Optimal Power Allocation Scheme Research Articles

OPTIMAL TRANSMIT POWER ALLOCATION FOR MAXIMIZING THE CHANNEL CAPACITY AND SINR IN MU-MIMO SYSTEM USING DIRTY PAPER CODING

Massive MIMO is the emerging technology to design 5G wireless communication systems. Perfect channel state information(CSI) is the essential condition to design the performance metrics for MU-MIMO system since the inaccuracies present in the CSI reduces data rates and channel capacity. The objective of this paper is to design a optimum power allocation scheme for MU-MIMO using dirty paper coder pre-coding. An expression is derived to determine the optimum power allocation and the ambient condition with degree of perfection factor under channel reliability at the base station to reduce the transmit power and the results obtained are presented and analysed. 2018 The Korean Institute of Communications and Information Sciences. Publishing Services by Elsevier B.V.

Random linear network coding based physical layer security for relay‐aided device‐to‐device communication

The authors investigate physical layer security design, which employs a random linear network coding with opportunistic relaying and jamming to exploit the secrecy benefit of both source and relay transmissions. The proposed scheme requires the source to transmit artificial noise along with a confidential message. Moreover, in order to further improve the dynamical behaviour of the network against an eavesdropping attack, aggregated power controlled transmissions with optimal power allocation strategy is considered. The network security is accurately characterised by the probability that the eavesdropper will manage to intercept a sufficient number of coded packets to partially or fully recover the confidential message.

Secrecy performance of non-orthogonal multiple access cognitive untrusted relaying with friendly jamming

In this paper, we consider a cooperative cognitive radio non-orthogonal multiple access network, where a secondary transmitter (ST) assists transmission of a primary source-destination (PS-PD) pair, while simultaneously communicating with a secondary receiver. Specifically, ST acts as an untrusted relay for primary network, that overhears the primary confidential messages. To improve the secrecy of the network, we consider a secure transmission with friendly jamming, in which a friendly jammer transmits a jamming signal to confound the untrusted relay and accordingly to increase the secrecy performance of the primary network. We derive closed-form expressions for the secrecy outage probability, intercept probability, and average secrecy rate. Moreover, an optimal power allocation scheme between the PS and jammer is developed to maximize the instantaneous secrecy rate of the primary network, while ensuring an specific QoS for secondary network. Our findings reveal that proposed scheme can significantly enhance the secrecy of the system, especially when the quality of PS-ST link is inferior to that of the jammer-ST link. In particular, at high signal-to-noise ratio regime, optimal power allocation achieves the average secrecy rate of 0.72 bps/Hz, which is about 2.25 times than that of equal power allocation.

Low Probability of Intercept-Based Optimal Power Allocation Scheme for an Integrated Multistatic Radar and Communication System

This paper investigates the problem of low probability of intercept-based optimal power allocation (LPI-OPA) for an integrated multistatic radar and communication system, which consists of multiple transmitters operating at different frequencies, a radar receiver, and a communication receiver (CR). The integrated multistatic radar and communication system is capable of fulfilling the requirements of both radar and communication subsystems. The key tenet of the integrated system is to minimize the total power consumption by optimizing the transmit power allocation at each transmitter for radar waveforms and information signals, which is constrained by a predetermined target detection performance for the RR and a desired information rate for the CR. Since the analytical closed-form expression of the probability of detection is not tractable, its upper bound is derived. We analytically show that the resulting optimization problem can be reformulated as two subproblems, which can be solved by an efficient solution procedure based on the approach of linear programming and the Karush–Kuhn–Tuckers optimality conditions. Simulation results are provided to show that the LPI performance of the integrated multistatic radar and communication system can significantly be enhanced by employing our proposed LPI-OPA scheme.

