无线通信信号抗干扰识别主要依赖于信号的表层特征,如频率、带宽等,这些特征仅能反映部分信号的内部特性和干扰环境,导致识别精度差,为此研究基于深度神经网络的无线通信信号抗干扰识别。从无线通信环境中采集干扰信号样本并进行预处理...无线通信信号抗干扰识别主要依赖于信号的表层特征,如频率、带宽等,这些特征仅能反映部分信号的内部特性和干扰环境,导致识别精度差,为此研究基于深度神经网络的无线通信信号抗干扰识别。从无线通信环境中采集干扰信号样本并进行预处理,应用短时傅里叶变换(Short Time Fourier Transform,STFT)将信号从时域转换到时频域,全面提取与干扰信号相关的特征。利用深度神经网络建立信号抗干扰识别模型,通过卷化等积、池操作自动学习干扰信号特征,并输出信号抗干扰识别结果。实验结果表明,基于深度神经网络的无线通信信号抗干扰识别方法在5种方法的对比中展现出最优的识别率和抗干扰识别性能,识别精度较好,具有实际应用价值。展开更多
For orthogonal frequency division multiplexing (OFDM) wireless communication, the system throughput and data rate are usually limited by pilots, especially in a high mobility environment. In this paper, an enhanced it...For orthogonal frequency division multiplexing (OFDM) wireless communication, the system throughput and data rate are usually limited by pilots, especially in a high mobility environment. In this paper, an enhanced iterative joint channel estimation and symbol detection algorithm is proposed to enhance the system throughput and data rate. With lower pilot power, the proposed scheme increases system throughput firstly, and then the channel estimation and symbol detection proceed iteratively within one OFDM symbol to improve the BER performance. In the proposed algorithm, the original channel estimate of each OFDM symbol is based on the channel estimate of the previous OFDM symbol, thus the variation of the mobile channel is traced efficiently, so the number of pilots in the time domain can be reduced greatly. Besides reducing the system overhead, the proposed algorithm is also shown by simulation to give much better BER performance than the conventional iterative algorithm does.展开更多
A novel radio-map establishment based on fuzzy clustering for hybrid K-Nearest Neighbor (KNN) and Artifi cial Neural Network (ANN) position algorithm in WLAN indoor environment is proposed. First of all, the Principal...A novel radio-map establishment based on fuzzy clustering for hybrid K-Nearest Neighbor (KNN) and Artifi cial Neural Network (ANN) position algorithm in WLAN indoor environment is proposed. First of all, the Principal Component Analysis (PCA) is utilized for the purpose of simplifying input dimensions of position estimation algorithm and saving storage cost for the establishment of radio-map. Then, reference points (RPs) calibrated in the off-line phase are divided into separate clusters by Fuzzy C-means clustering (FCM), and membership degrees (MDs) for different clusters are also allocated to each RPs. However, the singular RPs cased by the multi-path effect signifi cantly decreases the clustering performance. Therefore, a novel radio-map establishment method is presented based on the modifi cation of signal samples recorded at singular RPs by surface fitting. In the on-line phase, the region which the mobile terminal (MT) belongs to is estimated according to the MDs firstly. Then, in estimated small dimensional regions, MT's coordinates are calculated byKNN positioning method for efficiency purpose. However, for the regions including singular RPs, ANN method is utilized because ofits great pattern matching ability. Furthermore, compared with other typical indoor positioning methods, feasibility and effectiveness of this hybrid KNN/ANN method are also verified by the experimental results in static and tracking situations.展开更多
Wireless mesh network is a new emerging field with its potential applications in extremely unpredictable and dynamic environments.However,it is particularly vulnerable due to its features of open medium,dynamic changi...Wireless mesh network is a new emerging field with its potential applications in extremely unpredictable and dynamic environments.However,it is particularly vulnerable due to its features of open medium,dynamic changing topology, cooperative routing algorithms.The article surveys the state of the art in security for wireless mesh networks.Firstly,we analyze various possible threats to security in wireless mesh networks.Secondly,we introduce some representative solutions to these threats,including solutions to the problems of key management,secure network routing,and intrusion detection.We also provide a comparison and discussion of their respective merits and drawbacks,and propose some improvements for these drawbacks.Finally,we also discuss the remaining challenges in the area.展开更多
