Lifetime Optimization via Network Sectoring in Cooperative Wireless Sensor Networks

Employing cooperative communication in multihop wireless sensor networks provides the network with significant energy efficiency. However, the lifetime of such a network is directly dependant upon the lifetime of each of its individual sections (or clusters). Ignoring the fact that those sections close to sink have to forward more data (their own data plus the data received from the previous sections) and hence die sooner with considering equal section sizes, leads to a sub-optimal lifetime. In this paper, we optimize the section sizes of a multihop cooperative WSN so that it maximizes the network lifetime. Simulation results demonstrate a significant lifetime enhancement for the proposed optimal sectoring.

A Two Step Secure Spectrum Sensing Algorithm Using Fuzzy Logic for Cognitive Radio Networks

In this paper, a two step secure spectrum sensing algorithm is proposed for cognitive radio networks. In this algorithm, the sensing results of secondary users are pre-filtered and applying fuzzy logic, so, the overall sensing performance of the network is improved. To determine pre-filter parameters, statistical parameters of the sensing results are used to remove those sensing results which are far from the majority sensing results. However, to obtain a better performance in the spectrum sensing, we propose a fuzzy logic to nullify the effects of malicious users who transmit false sensing data to the fusion center. We further propose a Fuzzy Trust Level for each user as to weight the sensing result of the corresponding user before combining all sensing results in the fusion center. Simulation results demonstrate that our proposed algorithm yield significant improvement in the performance of the spectrum sensing and identifying malicious users.

A Novel Cooperative Spectrum Sharing Algorithm Based on Optimal Cognitive Radio User Selection

In this paper, we consider the problem of cognitive radio (CR) user selection to maximize overall CR network (CRN) throughput when the available spectrum bandwidth is less than the demand by all CR users. We formulate optimal CR user selection problem. Then, based on approximation of the average received signal to interference plus noise ratio (SINR) and adaptive modulation and coding (AMC), we estimate the required bandwidth of CR users with different required quality of services (QoSs). Using the principle of optimality, we propose a novel cooperative spectrum sharing algorithm for a CRN. The proposed algorithm not only achieves exhaustive search performance but also its complexity is in the order of N × M versus 2N for exhaustive search, where N is the number of CR users, and M is the spectrum pool size. Extensive simulation results illustrate that the proposed algorithm significantly outperforms the existing algorithms that ignore optimal CR user selection. Also, these results illustrate a better fairness criterion than those of previous works.

LDPC-Coded OFDM Transmission Based on Adaptive Power Weights in Cognitive Radio Systems

In this paper, we propose a new scheme to improve the performance of an LDPC-coded OFDM based cognitive radio (CR) link by applying adaptive power weights. To minimize estimation errors of detected signals in all the CR subcarriers, power weights are allocated to the CR subcarriers at the secondary transmitter. Some constraints for the power weights are considered, such as keeping the interference power introduced by the CR to primary users below a given interference threshold and also keeping sum of transmission powers in all CR subcarriers within a total transmission power. The LDPC decoder applies these power weights in the Log Likelihood Ratios (LLRs) used in message passing scheme at the secondary receiver to achieve more reliable communications. So, the received signal in each CR subcarrier will be decoded with the knowledge of transmission power weights, which come from the cognitive feedback channel without additional cost. Simulation results demonstrate that our proposed scheme achieves a lower bit error rate and a higher transmission rate compared with those of the same scheme without applying power weights.

Secure Cognitive Radio Communication for Internet-of-Things: Anti-PUE Attack Based on Graph Theory

Internet of Things (IoT) paradigm with strong impact on future life will be interconnected through Cognitive Radio Networks (CRNs). CRNs with Ubiquitous trait are highly promising to achieve interference-free and on-demand services. CRs are able to sense the spectral environment, to detect unoccupied bands, and to use them for signal transmissions. This opportunity encourages malicious Users to surpass CRs by Primary User Emulation (PUE) attack and use vacant spectrums. This paper proposes an unsupervised algorithm to distinguish CRs from PUs regardless of static and mobile user. Employing K-means and graph theory are coincident in our algorithm to improve detection outcomes. The edge of graph corresponding to the relation between signals is used and the result of comparison the signal properties is exposed to different clusters. The Receiver Operating Characteristic (ROC) and Detection Error Tradeoff (DET) of our proposed algorithm prove our claim.

Performance Analysis of Downlink MIMO WCDMA Systems Using Antenna Selection in Transmitter and MRC Plus LDD in Receiver over Correlated Nakagami-Fading Channels

In this paper bit error rate (BER) performance is analyzed for multiple input-multiple output (MIMO) communications systems using antenna selection in the transmitter, maximal ratio combining (MRC) and linear de-correlating detector (LDD) in the receiver in wide band code division multiple access (WCDMA) downlink channels with correlated Nakagami fading. The MRC maximizes signal to noise ratio of the received signal, then the LDD cancels out multiple access interference (MAI). Theoretical results are validated using computer simulations. Moreover, a pilot based estimation method is proposed to jointly estimate the channel gains and the rows of the LDD operator. Simulation results show that using this proposed method, diversity order is maintained in the receiver. Furthermore, our analysis shows the spectral efficiency degradation due to the pilot based strategy is negligible.

On the Performance of Blind Chip Rate Estimation in Multi-Rate CDMA Transmissions Using Multi-Rate Sampling in Slow Flat Fading Channels

This paper considers blind chip rate estimation of DS-SS signals in multi-rate and multi-user DS-CDMA systems over channels having slow flat Rayleigh fading plus additive white Gaussian noise. Channel impulse response is estimated by a subspace method, and then the chip rate of each signal is estimated using zero crossing of estimated differential channel impulse response. For chip rate estimation of each user, an algorithm which uses weighted zero-crossing ratio is proposed. Maximum value of the weighted zero crossing ratio takes place in the Nyquist rate sampling frequency, which equals to the twice of the chip rate. Furthermore, bit time of each user is estimated using fluctuations of autocorrelation estimators. Since code length of each user can be obtained using bit time and chip time ratio. Fading channels reduce reliability factor of the proposed algo-rithm. To overcome this problem, a receiver with multiple antennas is proposed, and the reliability factor of the proposed algorithm is analyzed over both spatially correlated and independent fading channels.