Sami Muhaidat

Performance Analysis of Relay Selection With Feedback Delay and Channel Estimation Errors

In this letter, we investigate the effect of feedback delay and channel estimation errors in a decode-and-forward (DF) cooperative network with relay selection. In particular, we consider a multirelay cooperative scenario, where the best relay is selected from a subset of relays that are able to decode the source information correctly. In the selection scenario, the destination terminal estimates the relay-to-destination (R → D) channel state information (CSI) and sends the index of the best relay to the relay terminals via a delayed feedback link. We investigate the performance of the considered scenario in terms of average symbol error rate (ASER) and asymptotic diversity order. Simulation results are presented to corroborate the analytical results.

Relay Selection in Dual-Hop Vehicular Networks

In this letter, we investigate cooperative diversity with relay selection over cascaded Rayleigh fading channels. In particular, we analyze the performance of a relay selection scheme for cooperative vehicular networks with the decode-and-forward (DF) protocol. Only the “best” relay, which satisfies an index of merit, is selected. We ignore the direct transmission between the source (S) and its destination (D), and assume that the destination has perfect knowledge of the S → R and R → D channel gains. We study the performance of the underlying scheme in terms of outage probability and investigate its achievable diversity order.

RF-powered cognitive radio networks: technical challenges and limitations

The increasing demand for spectral- and energy-efficient communication networks has spurred great interest in energy harvesting cognitive radio networks. Such a revolutionary technology represents a paradigm shift in the development of wireless networks, as it can simultaneously enable the efficient use of the available spectrum and the exploitation of RF energy in order to reduce reliance on traditional energy sources. This is mainly triggered by the recent advancements in microelectronics that puts forward RF energy harvesting as a plausible technique in the near future. On the other hand, it has been suggested that the operation of a network relying on harvested energy needs to be redesigned to allow the network to reliably function in the long term. To this end, the aim of this survey article is to provide a comprehensive overview of recent development and the challenges regarding the operation of CRNs powered by RF energy. In addition, the potential open issues that might be considered for future research are also discussed in this article.

Effect of Feedback Delay on the Performance of Cooperative Networks with Relay Selection

In this paper, we analyze the effect of feedback delay and channel estimation errors on the performance of a decode-and-forward (DF) cooperative transmission scenario with relay selection. In our relay selection scheme, only one relay with the best relay-to-destination (R → D) channel quality is selected among the set of relays that decode the source information correctly. Specifically, the destination terminal first estimates the channel state information (CSI) of all active R → D links and then sends the index of the best relay to the relay terminals via a delayed feedback link. Due to the time varying nature of the fading channels, selection is performed based on the old version of the channel estimate. Closed-form expressions for the outage probability, average capacity and average symbol error rate (ASER) are derived. Through asymptotic diversity order analysis, we show that the presence of feedback delay reduces the asymptotic diversity order to one, while the effect of channel estimation errors reduces it to zero. Finally, simulation results are presented to corroborate the analytical results.

Opportunistic Spectrum Access in Cognitive Radio Networks Under Imperfect Spectrum Sensing

In this paper, we investigate the effect of imperfect sensing on the performance of opportunistic spectrum access (OSA) in cognitive radio (CR) networks. We consider a system modeled as a continuous-time Markov chain (CTMC), and then evaluate its performance in terms of the probabilities of users being blocked or dropped. Our results demonstrate that the performance of the underlying system significantly degrades when imperfect sensing is considered; thus, there is a pressing need for a reliable spectrum sensing scheme to improve the overall quality of service in practical scenarios. A simulation study is presented to corroborate the analytical results and to demonstrate the performance of OSA under imperfect sensing conditions.

Data Randomization and Cluster-Based Partitioning for Botnet Intrusion Detection

Botnets, which consist of remotely controlled compromised machines called bots, provide a distributed platform for several threats against cyber world entities and enterprises. Intrusion detection system (IDS) provides an efficient countermeasure against botnets. It continually monitors and analyzes network traffic for potential vulnerabilities and possible existence of active attacks. A payload-inspection-based IDS (PI-IDS) identifies active intrusion attempts by inspecting transmission control protocol and user datagram protocol packets payload and comparing it with previously seen attacks signatures. However, the PI-IDS abilities to detect intrusions might be incapacitated by packet encryption. Traffic-based IDS (T-IDS) alleviates the shortcomings of PI-IDS, as it does not inspect packet payload; however, it analyzes packet header to identify intrusions. As the networks traffic grows rapidly, not only the detection-rate is critical, but also the efficiency and the scalability of IDS become more significant. In this paper, we propose a state-of-the-art T-IDS built on a novel randomized data partitioned learning model (RDPLM), relying on a compact network feature set and feature selection techniques, simplified subspacing and a multiple randomized meta-learning technique. The proposed model has achieved 99.984% accuracy and 21.38 s training time on a well-known benchmark botnet dataset. Experiment results demonstrate that the proposed methodology outperforms other well-known machine-learning models used in the same detection task, namely, sequential minimal optimization, deep neural network, C4.5, reduced error pruning tree, and randomTree.

