Cooperative Channel and Optimized Route Selection in Adhoc Network

Over the last decade,mobile Adhoc networks have expanded dramati-cally in popularity,and their impact on the communication sector on a variety of levels is enormous.Its uses have expanded in lockstep with its growth.Due to its instability in usage and the fact that numerous nodes communicate data concur-rently,adequate channel and forwarder selection is essential.In this proposed design for a Cognitive Radio Cognitive Network(CRCN),we gain the confidence of each forwarding node by contacting one-hop and second level nodes,obtaining reports from them,and selecting the forwarder appropriately with the use of an optimization technique.At that point,we concentrate our efforts on their channel,selection,and lastly,the transmission of data packets via the designated forwarder.The simulation work is validated in this section using the MATLAB program.Additionally,steps show how the node acts as a confident forwarder and shares the channel in a compatible method to communicate,allowing for more packet bits to be transmitted by conveniently picking the channel between them.We cal-culate the confidence of the node at the start of the network by combining the reliability report for thefirst hop and the reliability report for the secondary hop.We then refer to the same node as the confident node in order to operate as a forwarder.As a result,we witness an increase in the leftover energy in the output.The percentage of data packets delivered has also increased.

A New Infrared Atmospheric Sounding Interferometer Channel Selection and Assessment of Its Impact on Met Office NWP Forecasts

A new set of Infrared Atmospheric Sounding Interferometer （IASI） channels was re-selected from 314 EUMETSAT channels. In selecting channels, we calculated the impact of the individually added channel on the improvement in the analysis outputs from a one-dimensional variational analysis （1D-Var） for the Unified Model （UM） data assimilation system at the Met Office, using the channel score index （CSI） as a figure of merit. Then, 200 channels were selected in order by counting each individual channel＇s CSI contribution. Compared with the operationally used 183 channels for the UM at the Met Office, the new set shares 149 channels, while the other 51 channels are new. Also examined is the selection from the entropy reduction method with the same 1D-Var approach, Results suggest that channel selection can be made in a more objective fashion using the proposed CSI method. This is because the most important channels can be selected across the whole IASI observation spectrum. In the experimental trial runs using the UM global assimilation system, the new channels had an overall neutral impact in terms of improvement in forecasts, as compared with results from the operational channels. However, upper-tropospheric moist biases shown in the control run with operational channels were significantly reduced in the experimental trial with the newly selected channels. The reduction of moist biases was mainly due to the additional water vapor channels, which are sensitive to the upper-tropospheric water vapor.

A new layered space-time detection algorithm for frequency selective fading multiple-input multiple-output channels based on particle filter

In this paper, a new observation equation of non-Gaussian frequency selective fading Bell Labs layered space time （BLAST） architecture system is proposed, which is used for frequency selective fading channels and non-Gaussian noise in an application environment of BLAST system. With othogonal matrix triangularization （QR decomposition） of the channel matrix, the static observation equation of frequency selective fading BLAST system is transformed into a dynamic state space model, and then the particle filter is used for space-time layered detection. Making the full use of the finite alphabet of the digital modulation communication signal, the optimal proposal distribution can be chosen to produce particle and update the weight. Incorporated with current method of reducing error propagation, a new space-time layered detection algorithm is proposed. Simulation result shows the validity of the proposed algorithm.

CRAMER-RAO BOUNDS OF THE FREQUENCY ESTIMATION IN THE TIME SELECTIVE RADIO CHANNELS WITH DOPPLER SPREAD

The mobile channel is slow fading and time selective, thus the multiplicative and additive noise of the channel will smear the spectral line, or arouse Doppler spread. This spread will make the parameters estimation accuracy degrade. The goal of this paper is to analytically assess this degradation when Carrier Frequency Offset (CFO) and Doppler shift exist jointly. Then the finite-sample Cramer-Rao Lower Bound (CRLB) is derived and close-form asymptotical expression is given for large-sample CRLB. These expressions give insights into the performance room for frequency estimation. Also the variance of Doppler shift estimator is simulated to illustrate the theoretical results.

