A New Strategy for Dynamic Channel Allocation in CR-WMN Based on RCA

Channel assignment has emerged as an essential study subject in Cognitive Radio-basedWireless Mesh Networks(CR-WMN).In an era of alarming increase in Multi-Radio Multi-Channel(MRMC)network expansion interference is decreased and network throughput is significantly increased when non-overlapping or partially overlapping channels are correctly integrated.Because of its ad hoc behavior,dynamic channel assignment outperforms static channel assignment.Interference reduces network throughput in the CR-WMN.As a result,there is an extensive research gap for an algorithm that dynamically distributes channels while accounting for all types of interference.This work presents a method for dynamic channel allocations using unsupervisedMachine Learning(ML)that considers both coordinated and uncoordinated interference.Unsupervised machine learning uses coordinated and non-coordinated interference for dynamic channel allocation.To determine the applicability of the proposed strategy in reducing channel interference while increasingWMNthroughput,a comparison analysis was performed.When the simulation results of our proposed algorithm are compared to those of the Routing Channel Assignment(RCA)algorithm,the throughput of our proposed algorithm has increased by 34%compared to both coordinated and non-coordinated interferences.

Capacity of a Class of Dirty-Tape Gaussian Orthogonal Relay Channel with State Information at the Source and Relay

A Gaussian channel with additive interference that is causally known to the transmitter is called a Dirty-Tape Channel(DTC).In this paper,we consider a state-dependent dirty-tape Gaussian relay channel with orthogonal channels from the source to the relay and from the source and relay to the destination.The orthogonal channels are corrupted by two independent additive interferences causally known to both the source and relay.The lower and upper bounds of the channel capacity are established.The lower bound is obtained by employing superposition coding at the source,Partial Decode-and-Forward(PDF)relaying at the relay,and a strategy similar to that used by Shannon at the source and relay.The explicit capacity is characterised when the power of the relay is sufficiently large.Finally,several numerical examples are provided to illustrate the impact of additive interferences and the role of the relay in information transmission and in removing the interference.

Joint Channel Estimation and Decoding Design for 5G-Enabled V2V Channel

This paper addresses the problem of channel estimation in 5G-enabled vehicular-to-vehicular(V2V) channels with high-mobility environments and non-stationary feature. Considering orthogonal frequency division multiplexing(OFDM) system, we perform extended Kalman filter(EKF) for channel estimation in conjunction with Iterative Detector & Decoder(IDD) at the receiver to improve the estimation accuracy. The EKF is proposed for jointly estimating the channel frequency response and the time-varying time correlation coefficients. And the IDD structure is adopted to reduce the estimation errors in EKF. The simulation results show that, compared with traditional methods, the proposed method effectively promotes the system performance.