PSO-BP-Based Optimal Allocation Model for Complementary Generation Capacity of the Photovoltaic Power Station

To improve the operation efficiency of the photovoltaic power station complementary power generation system,an optimal allocation model of the photovoltaic power station complementary power generation capacity based on PSO-BP is proposed.Particle Swarm Optimization and BP neural network are used to establish the forecasting model,the Markov chain model is used to correct the forecasting error of the model,and the weighted fitting method is used to forecast the annual load curve,to complete the optimal allocation of complementary generating capacity of photovoltaic power stations.The experimental results show that thismethod reduces the average loss of photovoltaic output prediction,improves the prediction accuracy and recall rate of photovoltaic output prediction,and ensures the effective operation of the power system.

Activation Distance and Capacity Analysis for Ambient Backscatter Communications with Sensitivity Constraint and Beamforming

Circuit sensitivity of sensors or tags without battery is one practical constraint for ambient backscatter communication systems.This letter considers using beamforming to reduce the sensitivity constraint and evaluates the corresponding performance in terms of the tag activation distance and the system capacity.Specifically,we derive the activation probabilities of the tag in the case of single-antenna and multi-antenna transmitters.Besides,we obtain the capacity expressions for the ambient backscatter communication system with beamforming and illustrate the power allocation that maximizes the system capacity when the tag is activated.Finally,simulation results are provided to corroborate our proposed studies.

Adaptive Resource Allocation Algorithm for 5G Vehicular Cloud Communication

The current resource allocation in 5G vehicular networks for mobile cloud communication faces several challenges,such as low user utilization,unbalanced resource allocation,and extended adaptive allocation time.We propose an adaptive allocation algorithm for mobile cloud communication resources in 5G vehicular networks to address these issues.This study analyzes the components of the 5G vehicular network architecture to determine the performance of different components.It is ascertained that the communication modes in 5G vehicular networks for mobile cloud communication include in-band and out-of-band modes.Furthermore,this study analyzes the single-hop and multi-hop modes in mobile cloud communication and calculates the resource transmission rate and bandwidth in different communication modes.The study also determines the scenario of one-way and two-way vehicle lane cloud communication network connectivity,calculates the probability of vehicle network connectivity under different mobile cloud communication radii,and determines the amount of cloud communication resources required by vehicles in different lane scenarios.Based on the communication status of users in 5G vehicular networks,this study calculates the bandwidth and transmission rate of the allocated channels using Shannon’s formula.It determines the adaptive allocation of cloud communication resources,introduces an objective function to obtain the optimal solution after allocation,and completes the adaptive allocation process.The experimental results demonstrate that,with the application of the proposed method,the maximum utilization of user communication resources reaches approximately 99%.The balance coefficient curve approaches 1,and the allocation time remains under 2 s.This indicates that the proposed method has higher adaptive allocation efficiency.

A DYNAMIC TRANSMISSION CAPACITY ALLOCATION SCHEME FOR WIRED/WIRELESS ATM NETWORKS

The previous research on administration of the transmission capacity in the wired/ wireless ATM networks only focuses on wired part or wireless part. There are very few people do the work extending to the links associating with handoff in the whole network. This paper develops the algorithms of transmission capacity administration on the link connecting the base station and base station controller (including the air interface of the base station) and the VPs among the base station controllers in the wired/ wireless ATM networks, which adapt to the traffic state of each service in every cellular cell to allocate (provision) transmission capacity and to reserve handoff guard capacity on these links, respectively. By simulating and analyzing the performance of the algorithm, it is found that it does well for the multimedia communication in which the transmission capacity requirement of each service may be widely different, so that the network bandwidth resource can be used efficiently.

