Xiaokang Lin

Blind Estimation of the PN Sequence in Lower SNR DS/SS Signals

An approach based on signal subspace analysis is proposed to blind estimation of the PN (Pseudo Noise) sequence from lower SNR (Signal to Noise Ratios) DS/SS (Direct Sequence Spread Spectrum) signals. The received signal is divided into vectors according to a temporal window, from which an autocorrelation matrix is computed and accumulated. The PN sequence can be reconstructed from principal eigenvectors of the matrix.

Use APEX neural networks to extract the PN sequence in lower SNR DS-SS signals

This paper introduces an unsupervised adaptive principal components analysis (APEX) neural network (NN) for blind pseudo noise (PN) sequence extraction of lower signal to noise ratios (SNR) direct sequence spread spectrum (DS-SS) signals. The proposed method is based on eigen-analysis of DS-SS signals. As the eigen-analysis method is based on the decomposition of autocorrelation matrix of signals, it has computational defects when the signal vectors became longer, etc. So, we introduce the APEX NN to extract the PN sequence blindly. We also make complexity analysis of the proposed method and comparison with the other methods. Theoretical analysis and computer simulations verify the effectiveness of the method.

Improving voice capacity in IEEE 802.11 WLAN

Nowadays IEEE 802.11 Wireless Local Area Networks (WLANs) become pervasive driven by huge demands for portable access to the Internet. Meanwhile, Voice over Internet Protocol (VoIP) is one of the fastest growing Internet applications because of its high resource utilization and low cost. This paper focuses on the combination of these two technologies. Aiming to support more voice calls in IEEE 802.11 infrastructure networks, voice capacity in IEEE 802.11 WLAN is studied. Through simulation, it is found that Access Point (AP) is a bottleneck that limits the number of concurrent voice calls. This is because in infrastructure networks, all frames must go through the AP so that the AP has much more traffic, but the AP has no advantage on accessing the medium. In this paper an enhanced DCF protocol is proposed to give AP higher priority to access wireless medium and mitigate AP bottleneck effect. In proposed scheme, APs priority is adjusted dynamically by changing some Distributed Coordination Function (DCF) parameters according to the length of the AP queue. Simulations in various scenarios well verify the improvement achieved with increased voice capacity and decreased access delay.

Fuzzy neural network for VBR MPEG video traffic prediction

As a main video transmission mode for digital media networks, the capability to predict VBR video traffic can significantly improve the effectiveness of quality of services. Therefore, based on fuzzy theory and neural network, a novel video traffic prediction model is proposed for the complex traffic characteristics of MPEG videos. This model reduces the prediction error and computation. Simulation results show that the proposed method is able to predict the original traffic more accurately and reliably than the conventional AR method.

SDL design of OSPF protocol for the wireless private network

This paper presents the design of the open shortest path first (OSPF) protocol for the wireless private network using the specification and description language (SDL). Simulations are run in many scenarios to show that our design is excellent in the aspects of both function and performance. In addition, SDL is proven to be an efficient tool in the development of communication software.

MMAC-DCA: A Multi-Channel MAC Protocol with DCA Mechanism in CDMA Ad Hoc Networks

In this paper a multi-channel MAC protocol with dynamic channel allocation (MMAC-DCA) in CDMA Ad Hoc networks is proposed. Under MMAC-DCA, the service sub-channels are dynamically allocated by the RTS/CTS dialogue on the common sub-channel, only when a node has a packet to transmit. In addition, a Markov mode is presented to analyze the performance of MMAC-DCA.