Multi-Agent Few-Shot Meta Reinforcement Learning for Trajectory Design and Channel Selection in UAV-Assisted Networks

Unmanned aerial vehicle(UAV)-assisted communications have been considered as a solution of aerial networking in future wireless networks due to its low-cost, high-mobility, and swift features. This paper considers a UAV-assisted downlink transmission,where UAVs are deployed as aerial base stations to serve ground users. To maximize the average transmission rate among the ground users, this paper formulates a joint optimization problem of UAV trajectory design and channel selection, which is NP-hard and non-convex. To solve the problem, we propose a multi-agent deep Q-network(MADQN) scheme.Specifically, the agents that the UAVs act as perform actions from their observations distributively and share the same reward. To tackle the tasks where the experience is insufficient, we propose a multi-agent meta reinforcement learning algorithm to fast adapt to the new tasks. By pretraining the tasks with similar distribution, the learning model can acquire general knowledge. Simulation results have indicated the MADQN scheme can achieve higher throughput than fixed allocation. Furthermore, our proposed multiagent meta reinforcement learning algorithm learns the new tasks much faster compared with the MADQN scheme.

BLIND CHANNEL ESTIMATION IN DELAY DIVERSITY FOR FREQUENCY SELECTIVE CHANNELS

Delay diversity is an effective transmit diversity technique to combat adverse effects of fading. Thus far, previous work in delay diversity assumed that perfect estimates of current channel fading conditions are available at the receiver and training symbols are required to estimate the channel from the transmitter to the receiver. However, increasing the number of the antennas increases the required training interval and reduces the available time with in whichdata may be transmitted. Learning the channel coefficients becomes increasingly difficult for the frequency selective channels. In this paper, with the subspace method and the delay character of delay diversity, a channel estimation method is proposed, which does not use training symbols. It addresses the transmit diversity for a frequency selective channel from a single carrier perspective in the form of a simple equivalent flat fading model. Monte Carlo simulations give the performance of channel estimation and the performance comparison of our channel-estimation-based detector with decision feedback equalization, which uses the perfect channel information.

ESTIMATION OF BASIS EXPANSION MODELS FOR DOUBLY SELECTIVE CHANNELS

By analyzing the relationship between Basis Expansion Model (BEM) and Doppler spectrum, this letter proposed a quasi-MMSE-based BEM estimation scheme for doubly selective channels. Based on the assumption that the basis coefficients are approximately independent and have the same variance for the same channel tap, the quasi-MMSE estimation shows approximately optimal performance and is robust to noise. Moreover, it can avoid a high Peak-to-Average Power Ratio (PAPR) by using continuous pilots. Performance of the proposed estimation scheme has been shown with computer simulations.

Controlling Ion Conductance and Channels to Achieve Synapticlike Frequency Selectivity

Enhancing ion conductance and controlling transport pathway in organic electrolyte could be used to modulate ionic kinetics to handle signals. In a Pt/Poly(3-hexylthiophene-2,5-diyl)/Polyethylene?Li CF3SO3/Pt hetero-junction, the electrolyte layer handled at high temperature showed nano-fiber microstructures accompanied with greatly improved salt solubility. Ions with high mobility were confined in the nano-fibrous channels leading to the semiconducting polymer layer,which is favorable for modulating dynamic doping at the semiconducting polymer/electrolyte interface by pulse frequency.Such a device realized synaptic-like frequency selectivity, i.e., depression at low frequency stimulation but potentiation at high-frequency stimulation.

A Bintree Energy Approach for Colour Image Segmentation Using Adaptive Channel Selection

A new hierarchical approach called bintree energy segmentation was presented for color image segmentation. The image features are extracted by adaptive clustering on multi-channel data at each level and used as the criteria to dynamically select the best chromatic channel, where the segmentation is carried out. In this approach, an extended direct energy computation method based on the Chan-Vese model was proposed to segment the selected channel, and the segmentation outputs are then fused with other channels into new images, from which a new channel with better features is selected for the second round segmentation. This procedure is repeated until the preset condition is met. Finally, a binary segmentation tree is formed, in which each leaf represents a class of objects with a distinctive color. To facilitate the data organization, image background is employed in segmentation and channels fusion. The bintree energy segmentation exploits color information involved in all channels data and tries to optimize the global segmentation result by choosing the 'best' channel for segmentation at each level. The experiments show that the method is effective in speed, accuracy and flexibility.

THE THEORETICAL BER PERFORMANCE ANALYSIS OF A COOPERATIVE DIVERSITY SCHEME IN FREQUENCY SELECTIVE FADING CHANNEL

A novel cooperative diversity scheme based on Distributed Space-Time Block Coding and Multi-Carrier Code Division Multiple Access (DSTBC-MC-CDMA) is proposed which works well in frequency selective fading channels with multiple single-antenna users. And an analytical error model is established to describe the symbol decoding errors between interusers, based on which a close form expression for theoretical Bit Error Rate (BER) performance of the scheme is derived to analyze the influence of the interuser decoding errors on the BER performance of the scheme. Then simulation is complimented to verify the analytic result above, which also shows that the BER performance of DSTBC-MC-CDMA outgoes that of non-cooperative MC-CDMA with considerable gains. Further- more, the simulations coincide with the theoretical results well.