Capacity and Fairness Maximization-Based Resource Allocation for Downlink NOMA Networks

Non-orthogonal multiple access(NOMA)is one of the leading technologies for 5G communication.User pairing(UP)and power allocation(PA)are the key controlling mechanisms for the optimization of the performance of NOMA systems.This paper presents a novel UP and PA(UPPA)technique for capacity and fairness maximization in NOMA called(CFM-UPPA).The impact of the power allocation coefficient and the ratio between the channel gains of the paired users on the sum-rate capacity and the fairness in NOMA is firstly investigated.Then,based on this investigation,the PA and UP algorithms of the CFM-UPPA technique are proposed.The power allocation coefficient of the proposed PA is formulated as an exponentially decaying function of the ratio between the channel gains of the paired users to maximize the capacity and the fairness,and its maximum value is adjusted to guarantee the successive interference cancellation(SIC)constraints.The proposed UP is based on selecting the user that has the highest channel gain per subcarrier as the strong user to maximize the capacity and selecting the user that has the closest lower channel gain to the strong user’s channel gain as the weak user to improve the fairness and capacity.The performance evaluation of the proposed CFM-UPPA technique in terms of capacity,fairness,and outage probability demonstrates that its performance significantly outperforms that of the orthogonal multiple access(OMA)system and that of the NOMA system with random UP.Also,the simulation results demonstrate the efficiency of the proposed PA in improving the performance of other UP algorithms,such as the random UP algorithm.

Capacity Allocation of Renewable Energy Sources Considering Complementarity

The outputs of renewable energy sources(RESs)are inherently variable and uncertain,such as wind power(WP)and photovoltaic(PV).However,the outputs of various types of RESs in different regions are complementary.If the capacity of RESs could be properly allocated during system planning,variability of the total output could be reduced.Consequently,system reliability and renewable energy(RE)consumption could be improved.This paper proposes an analytical model for optimal complementary capacity allocation of RESs to decrease variability of the total output.The model considers the capacity ratio of RESs as decision variables and the coefficient of variation(CV)of the total output as the objective function.The proposed approach transforms the single-level optimization model into a bilevel optimization model and derives an analytical equation that can directly calculate the optimal complementary capacity ratio(OCCR)of system RESs.Case studies on wind and solar farms in Xinjiang and Qinghai,China,are performed to verify the effectiveness of the proposed analytical allocation method.

New method to compute the throughput capacity of HDR wireless networks

A new non-parameter method is proposed to compute the throughput capacity region of high data rate (HDR) wireless networks. We first transform the task of computing the throughput capacity region into a mathematical optimization problem without introducing any additional parameters. By using a greedy algorithm to solve the optimization problem, the non-parametric characterization of the throughput capacity region of HDR can be obtained. By using the new non-parameter method, the HDR throughput capacity region can be characterized by at most N(M2-M+1)N-1 linear constraints where N is the user number and M is the rate set size. The correctness of the new method is verified by several numerical examples.

Fair subcarrier-power allocation scheme for multiuser multicarrier systems

The main objective of multiuser orthogonal frequency division multiple access(MU-OFDM) is to maximize the total system capacity in wireless communication systems. Thus, the problem in MU-OFDM system is the adaptive allocation of the resources(subcarriers, bits and power) to different users subject to several restrictions to maximize the total system capacity. In this work, a proposed subcarrier allocation algorithm was presented to assign the subcarriers with highest channel gain to the users. After the subcarrier allocation, subcarrier gain-based power allocation(SGPA) was employed for power and bit loading. The simulation results show that the proposed subcarrier-power allocation scheme can achieve high total system capacity and good fairness in allocating the resources to the users with slightly high computational complexity compared to the existing subcarrier allocation algorithms.

Parameter allocation of parallel array bistable stochastic resonance and its application in communication systems

In this paper, we propose a parameter allocation scheme in a parallel array bistable stochastic resonance-based communication system(P-BSR-CS) to improve the performance of weak binary pulse amplitude modulated(BPAM) signal transmissions. The optimal parameter allocation policy of the P-BSR-CS is provided to minimize the bit error rate(BER)and maximize the channel capacity(CC) under the adiabatic approximation condition. On this basis, we further derive the best parameter selection theorem in realistic communication scenarios via variable transformation. Specifically, the P-BSR structure design not only brings the robustness of parameter selection optimization, where the optimal parameter pair is not fixed but variable in quite a wide range, but also produces outstanding system performance. Theoretical analysis and simulation results indicate that in the P-BSR-CS the proposed parameter allocation scheme yields considerable performance improvement, particularly in very low signal-to-noise ratio(SNR) environments.

