Earticle

The existence of malicious secondary users will bring damage to the performance of cooperative spectrum sensing and spectrum access in cognitive radio networks, so effectively curbing malicious behavior of secondary users become the key to success for cooperative spectrum sensing mechanism. Inspired by economics of repeated game theory, a trust game model and algorithm of distributed cooperative spectrum sensing oriented to malicious secondary users named FRTrust is proposed. In FRTrust, the reputation status is used to describe the performance of a secondary user in cooperative spectrum sensing process. It encourages secondary users to choose positive and honest behavior strategies for greater and long term benefits. Simultaneously, a ‘differentiation’ punishment mechanism is presented to respond malicious behaviors of secondary users. By this way, the ‘first offender’ secondary users and the ‘recidivist' secondary users can be distinguished effectively. If a secondary user departs from the normal times in its life period, it will be punished superimposed. Simulation results show that the FRTrust algorithm can encourage secondary users to participate in spectrum sensing in a cooperative attitude, improve the transaction success ratio of cooperative spectrum sensing, and guarantee the fairness and spectrum access performance for cognitive radio networks.

In this article, a dual band patch antenna is achieved by introducing T-slot in circular disk with small frequency ratio. It is theoretically investigated using equivalent circuit theory concept. The resonance frequency is found to be 1.84 and 2.02 GHz suitable for DCS-1800, PCS-1900 and IMT-2000 applications. The measured bandwidths at lower and upper resonances are found to be 6.59% and 6.89% respectively for proposed antenna specifications. The effect of slots dimension in the patch is studied. The frequency ratio is found to be 1.09. The maximum gain of the proposed antenna is found to be 6.52 dBi whereas efficiency is found to be 62.17% and 76.42% at lower and upper resonance frequencies respectively. The theoretical results are compared with simulated and measured results and they are in good agreement.

A channel parameter estimation method adapted to a wireless communication system is proposed. The wireless communication system includes a transmitter and a receiver. The proposed method includes following steps. The transmitter transmits a plurality of pilot signals to the receiver by using one of a plurality of preconfigured sparse random pilot patterns. The receiver receives the pilot signals, performs a channel parameter estimation on the pilot signals by using a compressive sensing algorithm to obtain a multipath channel number, and selects a pilot pattern for a next cycle among the preconfigured sparse random pilot patterns according to the multipath channel number and a current pilot number. Additionally, the receiver transmits feedback information associated with the selected pilot pattern to the transmitter.

Weight based clustering has become the mainstream clustering algorithm in low-speed Ad hoc networks because of its excellent cluster stability. However, due to the dynamic topology changing in high-speed Ad hoc network, the cluster stability (network stability) decreased and the cluster maintenance costs increased sharply. To solve the problem, we propose a dynamic entropy based combination weighted clustering approach (DECW). First, according to the history messages of an evaluation node in the network, the upper bound and the lower bound value of each clustering index will be recorded, so the information entropy deviation of the indexes and dynamic entropy weight of each node can be obtained. After, the linear combination weights set of evaluation nodes is modeled as the second-order norm game , and the weight vector deviation is minimized as the optimization goal to get the multi-node dynamic entropy weights. In the cluster maintenance, a new Monte Carlo optimization is proposed to avoid the frequent cluster-heads (CHs) replacement induced of high node mobility of. Simulation results reveal that the proposed approach has the better adaptability in high-speed mobile environment.

In this modern wireless technology Multicarrier communication is one of the more suitable and reliable communication technique. Orthogonal Frequency Division Multiplexing (OFDM) is used as modulation technique in multicarrier communication. The present paper gives an overview of OFDM and the various Channel Estimation techniques used in OFDM. The results implemented in MATLAB gives the performance of LS and the MMSE channel estimators for an OFDM system based on the parameters of BER and MSE. Paper also describes the Delayed feedback MIMO OFDM channel estimation performance of LS and LMMSE and DFT based channel estimation technique for LS-linear and MMSE estimator. BPSK and 16-QAM modulation techniques are used.

To recognize abnormal traffic in network, so as to perceive the illicit behavior in network, carry out scientific and effective management, and ensure the network security, we extracted the abnormal network traffic features and proposed an abnormal network traffic recognition method based on optimized Back Propagation Artificial Neural Networks (BP ANN). The experimental results indicate that, although the training time is longer, but the accuracy rate of BP ANN in abnormal network traffic identification is superior to other methods. And the convergence rate of optimized BP ANN model is significantly faster than traditional BP ANN model.

LTE Advanced has brought revolution in the field of wireless communication technology by providing high data rates of up to 1Gbps. There is a need of increased data rates these days that may support the delivery of richer mobile multimedia contents to the end users. Rate adaptation is one of the key enabling technology in the success of LTE Advanced that has cited attraction of academia and research communities in recent years. Rate adaptation is the determination of the optimal data transmission rate most suitable for current prevailing wireless channel conditions. To maximize the performance of wireless devices, it is important to select the best appropriate rate hence rate adaptation algorithms (RAA’s) are required. This work includes a comprehensive survey on various types of RAA’s in LTE-A for effective resource utilization. Depending on the channel conditions various performance parameters such as throughput, power consumption and latency have been studied. It has been observed from the literature survey that many proposals have been published on LTE-A. Sill there is a need of research to be carried in LTE-A as this technology is not fully matured so open issues and future scope are also raised in this work.

DVB-H is developed to broadcast digital videos to mobile handsets, but data loss is a concern due to the wireless broadcasting nature. In this paper, take WiMAX as an IP-based wireless network to recover the loss packets in DVB-H, and take E-WP based on network coding as the encoding packet selection algorithm. Furthermore, a prioritized scheme EWP-PNC based on E-WP packet selection algorithm is proposed. In this scheme, take a base station in WiMAX as encoding node to encode any two packets that meet the encoding and decoding necessary and sufficient condition into an encoding recovery packet according to the current lost packet distribution, and calculate the benefit of each encoding packet to decide the final priority of all encoding packets. The goals of this scheme are to improve the lost packet recovery ratio and reduce the discarded packet ratio. According to the simulation results, the validity of this scheme is proved.