Relay Selection Strategies for Single-Carrier Frequency-Domain Equalization Multi-Relay Cooperative Networks

In this paper, we investigate several relay selection strategies for cooperative Single-Carrier Frequency-Domain Equalization (SC-FDE) with the amplify-and-forward protocol. We consider both maximum likelihood (ML)-SC-FDE and minimum mean square error (MMSE)-SC-FDE receivers. We provide a novel pairwise error probability (PEP)-based selection criterion (SHARM) for frequency selective channels. We further present several selection strategies for cooperative (C) MMSE-SC-FDE receivers, which are motivated by minimizing the instantaneous error rate. These are, norm-based relay selection (NBRS), instantaneous mutual information-based relay selection (CBRS), singular value based relay selection (SVRS), and equalizer output signal quality-based relay selection (EQRS) strategies. We further propose a novel relay selection strategy, selective-to-flat fading relay selection (SFRS), in which from the effective frequency selective source-relay-destination channel link associated with the selected relay, only the channel tab with highest power is passed to the destination terminal. Additionally, to tackle the multiple relay selection problem considering generic mobile scenarios with moderately fast fading channels, in order to select the near best relay subset within the minimum processing time, we apply estimation of distribution algorithm (EDA) and formulate a modified EDA for the relay selection problem. Our results show promising performance of EDA with comparable computational complexity.

A new mathematical analysis of the probability of detection in cognitive radio over fading channels

Cognitive radio (CR) enriches wireless technology systems by harnessing spectrum white spaces. Such systems require continuous and reliable sensing to provide high-quality service to their users and to minimize the interference they may cause to legacy networks. As the simplicity of implementation of energy detectors and their incoherent requirements make them an ideal candidate for this type of application, this work provides a further mathematical analysis to the probability of detection over different fading channels. We derive a tight closed-form expression for the probability of detection over Nakagami channels. In addition, we introduce an accurate recursive algorithm to compute the probability of detection for an odd degree of freedom over additive white Gaussian noise channels, which has been overlooked in the literature so far. Finally, we present the simulation results which concur with the numerical results and which are also a perfect match with the mathematical expressions derived.

A Novel Receiver Design for Single-Carrier Frequency Domain Equalization in Broadband Wireless Networks with Amplify-and-Forward Relaying

In this paper, we propose an efficient receiver design for single carrier frequency-domain equalization (SC-FDE) for relay-assisted transmission scenario over frequency selective channels. Building upon our earlier work, we propose a novel minimum mean square error (MMSE)-based receiver design tailored to broadband cooperative networks. We show that, by incorporating linear processing techniques, our MMSE-based receiver is able to collect full antenna and multipath diversity gains, while maintaining low complexity implementation. Specifically, under the assumption of perfect power control and high signal-to-noise ratio (SNR) for the underlying links and assuming either of source-to-relay (S → R) or relay-to-destination (R → D) links to be frequency selective Rician fading, our performance analysis demonstrates that the proposed receiver is able to achieve a maximum diversity order of min (LSR,LRD) + LSD + 2, where LSR, LRD, and LSD are the channel memory lengths for S → R, R → D, and source-to-destination (S → D) links, respectively. Simulation results demonstrate that our proposed receiver outperforms the conventional cooperative MMSE-SC-FDE receiver by performing close to the matched filter bound (MFB).

On the Performance of Pilot Symbol Assisted Modulation for Cooperative Systems with Imperfect Channel Estimation

In this paper, we analyze the impact of imperfect channel estimation on the performance of pilot symbol assisted modulation (PSAM) used in a relay communication system with distributed space time block code (STBC) and amplify-and-forward protocol. We derive correlation coefficients between the channel coefficients and their estimates when the relay-to-destination link is either non-fading or fading, in terms of Doppler frequency, number of pilot symbols and SNR. This enables us to choose the optimum number of pilot symbols to compensate for the estimation error when the fading and Doppler effects are severe. Our performance analysis demonstrates that the presence of fading in the relay-to-destination link manifests itself by introducing additional Doppler frequency terms. Furthermore, we derive a tight lower bound for the bit error rate (BER) of BPSK modulation with channel estimation errors in terms of cross correlation coeffcients and the number of pilot symbols. Simulation results are also presented to validate our analytical results.