An Energy Sharing EH-DAS Model and its Power Allocation Among RAUs

For the energy sharing problem of distributed antenna system(DAS)with energy harvesting(EH),a distributed antenna system model capable of sharing collected energy among the components in system is proposed.Compared with the existing model in literatures,the proposed model connects with smart grid through a unified interface and facilitates energy management and scheduling.Based on the proposed model,three kinds of energy sharing methods including the partial energy sharing method,the complete energy sharing method and the self-sustaining energy sharing method are analyzed.Under various energy sharing methods,the corresponding optimization problems of power allocation among the remote antenna units(RAUs)are described,formed and solved.As a result,the corresponding power allocation algorithm to each method has been concluded.Simulation results show that the proposed model is more efficient in terms of the channel capacity and energy efficiency,compared to the existing model.

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

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

A superposition scheme for downlink multicell processing with finite backhaul capacity

In the scenario of downlink multicell processing with finite backhaul capacity in the case of two base stations and two mobile users, by regarding the channel as a multiple access diamond channel with two destinations, an achievability scheme that sends correlated codewords through the multiple access channel with common data is proposed. By considering the superposition structure, fully correlated codewords can be supported by the proposed scheme, which can benefit the system throughput in the case of a relatively-large-capacity backhaul. First, an achievable region for the achievable theory is given and it is proved from the perspective of information theory. Then, in the Gaussian scenario, a simulation combining dirty-paper coding and power allocating is provided for the achievable region. Simulation results demonstrate that when the backhaul capacity is relatively large, the proposed scheme outperforms the existing achievability scheme without the superposition structure.

OPTIMAL POWER ALLOCATION FOR COGNITIVE RADIO UNDER INTERFERENCE OUTAGE CONSTRAINT

Cognitive radio is able to share the spectrum with primary licensed user,which greatly improves the spectrum efficiency.We study the optimal power allocation for cognitive radio to maximize its ergodic capacity under interference outage constraint.An optimal power allocation scheme for the secondary user with complete channel state information is proposed and its approxi-mation is presented in closed form in Rayleigh fading channels.When the complete channel state in-formation is not available,a more practical transmitter-side joint access ratio and transmit power constraint is proposed.The new constraint guarantees the same impact on interference outage prob-ability at primary user receiver.Both the optimal power allocation and transmit rate under the new constraint are presented in closed form.Simulation results evaluate the performance of proposed power allocation schemes and verify our analysis.

Multi-QoS Guaranteed Resource Allocation for Multi-Services Based on Opportunity Costs

To meet the booming development of diversified services and new applications in the future, the fifth-generation mobile conmmnication system （5G） has arisen. Resources are increasingly scarce in the @namic time-varying of 5G networks. Allocating resources effectively and ensuring quality of service （QoS） requirements of multi-seiwices come to be a research focus. In this paper, we utilize effective capacity to build a utility function with multi-QoS metrics, including rate, delay bound and packet loss ratio. Taking advantage of opportunity cost （OC）, we also propose a multi-QoS guaranteed resource allocation algm＇ithm for multi-services to consider the future condition of system. In the algorithm, according to different business characteristics and the theory of OC, we propose different selection conditions for QoS users and best effort （BE） users to choose more reasonable resources. Finally, simulation results show that our proposed algorithm achieves superior system utility and relatively better fairness in multi-service scenarios.

Capacity Analysis and Optimization of Cognitive Ultra Wideband Networks

The integration of cognitive radio and Ultra wideband (UWB) networks has attracted lots of research interests. Cognitive UWB networks not only provide very high data rates but also guarantee the uninterrupted communication of primary system operated in the same frequency band. In this work, the problem of the capacity analyses of cognitive UWB networks is investigated. Different from the conventional cognitive spectrum sharing model which can only utilize the idle spectrum hole, the cognitive UWB system can operate adaptively based on spectrum sensing results. Taking into account several factors such as the transmission power constraint of UWB, the interference constraint of the receivers in primary systems, the secondary UWB network capacity problem is modeled as a convex optimization problem over the transmission power. The optimal power allocation strategy and algorithm are derived based on this optimization problem. Two cases (Perfect Spectrum Sensing and Imperfect Spectrum Sensing) are studied in the paper. Numerical simulation results show that the proposed adaptive power allocationscheme improves the ergodic and outage capacity under both transmission power and interference constraints compared with constant transmission power scheme.

