Adaptive Neural Network Control with Control Allocation for A Manned Submersible in Deep Sea

This paper thoroughly studies a control system with control allocation for a manned submersible in deep sea being developed in China. The proposed control system consists of a neural-network-based direct adaptive controller and a dynamic control allocation module. A control energy cost function is used as the optimization criteria of the control allocation module, and weighted pseudo-inverse is used to find the solution of the control allocation problem. In the presence of bounded unknown disturbance and neural networks approximation error, stability of the closed-loop control system of manned submersible is proved with Lyaponov theory. The feasibility and validity of the proposed control system is further verified through experiments conducted on a semi-physical simulation platform for the manned submersible in deep sea.

Resource Allocation and User Association for HTTP Adaptive Streaming in Heterogeneous Cellular Networks with Small Cells

Video streaming,especially hypertext transfer protocol based(HTTP) adaptive streaming(HAS) of video,has been expected to be a dominant application over mobile networks in the near future,which brings huge challenge for the mobile networks.Although some works have been done for video streaming delivery in heterogeneous cellular networks,most of them focus on the video streaming scheduling or the caching strategy design.The problem of joint user association and rate allocation to maximize the system utility while satisfying the requirement of the quality of experience of users is largely ignored.In this paper,the problem of joint user association and rate allocation for HTTP adaptive streaming in heterogeneous cellular networks is studied,we model the optimization problem as a mixed integer programming problem.And to reduce the computational complexity,an optimal rate allocation using the Lagrangian dual method under the assumption of knowing user association for BSs is first solved.Then we use the many-to-one matching model to analyze the user association problem,and the joint user association and rate allocation based on the distributed greedy matching algorithm is proposed.Finally,extensive simulation results are illustrated to demonstrate the performance of the proposed scheme.

Adaptive Resource Allocation Algorithm for Internet of Things with Bandwidth Constraint

In order to improve the transmission accuracy and efficiency of sensing and actuating signals in Internet of Things （loT） and ensure the system stability, an adaptive resource allocation algorithm is proposed, which dynami- cally assigns the network bandwidth and priority among components according to their signals＇ frequency domain characteristics. A remote sensed and controlled unmanned ground vehicle （UGV） path tracking test-bed was devel- oped and multiple UGV＇s tracking error signals were measured in the simulation for performance evaluation. Results show that with the same network bandwidth constraints, the proposed algorithm can reduce,, the accumulated and maximum errors of UGV path tracking by over 60% compared with the conventional static algorithm.

Adaptive resource management for multi-target tracking in co-located MIMO radar based on time-space joint allocation

Compared with the traditional phased array radar, the co-located multiple-input multiple-output(MIMO) radar is able to transmit orthogonal waveforms to form different illuminating modes, providing a larger freedom degree in radar resource management. In order to implement the effective resource management for the co-located MIMO radar in multi-target tracking,this paper proposes a resource management optimization model,where the system resource consumption and the tracking accuracy requirements are considered comprehensively. An adaptive resource management algorithm for the co-located MIMO radar is obtained based on the proposed model, where the sub-array number, sampling period, transmitting energy, beam direction and working mode are adaptively controlled to realize the time-space resource joint allocation. Simulation results demonstrate the superiority of the proposed algorithm. Furthermore, the co-located MIMO radar using the proposed algorithm can satisfy the predetermined tracking accuracy requirements with less comprehensive cost compared with the phased array radar.

Algorithm of Adaptive Bit Allocation Wavelet Transform Audio Coding

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Theory and model of water resources complex adaptive allocation system

Complex adaptive sys tem theory is a new and important embranchment of system science, which prov ides a new thought to research water resources allocation system. Based on the a nalysis of complexity and complex adaptive mechanism of water resources allocat ion system, a fire-new analysis model is presented in this paper. With t he description of dynamical mechanism of system, behavior characters of agents and the evaluation method of system status, an integrity research system is built to analyse the evolvement rule of water resources allocation system. A nd a brief research for the impact of water resources allocation in benefi cial regions of the Water Transfer from South to North China Project is conducted.

