Energy-aware power allocation in cooperative communication systems depends on the availability of channel state information (CSI), which is often imperfect in practice. This paper proposes energy-aware, optimal power allocation schemes for an amplify-and-forward cooperative communication system in the presence of imperfect CSI, to i) minimize the total transmit power; ii) maximize the end-to-end signal-to-noise ratio (SNR). Energy awareness is incorporated in the schemes either by avoiding over-provisioning of quality-of-service (QoS) or, by preventing unsuccessful transmissions, depending on the application. In both the schemes, the source and relay nodes share a fixed total transmit power budget, and transmission is allowed only if the minimum required end-to-end SNR can be achieved with the available power budget. Closed-form expressions for the source and relay optimal transmit powers are derived for both these schemes. Performance of the systems under the proposed schemes are investigated through simulations.

The paper presents design of a linear precoder for orthogonal space-time block coded orthogonal frequency division multiplexing (OFDM)-based multiple-input multiple-output (MIMO) antenna cognitive radio (CR) when operating in correlated Rayleigh fading channels. Unlike previous studies on precoder design for CR, this proposed linear precoder is capable of handling both transmit and receive correlation in a multi-carrier based CR system. The linear precoder is designed to minimize an upper bound on the average pairwise error probability, constrained to a set of per subcarrier transmit power constraints at the CR transmitter and a set of interference power thresholds at primary user receivers. The CR transmitter exploits the knowledge of transmit and receive correlation matrices while designing the precoder. It is shown that the linear precoder design problem is convex with these constraints, and convex optimization techniques are exploited to derive an efficient algorithm to obtain the optimal precoder matrices. Computer simulations are performed to investigate the performance of the proposed linear precoder in a CR system.

This paper presents a blind parameter estimation algorithm for orthogonal frequency division multiplexing (OFDM) signal affected by a time-dispersive channel, timing offset, carrier frequency offset and additive Gaussian noise. Unlike the previous studies, this paper presents the second-order cyclostationarity of OFDM signal considering the effect of time-dispersive channel. The cyclostationarity properties of received OFDM signal in time-dispersive channel is exploited to estimate the OFDM parameters. These parameters includes OFDM symbol period, useful symbol period, cyclic prefix factor, number of subcarriers and carrier frequency offset. Simulations are performed to investigate the performance of OFDM parameter estimation algorithm in diverse channel conditions.

This paper presents a lower-bound on the ergodic sum capacity of single-input single-output (SISO) opportunistic spectrum sharing multiple access channel (MAC) in Rayleigh fading channels with imperfect channel estimates. Unlike the previous studies, this paper considerers the channel estimation errors for both sets of SISO channels between the secondary user (SU) transmitters and the SU receiver and between the SU transmitters and the primary user receivers. By considering these channel estimation errors, an optimal power allocation policy for each SU transmitter is derived to achieve a lower-bound of the ergodic sum capacity of opportunistic spectrum sharing MAC, subject to a set of SUs transmit power constraints and a set of interference power constraints at each PU receiver. Furthermore, convex optimization techniques are exploited to derive an efficient algorithm to obtain the optimal power allocation for each SU transmitter. Numerical results are presented to illustrate the influences of the channel estimation errors on the ergodic sum capacity.

Previous studies on the cyclostationarity aspect of orthogonal frequency division multiplexing (OFDM) and single carrier linearly digitally modulated (SCLD) signals assumed simplified signal and channel models or considered only second-order cyclostationarity. This paper presents new results concerning the cyclostationarity of these signals under more general conditions, including time dispersive channels, additive Gaussian noise, and carrier phase, frequency, and timing offsets. Analytical closed-form expressions are derived for time- and frequency-domain parameters of the cyclostationarity of OFDM and SCLD signals. In addition, a condition to eliminate aliasing in the cycle and spectral frequency domains is derived. Based on these results, an algorithm is developed for recognizing OFDM versus SCLD signals. This algorithm obviates the need for commonly required signal preprocessing tasks, such as signal and noise power estimation and the recovery of symbol timing and carrier information.

We propose a power loading scheme for multi- carrier cognitive radio (CR) network employing multiple-input multiple-output (MIMO) antennas. We allocate power to different transmitting antennas within different subcarriers maximizing the total system capacity while maintaining the interference to primary user within a prescribed limit. We formulate this as a convex optimization problem and use numerical methods to solve for optimal power allocation. We also compare the performance of power loading scheme proposed in this paper to conventional uniform power loading scheme with and without interference constraint. Simulation results show that the capacity of MIMO CR using our proposed power loading scheme increases significantly with increase in interference temperature limit and the number of transmit antennas. However, we also confirm that if we include interference constraint in the conventional uniform power loading schemes, the capacity does not increase proportionally with increase in number of transmit antennas as those schemes do not take the instantaneous channel condition between cognitive user transmitter and primary user receiver into account.

In this paper, we introduce a spectrum holes detection approach, which combines blind modulation classification, angle of arrival estimation and number of sources detection. We perform eigenspace analysis to determine the number of sources, and estimate their angles of arrival. In addition, we classify detected sources as primary or secondary users with their distinct second-order/one-conjugate cyclostationarity features. Extensive simulations carried out indicate that the proposed system identifies and locates individual sources correctly, even at -4 dB SNR.

This paper studies the nth-order cyclostationarity of orthogonal frequency division multiplexing (OFDM) and single carrier linearly digitally modulated (SCLD) signals affected by a time dispersive channel, additive Gaussian noise, carrier phase, and frequency and timing offsets. The analytical closed-form expressions for the nth-order cyclic cumulants (CCs) and cycle frequencies (CFs) of OFDM and SCLD signals are derived. Furthermore, a second-order CC-based algorithm is developed to recognize OFDM against SCLD signals under the aforementioned conditions. This algorithm obviates the need for signal preprocessing tasks, such as symbol timing estimation, carrier and waveform recovery, and signal and noise power estimation. Simulation experiments confirm the theoretical analysis.

The paper studies the cyclostationarity of an orthogonal frequency division multiplexing (OFDM) with a view to recognizing OFDM against single carrier linear digital (SCLD) modulations. The analytical expressions for the nth-order cyclic cumulants (CCs) and cycle frequencies of an OFDM signal embedded in additive white Gaussian noise and subject to phase, frequency and timing offsets are derived An algorithm based on a second-order CC is proposed to recognize OFDM against SCLD modulations. The recognition algorithm of the authors obviates the need for preprocessing tasks, such as symbol timing estimation, carrier and waveform recovery, and signal and noise power estimation. The results of simulation experiments confirm the theoretical analysis.