AN ENHANCED DETECTION ALGORITHM FOR V-BLAST SYSTEM

A decoding method complemented by Maximum Likelihood (ML) detection for V-BLAST (Verti- cal Bell Labs Layered Space-Time) system is presented. The ranked layers are divided into several groups. ML decoding is performed jointly for the layers within the same group while the Decision Feedback Equalization (DFE) is performed for groups. Based on the assumption of QPSK modulation and the quasi-static flat fading channel, simulations are made to testify the performance of the proposed algorithm. The results show that the algorithm outperforms the original V-BLAST detection dramatically in Symbol Error Probability (SEP) per- formance. Specifically, Signal-to-Noise Ratio (SNR) improvement of 3.4dB is obtained for SEP of 10?2 (4×4 case), with a reasonable complexity maintained.

BER Performance Analysis of Asynchronous NOMA with Arbitrary Phase Offset

An asynchronous transmission scenario for non-orthogonal multiple access(NOMA)user signals with arbitrary phase offset is investigated in this paper.To improve the system performance in the user power-balanced conditions,we adopt a synthetic detection method at the receiver,i.e.,the jointly optimal maximal likelihood detection aided triangular successive interference cancellation(JO ML-TSIC)method.Analytical bit error rate(BER)solutions are obtained for a two-user case with the optimal,intentional onehalf symbol period time delay implemented between the user signals.Furthermore,closed-form BER solutions for the case using the triangular successive interference cancellation(TSIC)detection method are also derived for comparisons.Numerical results show that the JO ML-TSIC receiver for the asynchronous system outperforms the TSIC receiver as well as the synchronous successive interference cancellation(SIC)receiver in all the conditions concerned.The results also show that the superiority of the JO ML-TSIC receiver is strengthened when the signals experience flat Rayleigh fading channels compared to the TSIC and the synchronous SIC receivers.

Joint Semi-Blind Channel Estimation and Data Sequence Detection of OFDM Systems

In this paper, a joint semi blind channel estimation and data sequence detection of OFDM systems over the multipath frequency selective fading channels is proposed and investigated. The basic idea of the algorithm is to first use the correlation among adjacent subchannels in the frequency domain to estimate the channel's parameters with an AutoRegressive (AR) process based on the decision directed estimation principle, and then to search the ML solution using the Viterbi algorithm. The algorithm realizes on line channel estimation and data detection of OFDM signals without any periodic pilot signal and statistic information about the channels, so it is suited to high data rate transmission over slow fading channels in the coming generation mobile communication systems.

CNN demodulation model with cascade parallel crossing for CPM signals

The continuous phase modulation(CPM)technique is widely used in range telemetry due to its high spectral efficiency and power efficiency.However,the demodulation performance of the traditional maximum likelihood sequence detection(MLSD)algorithm significantly deteriorates in non-ideal synchronization or fading channels.To address this issue,this work proposes a convolutional neural network(CNN)called the cascade parallel crossing network(CPCNet)to enhance the robustness of CPM signals demodulation.The CPCNet model employs a multiple parallel structure and feature fusion to extract richer features from CPM signals.This approach constructs feature maps at different levels,resulting in a more comprehensive training of the model and improved demodulation performance.Simulation results show that under Gaussian channel,the proposed CPCNet achieves the same bit error rate(BER)performance as MLSD method when there is no timing error,but with 1/4 symbol period timing error,the proposed method has 2 dB demodulation gain compared with CNN and convolutional long short-term memory deep neural network(CLDNN).In addition,under Rayleigh channel,the BER of the proposed method is reduced by 5%-87%compared to that of MLSD in the wide signal-to-noise ratio(SNR)region.

Outage Detection for Distribution Networks Using Limited Number of Power Flow Measurements

Accurate topology estimation is crucial for effectively operating modern distribution networks.Line outages in a distribution network change the network topology by disconnecting some parts of the network from the main grid.In this paper,an outage detection(or topology estimation)algorithm for radial distribution networks is presented.The algorithm utilizes noisy power flow measurements collected from a subset of lines in the network,and statistical information characterizing errors in forecasting load demands.Additionally,a sensor placement scheme is presented.The sensor placement provides critical sensing for the outage detection algorithm so that any number of possible outages in the network can be detected.The performance of the proposed outage detection algorithm using the proposed sensor placement is demonstrated through several numerical results on the IEEE 123-node test feeder.

Novel incremental relaying protocol based on spatial modulation

This paper presents a novel incremental relaying protocol based on spatial modulation for cooperative transmission over quasi-static rayleigh fading channel, namely spatial modulation incremental relaying （SMIR）, which applies the concept of spatial modulation into incremental relaying. In the proposed protocol, information bits are mapped into two information carrying units： 1） a constellation point in the constellation diagram and 2） the spatial domain, i.e. into the location of a particular cooperative user number. The analytical expression of the frame error rate （FER） for SMIR protocol is derived. Simulation results confirm the presented mathematical analysis and show that SMIR protocol gains 2 and 3 dB in signal to noise ratio （SNR） over the conventional protocol for 3-and 5-bit/symbol transmissions respectively. Moreover, under this protocol the system can achieve a much higher throughput, which means that our proposed protocol brings significant gain in performance.