Signal Detection for OFDM-IDMA Uplink over Doubly Selective Channels

Orthogonal frequency division multiplexing-interleave division multiple access (OFDM-IDMA) systems may suffer from serious inter-carrier interference (ICI) in time-and frequency-selective (doubly selective) channels. In such case, the conventional OFDM-IDMA detection algorithm for quasi-static channels will result in significantly performance degradation. In this paper, signal detection is investigated for OFDM-IDMA uplink over doubly selective channels. Firstly, the impact of time-varying channels for OFDM-IDMA uplink is analyzed, which leads to the failure of the conventional algorithm. Secondly, a novel iterative detection algorithm is developed based on an integrated interference canceller, which can iteratively estimate and mitigate the ICI as well as multiple access interference (MAI) simultaneously. In addition, an improved detection algorithm is derived for reducing the complexity using an approximation to the mean and variance of the interference. Simulation results indicate that the proposed algorithm can significantly enhance the system performance to the conventional case, and the improved algorithm can strike a balance between performance and complexity.

Synthetic Channel-forming Peptides and Ion Selectivity

Introduction Peptides made up of alternating L- and D- amino acids can form β-helices as in gramicidin A or cyclic peptides that aggregate to form tubes In both cases the structures are hollow with all the side chains projecting outwards. Kennedy et al. postulated that. peptides having the （LLLD）n configuration could form helices with every fourth side chain projecting inward. It is a fact that synthetic N-formyl- （LeuSerLeuGly） 6- OH, when added to a lipid bilayer, dimerizes, to form ion channels having conductances greater than that of gramicidin.

Factor-graph-based iterative channel estimation and signal detection algorithm over time-varying frequency-selective fading channels

The problem of soft-input so,output （ SISO ） detection for time-varying frequency-selec- tive fading channels is considered. Based on a suitably-designed factor graph and the sum-product al- gorithm, a low-complexity iterative message passing scheme is proposed for joint channel estima- tion, equalization and decoding. Two kinds of schedules （parallel and serial） are adopted in message updates to produce two algorithms with different latency. The computational complexity per iteration of the proposed algorithms grows only linearly with the channel length, which is a significantly de- crease compared to the optimal maximum a posteriori （MAP） detection with the exponential com- plexity. Computer simulations demonstrate the effectiveness of the proposed schemes in terms of bit error rate performance.

Linear and Nonlinear Time Domain Block Equalizers on MIMO Frequency Selective Channels

Single-Carrier (SC) transmission with the same bandwidth as Multi-Carrier (MC) transmission (such as OFDM) may have far shorter symbol duration and is considered to be more robust against time selective fading. In this paper, we proposed the novel equalization and signal separation schemes in time domain for short block length transmission, i.e., Block Linear Equalization (BLE) and Block Nonlinear Equalization (BNLE) on MIMO frequency selective fading channels. The proposed BLE uses the MMSE based inverse matrix in time domain and the BNLE utilizes the QRD-M (QR Decomposition with M algorithm) with appropriate receiver complexity. We compared the computational complexity among the conventional SC-FDE (Frequency Domain Equalization) scheme and the proposed equalizers. We also used the Low-Density Parity Check (LDPC) decoder concatenated to the proposed BLE and BNLE.

Dynamic channel estimation-aware routing protocol in mobile cognitive radio networks for smart IIoT applications

Cognitive Radio Networks(CRNs)have become a successful platform in recent years for a diverse range of future systems,in particularly,industrial internet of things(IIoT)applications.In order to provide an efficient connection among IIoT devices,CRNs enhance spectrum utilization by using licensed spectrum.However,the routing protocol in these networks is considered one of the main problems due to node mobility and time-variant channel selection.Specifically,the channel selection for routing protocol is indispensable in CRNs to provide an adequate adaptation to the Primary User(PU)activity and create a robust routing path.This study aims to construct a robust routing path by minimizing PU interference and routing delay to maximize throughput within the IIoT domain.Thus,a generic routing framework from a cross-layer perspective is investigated that intends to share the information resources by exploiting a recently proposed method,namely,Channel Availability Probability.Moreover,a novel cross-layer-oriented routing protocol is proposed by using a time-variant channel estimation technique.This protocol combines lower layer(Physical layer and Data Link layer)sensing that is derived from the channel estimation model.Also,it periodically updates and stores the routing table for optimal route decision-making.Moreover,in order to achieve higher throughput and lower delay,a new routing metric is presented.To evaluate the performance of the proposed protocol,network simulations have been conducted and also compared to the widely used routing protocols,as a benchmark.The simulation results of different routing scenarios demonstrate that our proposed solution outperforms the existing protocols in terms of the standard network performance metrics involving packet delivery ratio(with an improved margin of around 5–20%approximately)under varying numbers of PUs and cognitive users in Mobile Cognitive Radio Networks(MCRNs).Moreover,the cross-layer routing protocol successfully achieves high routing performance in finding a robust route,selecting the high channel stability,and reducing the probability of PU interference for continued communication.