Power Scheduling in More Electric Aircraft Based on an Optimal Adaptive Control Strategy

In this article, an optimal control problem (OCP) for the power management system is proposed for the more electric aircraft (MEA) with consideration of the dynamics in the generators and the energy storage systems. Electrical power components included in the electrical power system (EPS) of MEA such as the generator, the bus, the rectifier, and the battery system are modeled in this OCP. Based on this formulation, a three-stage optimization architecture is introduced to obtain the optimal power references and the optimal control policies. In the first stage, an optimization problem for the power scheduling and allocation is solved as a mixed integer quadratic programming problem and the optimal power allocation schemes (power references) are obtained. In the second stage, an OCP to minimize the fluctuations in power generation systems is proposed and solved via an off-policy integral reinforcement learning approach. In the third stage, the voltage restoration is applied to maintain the main-bus voltage in the onboard high voltage dc system. Extensive case studies are carried out to illustrate the effectiveness of our proposed methodology. Simulations show that the optimal power references are obtained based on various requirements, and the optimal power control policy is achieved based on off-policy iterations.

Channel, Mode and Power Optimization for Non-Orthogonal D2D Communications: A Hybrid Approach

The increasing traffic demand in cellular networks has recently led to the investigation of new strategies to save precious resources like spectrum and energy. Direct device-to-device (D2D) communication becomes a promising solution if the two terminals are located in close proximity. In this case, the D2D communications should coexist with cellular transmissions, so they must be carefully scheduled in order to avoid harmful interference impacts. In this paper, we outline a novel framework encompassing channel allocation, mode selection and power control for D2D communications. Power allocation is done in a distributed and cognitive fashion at the beginning of each time slot, based on local information, while channel/mode selection is performed in a centralized manner only at the beginning of an epoch, a time interval including a series of subsequent time slots. This hybrid approach guarantees an effective tradeoff between overhead and adaptivity. We analyze in depth the distributed power allocation mechanism, and we state a theorem which allows to derive the optimal power allocation strategy and to compute the corresponding throughput. Extensive simulations confirm the benefits granted by our approach, when compared with state-of-the-art distributed schemes, in terms of throughput and fairness.

Power Allocation Schemes Based on Deep Learning for Distributed Antenna Systems

In recent years, a lot of power allocation algorithms have been proposed to maximize spectral efficiency (SE) and energy efficiency (EE) for the distributed antenna systems (DAS). However, the traditional iterative power allocation algorithms are difficult to be implemented in reality because of their high computational complexity. With the development of machine learning algorithms, it has been proved that the machine learning method has excellent learning ability and low computational complexity, which can approximate the traditional iterative power allocation well and be easily to be implemented in reality. In this paper, we propose a new deep neural network (DNN) model for DAS. From the perspective of machine learning, traditional iterative algorithms can be regarded as a nonlinear mapping between user channel realizations and optimal power allocation schemes. Therefore, we train the DNN to learn the nonlinear mapping between the user channel realizations and the corresponding power allocation schemes based on the traditional iterative algorithm. Then, a power allocation schemes based on DNN method is developed to maximize SE and EE for DAS. The simulation results show that the proposed scheme can not only obtain the almost similar performance as the traditional iterative algorithm, but also reduce much online computational time.

Multi Interference Analysis of Two-Way Full-Duplex Decode and Forward Relay System

Abstract A number of new technologies have been designed for cooperative communication due to the advancement in wireless communication. High throughput, data rates and high quality of service are required by current generation like 4G and future generation like 5G wireless communication. MIMO antennas have few limitations like hardware complexity, resource requirements when it uses simplex or half duplex mode of operations. To overcome its drawback like self interference, the outage performance analysis of Two way full duplex (FD) decode and forward relay system is carried out by considering residual self interference caused due to the mode called FD when compared to traditional analysis with perfect self interference cancellation. This article investigated the outage performance of a two way network with decode and forward technique in the presence of multi interferers at the source and or destination terminals. Anyway, it was not taken into account in the previous research papers due to the strong self interference (SI) which occurred from the transmitting antenna (Tx) to the local receiving antenna (Rx). The SI has been highly eliminated using various self interference cancellation (SIC) techniques. To improve the outage performance, further optimal power allocation schemes and optimal relay node placement strategies are proposed. Then, simulation results are shown for symmetrical and asymmetrical situations.