Adaptive Feature Extraction of Lower SNR DS-CDMA signals

This paper introduces an on-line unsupervised learning neural network (NN) for adaptive feature extraction via principal component analysis (LEAP) of lower signal to noise ratios (SNR) direct sequence code-division multiple-access (DS-CDMA) signals. The proposed method is based on eigen-analysis of DS-CDMA signals. The received signal is firstly sampled and divided into non-overlapping signal vectors according to a temporal window, which duration is a period of signature waveform. Then an autocorrelation matrix is computed and accumulated by these signal vectors one by one. Since we have assumed that the synchronous point between the symbol waveform and observation window have been known, the signal vectors may be sampled and divided at the beginning of this synchronous point, therefore, each vector must contain all information of signature waveforms. In the end, each signature waveform and its strength can be extracted by the principal eigenvector and its associated eigenvalue of autocorrelation matrix blindly. However, the eigenanalysis method belongs to a batch processing method, it becomes inefficiency when it uses in real-time signal process and input signal tracking. In this case, we can use the LEAP NN method to realize on-line adaptive principal feature extraction of the lower SNR input DS-CDMA signals effectively

An On-Line Unsupervised Neural Network to Adaptive Feature Extraction of Lower SNR DS-SS signals

This paper introduces an on-line unsupervised learning neural network (NN) for adaptive feature extraction via principal component analysis (LEAP) of lower signal to noise ratios (SNR) direct sequence spread spectrum (DS-SS) signals. The proposed method is based on eigen-analysis of DS-SS signals. The PN sequence and the strength of the signal can be extracted by the first and second principal eigenvectors and their associated eigenvalues of autocorrelation matrix of DS-SS signals blindly. However the eigen-analysis method belongs to a batch method, it is difficult to real-time implementation. In this case, we can use the LEAP NN method to realize on-line adaptive principal feature extraction of the lower SNR received DS-SS signals effectively. Unlike other feature extraction methods, the estimate of the PN sequence and signal strength improves steadily with the number of code repeats. The method is applicable to arbitrary PN spreading sequence and message sequences and can theoretically operate in environments containing arbitrary levels of white background noise, and for signals with arbitrary unknown timing phase. The method requires the DS-SS signal to have a constant-modulus spreading sequence and unrelated message and code-repeat rates. This paper introduces the basic technique, and demonstrates the algorithm via computer simulation for a single DS-SS signal received in the presence of white Gaussian noise

A multichannel protocol with QoS provision in ad hoc network

Since the packages from different nodes collide with each other frequently in Ad Hoc networks, it is hard to guarantee QoS of Real-Time multimedia services if only adopting traditional multi-channel MAC protocols such as DCA, MMAC, etc. In this paper, a new multi-channel MAC technology called MAC-MC is proposed. Under MAC-MC protocol, the wireless channel is divided into one control sub-channel and N service sub-channels. The nodes in Ad Hoc network exchange RTS/CTS messages in the control sub-channel to reserve the service sub-channel for dada package. The access mechanism in the control sub-channel is designed basing on DIFFSERV mode. The parameters value of the Real-Time service package CW is different to that of Best-Effort service packages, so that the Real-Time service packages can obtain the higher priority to access the control sub-channel. In addition, a bi-dimension Markov mode is presented to analyze the performances of MAC-MC protocol theoretically. The results via simulation show that: Compared with MMAC protocol, the transfer delay of Real-Time service package is decreased greatly under the MAC-MC protocol; the networks throughput under MAC-MC protocols is larger than the networks throughput under IEEE 802.11 EDCF protocols.

Use of embedded top-set box to reconstruct the traditional optical network equipment into ASON equipment

ASON is new type of optical network which can offer the flexibility for bandwidth allocation and fast provision of the new service. However, until now there still are many non-ASON optical networks. It is a challenging issue to reconstruct them into ASON smoothly. In this paper, we propose a new reconstructing technology. This technology performs the function of the control plane such as link management, path management and interface management by an embedded top-set-box (ETSB). The ETSB is located between EMS and the traditional NE such as DWDM, WDM, SDH, etc. By this technology the hardware module of the existing optical network element (NE) need not modification. Thus, compared with other reconstructing technologies, the cost and the risk of this reconstructing technology are smaller.