Anti-jamming channel access in 5G ultra-dense networks: a game-theoretic learning approach

This paper investigates the Quality of Experience(QoE)oriented channel access anti-jamming problem in 5th Generation Mobile Communication(5G)ultra-dense networks.Firstly,considering that the 5G base station adopts beamforming technology,an anti-jamming model under Space Division Multiple Access(SDMA)conditions is proposed.Secondly,the confrontational relationship between users and the jammer is formulated as a Stackelberg game.Besides,to achieve global optimization,we design a local cooperation mechanism for users and formulate the cooperation and competition among users as a local altruistic game.By proving that the local altruistic game is an Exact Potential Game(EPG),we further prove the existence of pure strategy Nash Equilibrium(NE)among users and Stackelberg Equilibrium(SE)between users and jammer.Thirdly,to obtain the equilibrium solutions of the proposed games,we propose an anti-jamming channel selection algorithm and improve its convergence speed through heterogeneous learning parameters.The simulation results validate the convergence and effectiveness of the proposed algorithm.Compared with the throughput optimization scheme,our proposed scheme obtain a greater network satisfaction rate.Finally,we also analyze user fairness changes during the algorithm convergence process and get some interesting conclusions.

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.

Wavelength Channel Bandwidth of Wavelength-Selective Devices

Narrow bandwidth is a crucial factor in a high performance wavelength selective device(WSD). There are many different expressions to estimate bandwidths of many different WSDs. In this paper, we derive an important rule that the differential time delay between two coupling modes is the most important factor deciding the wavelength channel bandwidth for several different WSDs. This rule reveals that larger differential time delay between two coupling modes results in higher discrimination level of the operating wavelength. Based on the rule, a novel design of wavelength selective coupler that has a bandwidth narrower than normal couplers is presented.

Mode Selection Strategy of Dual Distribution Channel Based on Revenue Analysis

Within the scope of dual distribution channel(DDC)modes—ME&T-C and M-T&E-C,a game model designed for channel members was proposed.Based on this game model,the game equilibrium under both centralized and decentralized decisionmaking situations was analyzed,the channel members' and overall revenues of two modes under the same decision-making situation are compared,and the influence of demand shift coefficient to the overall and members' revenue was also studied through example analysis.Based on the comparison and analysis of the revenue yielded from the two DDC modes,it's discovered that within a certain hypothetical range,the M-T&E-C mode seems to be a better option for the manufacturer than the ME&T-C mode.Therefore,this discovery can be served as a theoretical reference for manufacturers when choosing the optimal DDC mode in real life.

考虑碳排放与交付时间敏感的渠道选择研究

为了研究消费者对碳排放和交付时间具有双重敏感性的市场环境下,制造商选择传统单一零售渠道或网上零售渠道的策略,本文构建了由制造商和传统零售商组成的传统单一零售渠道和网上直销双渠道两种供应链结构,对比分析两种模型的均衡定价策略及供应链成员的最优利润,探讨在消费者具有双重敏感性下,零售商与制造商的渠道偏好。研究发现,双渠道的碳减排水平总是比单渠道的高。当消费者偏好于网上直销渠道,且消费者的双重敏感性及双渠道中渠道竞争均较小时,零售商愿意接受较高的批发价格并且偏好传统单一零售渠道;反之,零售商更偏好网上直销双渠道。当消费者偏好于网上直销渠道时,制造商会选择网上直销双渠道模型。当消费者不偏好网上直销渠道,且消费者双重敏感性及双渠道中渠道竞争均较小时,制造商才会选择传统单一零售渠道模型;否则,即使消费者不偏好网上渠道,双重敏感性及竞争有一项较大时,制造商也会选择网上直销双渠道。