Secure transmission in large‐scale cooperative millimetre‐wave systems with passive eavesdroppers

By considering millimetre wave (mmWave) transmission as an effective solution for the fifth-generation (5G) wireless communication systems, the authors propose a new optimal power allocation (OPA) scheme to maximise the instantaneous secrecy rate of a cooperative wireless network. The communication network under study is comprised of a multiple-antennas source, a multiple-antennas destination, a single antenna untrusted relay and single antenna passive eavesdroppers (Eves). To prevent the untrusted relay and passive Eves from overhearing the source message, a new secure transmission scheme is proposed. Based on this scheme, the destination sends an artificial noise (AN) towards the untrusted relay, and concurrently, the source is forced to dedicate part of its power to transmit AN to keep the information confidential from the Eves. For such a communication network, two cases of non-colluding Eves (NCE) and colluding Eves (CE) are taken into account. Based on the proposed OPA, a novel closed-form expression is presented for the ergodic secrecy rate (ESR) performance over mmWave channels. Next, the authors derive the high signal-to-noise ratio slope and power offset of the ESR to evaluate the effects of network parameters on the ESR performance. Numerical examples depict that the proposed optimised systems for both NCE and CE present superior ESR compared to other transmission policies.

An Optimizing Method of OFDM Radar Communication and Jamming Shared Waveform Based on Improved Greedy Algorithm

Orthogonal frequency division multiplexing (OFDM) has been widely used as radar, communication, and jamming shared waveform. To improve the power utilization and efficiency of radar, communication, and jamming integrated system, we propose an adaptive OFDM shared waveform design method. Considering the problem of jamming path propagation loss and sensitivity of frequency response error of radar and communication channels, we propose a robust OFDM shared waveform design method. Firstly, the suppressed jamming entropy model, the detection probability (Pd) of the stationary point target model, the data information rate (DIR) model with a given bit error rate (BER) are formulated. With the constraints on total power and BER, the adaptive and the robust OFDM optimization problems are formulated. Then we derive the Karush-Kuhn-Tucker (KKT) conditions of the two optimization problems and an improved greedy algorithm is proposed to solve the optimization problems, and the optimal power and bit allocation schemes for the two problems are obtained. Finally, we present several numerical results to demonstrate the effectiveness of the proposed method.

Cross-Media Communications With Decode-and-Forward Relay and Optimal Power Allocation

With the rapid development of wireless communications, the signals may be transmitted in different media, such as visible light and millimeter-wave along the communication path. In this case, there will be different devices working in different media, which cannot directly communicate to each other. For alleviating this problem, we first conceive a cross-media communication scenario where two devices for different media could communicate with the aid of a relay working in both media. Furthermore, we derive the average outage probability of the uplink and downlink communications. Finally, aiming at minimizing the derived average outage probability, the optimal power allocation (PA) scheme at the relay side is also derived and verified by simulation results.

On the Secrecy Performance and Power Allocation in Relaying Networks With Untrusted Relay in the Partial Secrecy Regime

Recently, three useful secrecy metrics based on the partial secrecy regime were proposed to analyze secure transmissions on wireless systems over quasi-static fading channels, namely: generalized secrecy outage probability, average fractional equivocation, and average information leakage. These metrics were devised from the concept of fractional equivocation, which is related to the decoding error probability at the eavesdropper, so as to provide a comprehensive insight on the practical implementation of wireless systems with different levels of secrecy requirements. Considering the partial secrecy regime, in this paper we examine the secrecy performance of an amplify-and-forward relaying network with an untrusted relay node, where a destination-based jamming is employed to enable secure transmissions. In this regard, a closed-form approximation is derived for the generalized secrecy outage probability, and integral-form expressions are obtained for the average fractional equivocation and the average information leakage rate. Additionally, equal and optimal power allocation schemes are investigated and compared for the three metrics. From this analysis, we show that different power allocation approaches lead to different system design criteria. The obtained expressions are validated via Monte Carlo simulations.