Joint Adaptive Modulation and Power Allocation in Cognitive Radio Networks

Link adaptation is an important issue in the design of cognitive radio networks, which aims at making efficient use of system resources. In this paper, we propose and investigate a joint adaptive modulation and power allocation algorithm in cognitive radio networks. Specifically, the modulation scheme and transmit power are adjusted adaptively according to channel conditions, interference limit and target signal-to-interference-plus-noise ratio (SINR). As such the total power consumption of cognitive users (CUs) is minimized while keeping both the target SINR of CUs and interference to primary user (PU) at an acceptable level. Simulation results are provided to show that the proposed algorithm achieves a significant gain in power saving.

An Adaptive Power Allocation Scheme for Performance Improvement of Cooperative SWIPT NOMA Wireless Networks

Future wireless networks demand high spectral efficiency,energy efficiency and reliability.Cooperative non-orthogonal multiple access(NOMA)with simultaneous wireless information and power transfer(SWIPT)is considered as one of the novel techniques to meet this demand.In this work,an adaptive power allocation scheme called SWIPT based adaptive power allocation(SWIPT-APA-NOMA)is proposed for a power domain NOMA network.The proposed scheme considers the receiver sensitivity of the end users while calculating the power allocation coefficients in order to prevent wastage of power allocated to user in outage and by offering priority to any one of the users to use maximum harvested power.A detailed analysis on the bit error rate(BER)performance of the proposed scheme is done and closed form expression is obtained.Simulations have been carried out with various parameters that influence the receiver sensitivity and the results show that the network achieves better outage and BER performance using the proposed scheme.It is found that the proposed scheme leads to a ten-fold decrease in transmit power for the same error performance of a fixed power allocation scheme.Further,it offers 96.06%improvement in the capacity for a cumulative noise figure and fading margin of 10 dB.

Adaptive resource allocation for multi-user multi-server power-line communication OFDM systems

The bits and power allocation model of adaptive power-rate mixture for multi-user multi-server power-line communication systems was analyzed with the restrictions of maximal total power,fixed rate for each real time (RT) user,minimal rate for each non-real time (NRT) user,maximal bits and power for each subcarrier in each orthogonal frequency division multiplexing (OFDM) symbol. An algorithm of resource dynamic allocation in the first OFDM symbol of each frame and resource optimal adjustment in the latter OFDM symbol of each frame was proposed. In the first OFDM symbol of every frame,resource is firstly assigned for RT users so as to minimize their total used power until satisfying their fixed rates; secondly the remainder resource of power and subcarriers are assigned for NRT users so as to minimize their total used power until satisfying their minimal rates also; lastly the remainder resource is again assigned for NRT users according to the proportional fairness strategy so as to maximize their total assigning rate. In the latter OFDM symbol of each frame,bits are swapped and power is adjusted for every user based on the resource allocation results of anterior OFDM symbol. The algorithm is tested in the typical power-line channel scenarios and the simulation results indicate that the proposed algorithm has better performances than the classical multi-user resource allocation algorithms and it realizes the multiple aims of multi-user multi-server resource allocation for power-line communication systems.

Adaptive Time Slot Resource Allocation in SWIPT IoT Networks

The rapid advancement of Internet of Things(IoT)technology has brought convenience to people’s lives;however further development of IoT faces serious challenges,such as limited energy and shortage of network spectrum resources.To address the above challenges,this study proposes a simultaneous wireless information and power transfer IoT adaptive time slot resource allocation(SIATS)algorithm.First,an adaptive time slot consisting of periods for sensing,information transmission,and energy harvesting is designed to ensure that the minimum energy harvesting requirement ismet while the maximumuplink and downlink throughputs are obtained.Second,the optimal transmit power and channel assignment of the system are obtained using the Lagrangian dual and gradient descent methods,and the optimal time slot assignment is determined for each IoT device such that the sum of the throughput of all devices is maximized.Simulation results show that the SIATS algorithm performs satisfactorily and provides an increase in the throughput by up to 14.4%compared with that of the fixed time slot allocation(FTS)algorithm.In the case of a large noise variance,the SIATS algorithm has good noise immunity,and the total throughput of the IoT devices obtained using the SIATS algorithm can be improved by up to 34.7%compared with that obtained using the FTS algorithm.

