Timing jitter in OFDM systems results in non-ideal sampling and pulse-shaped transmission times and thus, is an important limiting factor for practical OFDM systems. In this paper, the effect of sampling jitter on the spectrum of a transmitted OFDM signal is considered. This effect in particular can lead to a significant degradation in the performance of spectral shaping techniques in OFDM, e.g., out-of-band radiation reduction techniques, that are mostly based on the assumption of ideal sampling times and accurate synchronization. In this work, we first evaluate the effect of random sampling time jitter on the performance of the active interference cancellation (AIC) technique, a well-known out-of-band radiation reduction technique for OFDM. Then, using a minimax approach, we propose a robust scheme that takes the jitter effect into consideration and therefore, makes the sidelobe suppression technique robust against worst-case random jitter. Numerical simulations show a performance improvement of almost 3 dB in interference reduction for our proposed robust scheme in the presence of timing jitter.

We study the transmission of two correlated and memoryless sources (U1, U2) over several multiuser phase asynchronous channels. Namely, we consider a multiple access relay channel (MARC) with causal, and a MARC with non-causal unidirectional cooperation between encoders, referred to as phase-incoherent causal (respectively, non-causal) cognitive MARCs. We also consider phase-incoherent interference channel models with and without relay, in the same context. In all cases, the input signals are assumed to undergo non-ergodic phase shifts, which are unknown to the transmitters and known to the receivers as a realistic assumption. Both necessary and sufficient conditions in order to reliably send the correlated sources to the destinations are derived. In particular, for all of the channel models, by using a key lemma, we first derive an outer bound for reliable communication. Then, using separate source and channel coding and under specific gain conditions, we establish the same region as the inner bound. We thus conclude that without the knowledge of the phase shifts at transmitters, and under specific gain conditions, separation is optimal.

We investigate the problem of continuous-time energy harvesting in communication systems operating over fading wireless channels. We model the fading as a finite-state continuous-time Markov process, and the battery dynamics as a storage dam process with reflecting boundary conditions. We describe a set of necessary conditions for the ergodicity of the dam process. Followed by these conditions, we establish an upper bound on the ergodic channel throughput. We further determine some structure for good transmission power policies based on a throughput maximization problem. Specifically, using calculus of variations techniques, we derive Euler-Lagrange equations as a necessary condition for optimal power policies. In the case of a Markov channel with two channel states (i.e. Gilbert-Elliot channel), we characterize power policies by solving these equations numerically.

The problem of cross-band interference in single-antenna and multi-antenna OFDM cognitive transmitters is considered. Cross-band interference, which is caused by large OFDM signal sidelobes, is a major drawback of OFDM, especially in cognitive radio applications where it is crucial to protect primary licensed users from the secondary user's interference. In this paper, we propose a novel low complexity technique, referred to as a phase adjustment technique, to tackle this problem in single-antenna and multi-antenna OFDM cognitive transmitters. In this technique, the phase of each OFDM symbol is adjusted in an attempt to minimize the interference caused by the secondary user to the primary. Unlike prior methods, this technique does not decrease data throughput and has no impact on the bit-error-rate and peak-to-average power ratio of the OFDM symbols. Furthermore, to calculate the adjustment phases, three heuristics, one of which is very low complexity and achieves near optimal performance in numerical simulations, are also proposed. In addition, the performance of the proposed technique is evaluated analytically in some special cases in single and multi-antenna cognitive transmitters, and is verified by numerical simulations.

Active interference cancellation (AIC) is known to be a very effective technique for reducing the interference of OFDM sidelobes to primary licensed users in cognitive OFDM systems. However, AIC has some shortcomings such as high computational complexity and spectrum overshoot on the cancellation subcarriers. Spectrum overshoot is mainly caused due to unconstrained or unbalanced power allocation to the cancellation tones used in AIC. In this paper, we propose an improved AIC technique in which the problem of spectrum overshoot is tackled. We show that by a modification to the solution of the optimization problem involved in AIC, we can obtain a trade-off between the amount of spectrum overshoot and sidelobe suppression without increasing the system complexity. In particular, spectrum overshoot can be completely eliminated. Furthermore, simulations prove that with this modification, the peak spectral interference at the primary band is less than that of the AIC technique with a single power constraint.

In this paper, we propose a new technique to reduce the interference caused by high OFDM sidelobes to the primary users in MIMO-OFDM cognitive systems. The proposed technique does not affect the rate of the system and has very low complexity. We also analyze the performance of the technique for a class of flat fading channels and show that the analytical results agree with simulations. Furthermore, for frequency selective fading channels, numerical results show that the performance is almost the same as that obtained analytically for flat fading channels.

Cognitive radio is a promising approach for efficient utilization of radio spectrum. Due to its high spectral efficiency and flexibility, OFDM is considered as a good signaling scheme for cognitive radios. In this paper, we investigate the problem of cross-band interference minimization in OFDM-based cognitive systems. Cross-band interference is mainly caused by high OFDM sidelobes. In the first part of our work, we propose a framework to study the trade-off between two recently proposed techniques, adaptive symbol transition which is performed in the time domain, and active interference cancellation which is performed in the frequency domain. We use the trade-off study results to maximize the useful data rate for a desired level of interference. Simulation results show that the best trade-off depends on the configuration of spectral opportunities. In the second part, a new method for interference reduction in multiple-antenna cognitive systems is developed. We show that with knowledge of the channel, the secondary transmitted sequences can be jointly optimized over multiple antennas such that the interference at the primary receiver location is better minimized. Computer simulations demonstrate an improvement of almost 10 dB compared to separate-antenna optimization.