Energy harvesting and information transmission scheme with UAV relay cooperation

This paper proposed a system architecture model of two-hop unmanned aerial vehicle (UAV) relay wireless communication and designed an energy harvesting and information transmission algorithm based on the energy harvested by UAV relay node. The energy of nodes except source node can be obtained by energy harvesting and all the UAV relay nodes transmitted signals via power splitting. Under the advance of non-static channel, the information user nodes were configured with multiple antennas and adopted max ratio combination (MRC). Based on the optimization criterion of energy efficiency maximization, the analytical solution of the optimal power allocation scheme for energy harvested and information transmission of multi-user two-UAV relay system was derived in detail. Since the optimization problem was a non-convex problem, this paper adopted the high signal-to-noise ratio approximation method and the power splitting method to realize the closed-form solution expression. The optimal solution of the objective function subjected with constraints can be obtained by Lagrangian algorithm and Lambert W function. Finally, the proposed algorithms and theoretical analysis are verified by simulations.

Computation Efficiency Maximization in OFDMA-Based Mobile Edge Computing Networks

Computation-efficient resource allocation strategies are of crucial importance in mobile edge computing networks. However, few works have focused on this issue. In this letter, weighted sum computation efficiency (CE) maximization problems are formulated in a mobile edge computing (MEC) network with orthogonal frequency division multiple access (OFDMA). Both partial offloading mode and binary offloading mode are considered. The closed-form expressions for the optimal subchannel and power allocation schemes are derived. In order to address the intractable non-convex weighted sum-of ratio problems, an efficiently iterative algorithm is proposed. Simulation results demonstrate that the CE achieved by our proposed resource allocation scheme is better than that obtained by the benchmark schemes.

Energy Efficiency of a Decode-and-Forward Multiple-Relay Network with Rate Adaptive LDPC Codes.

This paper presents cooperative transmission (CT), where multiple relays are used to achieve array and diversity gains, as an enabling technology for Internet of Things (IoT) networks with hardware-limited devices. We investigate a channel coding aided decode-and-forward (DF) relaying network, considering a two-hop multiple-relay network, where the data transmission between the source and the destination is realized with the help of DF relays. Low density parity check (LDPC) codes are adopted as forward error correction (FEC) codes to encode and decode the data both at the source and relays. We consider both fixed and variable code rates depending upon the quality-of-service (QoS) provisioning such as spectral efficiency and maximum energy efficiency. Furthermore, an optimal power allocation scheme is studied for the cooperative system under the energy efficiency constraint. We present the simulation results of our proposed scheme, compared with conventional methods, which show that if decoupled code rates are used on both hops then a trade-off has to be maintained between system complexity, transmission delay, and bit error rate (BER).

Performance Analysis and Optimization of Cooperative Full-Duplex D2D Communication Underlaying Cellular Networks

This paper investigates the cooperative full-duplex device-to-device (D2D) communication underlaying a cellular network, where the cellular user (CU) acts as a full-duplex relay to assist the D2D communication. To simultaneously support D2D relaying and uplink transmission, superposition coding and successive interference cancellation are adopted at the CU and the D2D receiver, respectively. The achievable rate region and joint outage probability are derived to characterize the performance of the considered system. In consideration of the fairness between the cellular uplink and the D2D link, an optimal power allocation scheme is proposed to maximize the minimum achievable rate of them. Besides, by analyzing the upper bound of the joint outage probability, we study a suboptimal power allocation to improve the outage performance. The simulation results confirm the theoretical analysis and the advantages of the proposed power allocation schemes.