MULTICARRIER DS-CDMA WITH ADAPTIVE MODULATION AND POWER ALLOCATION

Adaptive modulation and power allocation is introduced into the multicarrier DS-CDMA system to improve the system performance and bandwidth efficiency. First, the systemdesign appropriate for adaptive modulation and power allocation is given, then the algorithmof adaptive modulation and power allocation is applied. Simulation results demonstrate greatperformance improvement compared with the fixed modulated one.

ADAPTIVE RESOURCE ALLOCATION TECHNIQUES IN OFDMA USING CROSS-LAYER ARCHITECTURE

This paper utilizes the cross-layer architecture to implement adaptive resource allocation in Orthogonal Frequency Division Multiple Access （OFDMA） based on the broadband wireless access system. According to the cross-layer architecture, the information in link layer is used for adaptive resource allocation in OFMDA. A new cross-layer adaptive resource allocation algorithm is developed which can guarantee the users to be in minimum average waiting time in link-layer and get the better spectrum utilization. Numerical results show that our scheme is appealing and can get about half of average waiting time less and 0.5 bps/Hz spectrum utilization more than the scheme in 1EEE802.16a.

POWER ALLOCATION AND ADAPTIVE MODULATION STRATEGY FOR MIMO-OFDM SYSTEMS WITH IMPERFECT CSI

The presented scheme named M-CAP (Maximum CAPacity) uses the CSI (Channel State Information) and its statistics to deduce an equivalent channel according to which the transmit power is allocated to the subchannels. And then modulation scheme is determined adaptively according to the power allocated to each subchannel. The advantage of the M-CAP scheme is that it combines power allocation and adaptive modulation while maintaining a large capacity. We demonstrate by computer simulations that the proposed M-CAP scheme can significantly improve system performance compared with the traditional schemes.

Adaptive Energy-Efficient Power Allocation for DAS with Imperfect Channel State Information and Antenna Selection

Considering that perfect channel state information(CSI) is difficult to obtain in practice,energy efficiency(EE) for distributed antenna systems(DAS) based on imperfect CSI and antennas selection is investigated in Rayleigh fading channel.A novel EE that is defined as the average transmission rate divided by the total consumed power is introduced.In accordance with this definition,an adaptive power allocation(PA) scheme for DAS is proposed to maximize the EE under the maximum transmit power constraint.The solution of PA in the constrained EE optimization does exist and is unique.A practical iterative algorithm with Newton method is presented to obtain the solution of PA.The proposed scheme includes the one under perfect CSI as a special case,and it only needs large scale and statistical information.As a result,the scheme has low overhead and good robustness.The theoretical EE is also derived for performance evaluation,and simulation result shows the validity of the theoretical analysis.Moreover,EE can be enhanced by decreasing the estimation error and/or path loss exponents.

Video transcoding for adaptive bitrate streaming over edge-cloud continuum

Video transcoding is to create multiple representations of a video for content adaptation.It is deemed as a core technique in Adaptive BitRate(ABR)streaming.How to manage video transcoding affects the performance of ABR streaming in various aspects,including operational cost,streaming delays,Quality of Experience(QoE),etc.Therefore,the problems of implementing video transcoding in ABR streaming must be systematically studied to improve the overall performance of the streaming services.These problems become more worthy of investigation with the emergence of the edge-cloud continuum,which makes the resource allocation for video transcoding more complicated.To this end,this paper provides an investigation of the main technical problems related to video transcoding in ABR streaming,including designing a rate profile for video transcoding,providing resources for video transcoding in clouds,and caching multi-bitrate video contents in networks,etc.We analyze these problems from the perspective of resource allocation in the edge-cloud continuum and cast them into resource and Quality of Service(QoS)optimization problems.The goal is to minimize resource consumption while guaranteeing the QoS for ABR streaming.We also discuss some promising research directions for the ABR streaming services.