Dual Waterfilling Power Allocation Algorithm in MIMO Systems

Aiming at the problem of resource allocation in multiuser multi-input multi-output (MIMO)systems,a new power allocation algorithm based on dual waterfilling is proposed.Block diagonalization is adopted to cancel the inter-user interference,and then the complete diagonalization method is employed to derive the spatial sub-channels for each user.The overall power of the system is divided among users based on each user’s large scale fading;then the power of each user is further allocated to its spatial sub-channels based on the small scale fading.Simulation results show that compared with the existing resource allocation strategies,the proposed algorithm can provide more ergodic capacity for multi-user MIMO systems.When the total transmit power is 100w,it has 15%capacity advantage over the traditional waterfilling method.

A Resource Allocation Algorithm of Physical-Layer Security for OFDMA System under Non-ideal Condition

In this paper, a resource allocation scheme based on physical layer security under non-ideal condition for OFDMA system is introduced. Firstly, the program uses the information security constructing an OFDMA system Wiretap Channel Model under non-ideal condition. Based on this model, arti?cial noise is generated for secure communications combatting passive multiple eavesdroppers. In order to maximize the average secrecy outage capacity without channel state information of eavesdroppers, we use dual decomposition method to implement subcarriers and power allocation in joint optimization. Simulation results show that the average secrecy outage capacity can achieve 7.81 bit/s/Hz while secrecy outage probability is 0.05 with 50 dB mtransmitpower and 64 sub-carrier for 8 authorized users.

Secure Resource Allocation in Device-to-Device Communications Underlaying Cellular Networks

With increasing the demand for transmitting secure information in wireless networks,deviceto-device(D2D)communication has great potential to improve system performance.As a well-known security risk is eavesdropping in D2D communication,ensuring information security is quite challenging.In this paper,we first obtain the closed-forms of the secrecy outage probability(SOP)and the secrecy ergodic capacity(SEC)for direct and decodeand-forward(DF)relay modes.Numerical results are presented to verify the theoretical results,and these results show the cases that the DF relay mode improves security performance compared to the direct mode at long distances between the transmitter and receiver nodes.Further,we look into the optimization problems of secure resource allocation in D2D communication to maximize the SEC and to minimize the SOP by considering the strictly positive secrecy capacity constraint as a mixed-integer non-linear programming(MINLP)problem.In the continue,we convert the MINLP to convex optimization.Finally,we solve this program with a dual method and obtain an optimal solution in the direct and DF relay modes.

OPTIMAL POWER ALLOCATION WITH AF AND SDF STRATEGIES IN DUAL-HOP COOPERATIVE MIMO NETWORKS

Dual-hop cooperative Multiple-Input Multiple-Output (MIMO) network with multi-relay cooperative communication is introduced. Power allocation problem with Amplify-and-Forward (AF) and Selective Decode-and-Forward (SDF) strategies in multi-node scenario are formulated and solved respectively. Optimal power allocation schemes that maximize system capacity with AF strategy are presented. In addition, optimal power allocation methods that minimize asymptotic Symbol Error Rate (SER) with SDF cooperative protocol in multi-node scenario are also proposed. Furthermore, performance comparisons are provided in terms of system capacity and approximate SER. Numerical and simulation results confirm our theoretical analysis. It is revealed that, maximum system capacity could be obtained when powers are allocated optimally with AF protocol, while minimization of system's SER could also be achieved with optimum power allocation in SDF strategy. In multi-node scenario, those optimal power allocation algorithms are superior to conventional equal power allocation schemes.

Utility-optimization dynamic subcarrier allocation algorithm for SC-FDMA systems

Two utility-optimization dynamic subcarrier allocation(DSA) algorithms are designed for single carrier frequency division multiple access system(SC-FDMA).The two proposed algorithms aim to support diverse transmission capacity requirements in wireless networks,which consider both the channel state information(CSI) and the capacity requirements of each user by setting appropriate utility functions.Simulation results show that with considerable lower computational complexity,the first utility-optimization algorithm can meet the system capacity requirements of each user effectively.However,the rate-sum capacity performance is poor.Furthermore,the second proposed utility-optimization algorithm can contribute a better trade-off between system rate-sum capacity requirement and the capacity requirements of each user by introducing the signal to noise ratio(SNR) information to the utility function based on the first utility-optimization algorithm,which can improve the user requirements processing capability as well as achieve a better sum-rate capacity.