multiple-output downlink transmission. A single-retransmission scheme that combines two THP signals at each user with a complementary multi-user suppression order is investigated. For a system with <formula formulatype="inline" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex Notation="TeX">$M$</tex></formula> antennas at the transmitter and a single antenna at each user, the proposed scheme provides a diversity order <formula formulatype="inline" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex Notation="TeX">$M+1$</tex></formula> for all users and ensures diversity fairness. We study two retransmission policies, where the users either consider only the current received codeword or combine both codewords for decoding. An asymptotic analysis of the outage probability for both THP retransmission schemes is provided. In addition, a power allocation policy that minimizes the outage probability and accommodates the same coding gain at each user is discussed by formulating a geometric optimization problem.

Power Control for Two User Cooperative OFDMA Channels

For a two user cooperative orthogonal frequency division multiple access (OFDMA) system with full channel state information (CSI), we obtain the optimal power allocation (PA) policies which maximize the rate region achievable by a channel adaptive implementation of inter-subchannel block Markov superposition encoding (BMSE), used in conjunction with backwards decoding. We provide the optimality conditions that need to be satisfied by the powers associated with the users' codewords and derive the closed form expressions for the optimal powers. We propose two algorithms that can be used to optimize the powers to achieve any desired rate pair on the rate region boundary: a projected subgradient algorithm, and an iterative waterfilling-like algorithm based on Karush-Kuhn-Tucker (KKT) conditions for optimality, which operates one user at a time and converges much faster. We observe that, utilization of power control to take advantage of the diversity offered by the cooperative OFDMA system, not only leads to a remarkable improvement in achievable rates, but also may help determine how the subchannels have to be instantaneously allocated to various tasks in cooperation. Simulations show that the gain from power allocation is still significant even when the CSI feedback is limited.

Power Allocation for Statistical QoS Provisioning in Opportunistic Multi-Relay DF Cognitive Networks

In this letter, we propose a power allocation scheme for statistical quality-of-service (QoS) provisioning in multi-relay decode-and-forward (DF) cognitive networks (CN). By considering the direct link between the source and destination, the CN first chooses the transmission mode (direct transmission or relay transmission) based on the channel state information. Then, according to the determined transmission mode, efficient power allocation will be performed under the given QoS requirement, the average transmit and interference power constraints as well as the peak interference constraint. Our proposed power allocation scheme indicates that, in order to achieve the maximum throughput, at most two relays can be involved for the transmission. Simulation results show that our proposed scheme outperforms the max-min criterion and equal power allocation policy.

Managing Femto to Macro Interference without X2 Interface Support through POMDP

We present a self-organized downlink power control for interference management when Home eNodeBs (HeNBs) work in co-channel operation with the macrocell system. The main novelty with regards to previous works is that we provide a completely autonomous framework, considering 3GPP release 11 hypothesis of non availability of X2 interface between evolved NodeBs (eNBs) and HeNBs. In this situation, the HeNB has to make autonomous decisions without receiving any feedback from the macro network. We model the HeNBs as a multiagent system where each node is an independent agent able to learn through Reinforcement Learning (RL) techniques a downlink power allocation policy for different interference situations. To deal with the lack of information in the scenario, we rely on the theory of Partially Observable Markov Decision Process (POMDP). POMDP works on the basis of a set of beliefs that the HeNB builds considering the impact it causes to the macrocell system. To gather this system performance information, we propose that HeNBs use spatial interpolation techniques, such as ordinary Kriging. Results show that the proposed approach allows HeNBs to autonomously learn a power allocation policy to coexist with the macro network, in a 3GPP compliant fashion, and without introducing overhead signaling in the system.

Impact of Detection Uncertainties on the Performance of a Spectrum-Sharing Cognitive Radio With Soft Sensing

We investigate the impact of detection uncertainties in the sensing information on the power-allocation policy that achieves the maximum capacity offered by a cognitive radio (CR) in a spectrum-sharing system. It is assumed that the transmit power of the secondary user can be adjusted based on soft-sensing information pertaining to the activity of the primary user in the secondary transmission region. In particular, considering an imperfect soft-sensing mechanism at the secondary system, we obtain the optimal power transmission policy in terms of false alarm and detection probabilities and under constraints on the average interference power at the primary receiver. Furthermore, we present a quantized sensing mechanism that considers only restricted levels of the sensing observations. Finally, we illustrate our analysis through numerical results and comparisons and explore the impact of imperfect spectrum sensing information on the performance of CR systems.