Spot beam handover trigger and channel allocation scheme in GEO mobile satellite communication

An effective spot beam handover trigger and channel allocation scheme is proposed for GEO mobile satellite communication based on its characteristic and application. By using both signal strength and terminal location information, necessary handover is triggered promptly and accurately to reduce the negative effect of long signaling delay. Then handover decision is made with the handover queuing and channel allocation strategy. An adaptive channel resource allocation scheme is considered to optimize resource utilization with guarantee of emergency communication, which is significant for emergency rescue and disaster relief. Simulation results show that the proposed scheme prevents unnecessary handover effectively and has favorable adaptability to emergent requirement of satellite communication.

WORST SUBCARRIER AVOIDING WATER-FILLING SUBCARRIER ALLOCATION SCHEME FOR OFDM-BASED CRN

Efficient and reliable subcarrier power joint allocation is served as a promising problem in cognitive OFDM-based Cognitive Radio Networks (CRN). This paper focuses on optimal subcarrier allocation for OFDM-based CRN. We mainly propose subcarrier allocation scheme denoted as Worst Subcarrier Avoiding Water-filling (WSAW), which is based on Rate Adaptive (RA) criterion and three constraints are considered in CRN. The algorithm divides the assignment procedure into two phases. The first phase is an initial subcarrier allocation based on the idea of avoiding selecting the worst subcarrier in order to maximize the transmission rate; while the second phase is an iterative adjustment process which is realized by swapping pairs of subcarriers between arbitrary users. The proposed scheme could assign subcarriers in accordance with channel coherence time. Hence, real time subcarrier allocation could be implemented. Simulation results show that, comparing with the similar existing algorithms, the proposed scheme could achieve larger capacity and a near-optimal BER performance.

Fractal image encoding based on adaptive search

Finding the optimal algorithm between an efficient encoding process and therate distortion is the main research in fractal image compression theory. A new method has beenproposed based on the optimization of the Least-Square Error and the orthogonal projection. A largenumber of domain blocks can be eliminated in order to speed-up fractal image compression. Moreover,since the rate-distortion performance of most fractal image coders is not satisfactory, an efficientbit allocation algorithm to improve the rate distortion is also proposed. The implementation andcomparison have been done with the feature extraction method to prove the efficiency of the proposedmethod.

Fuzzy Service Aware Adaptive Cooperative Spectrum Sensing Algorithm

Based on the service characteristics and the sensing ability for secondary users, a joint optimization scheme of spectrum detection and allocation is investigated to expand the available sensing region and allocate the Qo S-specified channels. On the aspect of spectrum detection, due to the available detection index with the global detection metrics, cooperation thresholds are adaptively adjusted to select the cooperative model for maximizing the available sensing region. On the aspect of spectrum allocation, for different service category, the idle channels are efficiently allocated that depend on their stability and available bandwidth. Meanwhile, based on the requested rates defined by fuzzy theory, the secondary users can be divided into two categories, i.e.,delay sensitive service and reliability sensitive service. Finally, the Qo S-specified channels from the targeted spectrum subset are allocated to secondary users. Simulation results show that our proposed algorithm can not only expand the available sensing region,but also decrease the outage probability of delay sensitive services. Additionally, it enables stable power consumption in the time-variation channel.

Downlink call admission control with power allocation and rate scheduling for IDMA-based multi-beam satellite systems

Considering the advantage of interleave-division multiple-access(IDMA) technique and the technical bottlenecks in the existing satellite systems,IDMA is introduced into satellite communication networks.To further validate the IDMA into satellite systems,an effective call admission control(CAC) is proposed to maximize the resource utilization.After establishing the multi-beam satellite system model based on variable spreading gain(VSG) IDMA,the power allocation scheme based on SINR evolution technique and transmission rate adaptation for nonreal time interactive traffic are designed as integrated parts of the CAC,working together to improve the system performance in terms of power efficiency and throughput.Further,the analysis and simulation results show that IDMA under the proposed scheme can provide better QoS,in terms of the blocking/dropping probability,outage probability as well as delay performance.