Generalized Coordinated Multipoint (GCoMP)-Enabled NOMA: Outage, Capacity, and Power Allocation

A novel generalized coordinated multi-point transmission (GCoMP)-enabled non-orthogonal multiple access (NOMA) scheme is proposed. In particular, distributed base stations (BSs) in a network coverage area cooperate on the downlink to serve a set of user equipments (UEs) using the same transmission frequency band. Furthermore, all UEs associated to a BS and using a particular frequency band forms a single NOMA cluster. The number of BSs serving a UE in a particular frequency band is referred to as the order of clustering (or order of BS cooperation). To evaluate the proposed scheme, we derive a closed-form expression for the probability of outage for a UE with different orders of BS cooperation. To obtain important insights on the performance of the proposed system, approximate (asymptotic) expressions for the probability of outage and outage capacity are derived considering both perfect and imperfect channel state information (CSI) estimation. We observe that improved spectral efficiency with a large number of UEs per NOMA cluster can be achieved by increasing the clustering order (i.e., number of cooperating BSs per UE). Furthermore, an optimal transmission power allocation scheme that jointly allocates transmission power fractions from all cooperating BSs to all connected UEs is developed.

An Energy-Efficient Privacy Preserving Security-Oriented DSA With Low Latency

Conventional cryptography techniques based upper layer secure wireless communication solutions are often subject to major issues such as complex key management, high computational complexity, etc. Physical layer security mechanisms are proposed as appealing alternative solutions for secure wireless communications. However, existing physical layer security schemes each faces some major limitations including limited achievable secrecy capacity, sensitive to time-varying channel status, high power consumption and long delay. To tackle these issues, we propose a novel energy efficient security-oriented dynamic spectrum allocation/assignment (S-DSA) algorithm to provide message privacy (confidentiality) with low latency. Our S-DSA algorithm solves the radio resource (spectrum and power) allocation and privacy preserving problems jointly, which is modeled as a mixed-integer multi-objective optimization problem. The branch and bound mechanism integrated with non-dominated sorting genetic algorithm-II (NSGA-II) is proposed to search the optimal channel and power allocation strategy to maximize the achievable system secrecy capacity and minimize the latency and power consumption simultaneously. Simulations confirm that the confidentiality achieved by our serenity-oriented DSA induces negligible degradation on average throughput per user compared with exiting DSA schemes.

Low‐complexity energy‐efficient power allocation scheme for distributed MISO system with beamforming

This letter investigates the energy efficiency (EE) optimisation of a distributed multiple-input single-output (D-MISO) system, and a suboptimal power allocation (PA) scheme with low complexity is developed for D-MISO system with beamforming. Different from the existing optimal PA scheme that needs iterative calculation, the developed scheme can provide closed-form PA and no iteration is required. Using the Cauchy-Schwarz inequality, the upper bound of EE is first obtained, and then the optimised objective function is formulated subject to a set of power budget constraints. By maximising this upper bound, a suboptimal PA scheme for the system is derived, and closed-form PA coefficients are attained. Interestingly, it is found that the proposed scheme has the same general form of PA as the optimal scheme. Numerical results verify the effectiveness of the proposed scheme, it can achieve the EE performance very close to that of the existing optimal scheme due to better approximation, but it has lower complexity than the latter.

A Quasi-Optimal Clustering Algorithm for MIMO-NOMA Downlink Systems

In this letter we consider a resource allocation problem for multi-user MIMO non orthogonal multiple access (MU-MIMO-NOMA) downlink transmissions. Under the NOMA paradigm, users are organized in clusters of strong/weak pair and our aim is to find an optimal clustering, beamforming and power allocation scheme to minimize the power transmitted subject to a rate constraint for each user. Since the joint optimization problem is intractable, we split it in three sub-problems: clustering, which is formulated as a mixed integer linear programming (MILP) problem, beamforming and power allocation. Simulations results show that the our proposed scheme greatly outperforms both the classical OMA scheme and state-of-the-art NOMA techniques.