This paper reviews the requirements for Software Defi ned Radio (SDR) systems for high-speed wireless applications and compares how well the different technology choices available-from ASICs, FPGAs to digital signal p...This paper reviews the requirements for Software Defi ned Radio (SDR) systems for high-speed wireless applications and compares how well the different technology choices available-from ASICs, FPGAs to digital signal processors (DSPs) and general purpose processors (GPPs) - meet them.展开更多
文摘无线通信信号抗干扰识别主要依赖于信号的表层特征,如频率、带宽等,这些特征仅能反映部分信号的内部特性和干扰环境,导致识别精度差,为此研究基于深度神经网络的无线通信信号抗干扰识别。从无线通信环境中采集干扰信号样本并进行预处理,应用短时傅里叶变换(Short Time Fourier Transform,STFT)将信号从时域转换到时频域,全面提取与干扰信号相关的特征。利用深度神经网络建立信号抗干扰识别模型,通过卷化等积、池操作自动学习干扰信号特征,并输出信号抗干扰识别结果。实验结果表明,基于深度神经网络的无线通信信号抗干扰识别方法在5种方法的对比中展现出最优的识别率和抗干扰识别性能,识别精度较好,具有实际应用价值。
文摘For orthogonal frequency division multiplexing (OFDM) wireless communication, the system throughput and data rate are usually limited by pilots, especially in a high mobility environment. In this paper, an enhanced iterative joint channel estimation and symbol detection algorithm is proposed to enhance the system throughput and data rate. With lower pilot power, the proposed scheme increases system throughput firstly, and then the channel estimation and symbol detection proceed iteratively within one OFDM symbol to improve the BER performance. In the proposed algorithm, the original channel estimate of each OFDM symbol is based on the channel estimate of the previous OFDM symbol, thus the variation of the mobile channel is traced efficiently, so the number of pilots in the time domain can be reduced greatly. Besides reducing the system overhead, the proposed algorithm is also shown by simulation to give much better BER performance than the conventional iterative algorithm does.
基金supported by National High-Tech Research & Development Program of China (Grant No. 2008AA12Z305)
文摘A novel radio-map establishment based on fuzzy clustering for hybrid K-Nearest Neighbor (KNN) and Artifi cial Neural Network (ANN) position algorithm in WLAN indoor environment is proposed. First of all, the Principal Component Analysis (PCA) is utilized for the purpose of simplifying input dimensions of position estimation algorithm and saving storage cost for the establishment of radio-map. Then, reference points (RPs) calibrated in the off-line phase are divided into separate clusters by Fuzzy C-means clustering (FCM), and membership degrees (MDs) for different clusters are also allocated to each RPs. However, the singular RPs cased by the multi-path effect signifi cantly decreases the clustering performance. Therefore, a novel radio-map establishment method is presented based on the modifi cation of signal samples recorded at singular RPs by surface fitting. In the on-line phase, the region which the mobile terminal (MT) belongs to is estimated according to the MDs firstly. Then, in estimated small dimensional regions, MT's coordinates are calculated byKNN positioning method for efficiency purpose. However, for the regions including singular RPs, ANN method is utilized because ofits great pattern matching ability. Furthermore, compared with other typical indoor positioning methods, feasibility and effectiveness of this hybrid KNN/ANN method are also verified by the experimental results in static and tracking situations.
基金Project supported by the Shanghai Minicipal Natural Science Foundation(Grant No09ZR1414900)the National High Technology Development 863 Program of China(Grant No2006AA01Z436,No2007AA01Z452,No2009AA01Z118)
文摘Wireless mesh network is a new emerging field with its potential applications in extremely unpredictable and dynamic environments.However,it is particularly vulnerable due to its features of open medium,dynamic changing topology, cooperative routing algorithms.The article surveys the state of the art in security for wireless mesh networks.Firstly,we analyze various possible threats to security in wireless mesh networks.Secondly,we introduce some representative solutions to these threats,including solutions to the problems of key management,secure network routing,and intrusion detection.We also provide a comparison and discussion of their respective merits and drawbacks,and propose some improvements for these drawbacks.Finally,we also discuss the remaining challenges in the area.
文摘This paper reviews the requirements for Software Defi ned Radio (SDR) systems for high-speed wireless applications and compares how well the different technology choices available-from ASICs, FPGAs to digital signal processors (DSPs) and general purpose processors (GPPs) - meet them.
