We consider video transmission over a mobile cognitive radio (CR) system operating in a hostile environment where an intelligent adversary tries to disrupt communications. We investigate the optimal strategy for spoofing, desynchronizing, and jamming a cluster-based CR network with a Gaussian noise signal over a slow Rayleigh fading channel. The adversary can limit access for secondary users (SUs) by either transmitting a spoofing signal in the sensing interval, or a desynchronizing signal in the code acquisition interval. By jamming the network during the transmission interval, the adversary can reduce the rate of successful transmission. We show how the adversary can optimally allocate its energy across subcarriers during sensing, code acquisition, and transmission intervals. We determine a worst-case optimal energy allocation for spoofing, desynchronizing, and jamming, which gives an upper bound to the received video distortion of SUs. We also propose cross-layer resource allocation algorithms and evaluate their performance under disruptive attacks.

Filter Bank Multicarrier (FBMC) systems has drawn interest as an alternative to orthogonal frequency division multiplexing (OFDM), as FBMC offers higher spectral efficiency and less susceptibility to synchronization errors. One drawback in FBMC systems is the presence of inter-carrier-interference (ICI) and inter-symbol-interference (ISI), which degrades the system performance when operating under fading channels. In this work we consider the bit error rate (BER) performance of a multiple input multiple output (MIMO) FBMC system. We evaluate the performance of linear and non-linear transceiver processing techniques, which attempt to mitigate the effect of ICI and ISI in MIMO FBMC systems. Simulation results are presented to evaluate and compare the transceiver processing techniques discussed.

We examine the performance of a cognitive radio system in a hostile environment where an intelligent adversary tries to disrupt communications by minimizing the system throughput. We investigate the optimal strategy for spoofing and jamming a cognitive radio network with a Gaussian noise signal over a Rayleigh fading channel. We analyze a cluster-based network of secondary users (SUs). The adversary may attack during the sensing interval to limit access for SUs by transmitting a spoofing signal. By jamming the network during the transmission interval, the adversary may reduce the rate of successful transmission. We present how the adversary can optimally allocate power across subcarriers during sensing and transmission intervals with knowledge of the system, using a simple optimization approach specific to this problem. We determine a worst-case optimal energy allocation for spoofing and jamming, which gives a lower bound to the overall information throughput of SUs under attack.

We derive simple uniform approximations (UAs) for the bit error rate (BER), the symbol error rate (SER), and the outage of wireless digital communication systems impaired by fading, noise, and interference. The striking feature of the UAs is their accuracy over the whole range of signal-to-noise ratio (SNR) values, whereas the existing high-SNR approximations break down as the SNR decreases. The UAs require slightly more information than that for high-SNR expressions. The additional information required in the case of error probabilities is the several moments (fractional) of channel gain, which can be extracted readily from the PDF, MGF or the Mellin transform of the PDF. The computation of the UA is simple and requires only the solution of a set of linear equations. Additionally, we also generalize the previous asymptotic results of Wang and Giannakis. The unified asymptotic results of the average of an arbitrary performance measure are thus derived. Various BER and SER expressions then become special cases of this unified approach.

This paper investigates the impact of using outdated channel estimates for relay selection and signal amplification on the performance of amplify-and-forward (AF) relays under partial relay selection (PRS) and opportunistic relay selection (ORS). In practice, outdated channel state information (CSI) can occur due to feedback or scheduling delay. Both variable gain (VG) AF and fixed gain AF schemes are considered. Outage probability, the average bit error rate (BER) and simplified high signal-to-noise ratio approximations are derived. The effect of parameters such as the number of relays, the rank of chosen relay, and the correlation between the delayed and current channel state information are analyzed. Outdated CSI for computing relay gains in PRS causes about 2 dB loss. In ORS, a 3% reduction in correlation causes up to an order of magnitude increase in the outage probability.

This paper evaluates the impact of using outdated channel estimates due to feedback delay for relay selection and signal amplification on the performance of partial relay selection with amplify-and-forward (AF) relays. Both variable and fixed gain AF schemes are considered. Expressions for the system's outage probability and the average bit error rate, and their high signal-to-noise ratio (SNR) approximations are derived. The effect of parameters such as the rank of relay chosen, SNR imbalance and the correlation between the delayed and current channel state information are studied and verified through simulations.

This paper evaluates the impact of using outdated channel estimates in a multiuser Amplify-and-Forward (AF) relay network, under Nakagami-m fading. Both variable gain AF and fixed gain AF schemes are considered. Expressions for the system's outage probability and the average bit error rate (BER) are derived. Since the expressions are barely tractable, we also present approximations for the high signal-to-noise ratio (SNR) regime. By doing so we characterize the impact of network parameters such as the number of relays, correlation between the delayed and current channel state information, chosen user rank and SNR imbalance on the performance degradation.

The performance of a cooperative network with Cooperative Maximal Ratio Combining (C-MRC) is analyzed. To this end, we propose a heuristic approximation to the total received SNR (signal-to-noise ratio) at the destination. The approximation is not only an accurate representation of the received SNR, but also amenable to performance analysis. We then derive the probability density function (PDF) of the approximate SNR. The PDF is used to derive expressions of the parameters required for the performance analysis of rate adaptive transmission, based on the use of a discrete set of modes of square M-ary quadrature amplitude modulation (QAM), with a cooperative network employing C-MRC. Analytical expressions for mode selection probability, the outage probability, the average spectral efficiency, and the average bit error rate are derived. Results show that performance of the system under C-MRC is comparable with other cooperative networks.

We analyze the impact of outdated channel state information due to feedback delay on the performance of amplify-and-forward relays with the$k$th worst partial relay selection scheme. In our analysis, new expressions for the system's outage probability and the average bit error rate are derived. The effects of the rank of the relay chosen, the average SNR imbalance, and the correlation between the delayed and current signal-to-noise ratio (SNR) on the system performance are investigated. Additionally, simple and accurate outage and average BER approximations are also derived to quantify the performance at high SNR. We also give simulation results to support the theoretical study.