The paper studies the problem of waveform design for a joint Radar-Communications (RadComms) system in an automotive setting characterized by a multitarget environment. The envisaged joint waveform allows exploitation of existing infrastructure to support additional functionalities. In this contribution, an automotive radar employing Phase Modulated Continuous Waveform (PMCW) is considered wherein, the transmission of communications bits is additionally facilitated. Particularly, the RadComms system is enabled by the transmission of Differential Phase Shift Keying (DPSK) communications symbols, each symbol modulated by the PMCW sequence. Further, the receiver processing includes demodulation of the communication symbols in addition to the extraction of the radar parameters — range, Angles of Arrival (AoA) and Doppler returns of the targets. In particular, FFT and subspace-based methods are proposed for estimating the radar parameters which are subsequently used in the demodulation of the communication symbols using diversity combining techniques. The performed study demonstrates the impact of the joint set-up on the two systems. It also highlights the effect of system parameters on the performance of receiver algorithms and the trade-off between the FFT and sub-spaced based processing.

This paper presents wireless sensor network unmanned aerial vehicle (WSN-UAV) system for military remote monitoring and surveillance. Large scale WSN is deployed in a battlefield or wide hostile region to collect information of interest and send it to a UAV. Collaborative beamforming (CB) is used to achieve the ground-to-air transmissions. An automatic dependent surveillance-broadcast (ADS-B) based multilateration is used to obtain the UAV location and tracking information. It is found that a minimum distance between the UAV and the WSN is required for proper operation of the CB due to the precision of the multilateration and the movement of the UAV.

A novel spectrum sensing approach based on distribution discontinuity estimation facilitated by change-point (CP) detection algorithm has been presented in this work. Specifically, a Markov Chain Monte Carlo (MCMC) based CP detection algorithm to estimate the variations in the distribution over the received signal is developed. Primary User (PU) activity, autonomous classification of modulation and detection of PU emulation attempts are detected using the CP- Maximum Likelihood Estimation (MLE) framework. Specifically, the CP based approach facilitates PU activity detection and initiates the MLE based mechanism to discern or reveal the underlying modulation scheme within the received signal. Thus, the proposed joint CP-MLE framework not only aims at detecting the discontinuity or the variations in the underlying distribution over the sensed signal, but also helps in attributing those variations to distinct modulation schemes, in an effort to identify PU emulation attempts. This CP- MLE framework has been extensively validated using the Universal Software Radio Peripheral (USRP) devices for various types of scenarios involving real-time modulation classification and identification of PU emulation type attacks.

Data rate and energy efficiency decrement caused by the transmission of reference and data carrier signals in equal portions constitute the major drawback of differential chaos shift keying (DCSK) systems. To overcome this dominant drawback, a short reference DCSK system (SR-DCSK) is proposed. In SRDCSK, the number of chaotic samples that constitute the reference signal is shortened to R such that it occupies less than half of the bit duration. To build the transmitted data signal, P concatenated replicas of R are used to spread the data. This operation increases data rate and enhances energy efficiency without imposing extra complexity onto the system structure. The receiver uses its knowledge of the integers R and P to recover the data. The proposed system is analytically studied and the enhanced data rate and bit energy saving percentages are computed. Furthermore, theoretical performance for AWGN and multipath fading channels are derived and validated via simulation. In addition, optimising the length of the reference signal R is exposed to detailed discussion and analysis. Finally, the application of the proposed short reference technique to the majority of transmit reference systems such as DCSK, multicarrier DCSK, and quadratic chaos shift keying enhances the overall performance of this class of chaotic modulations and is, therefore, promising.

A cognitive detect and avoid radar system based on chaotic UWB-MIMO waveform design to enable autonomous UAV navigation is presented. A Dirichlet-process-mixture-model (DPMM)-based Bayesian clustering approach to discriminate extended targets and a change-point (CP) detection algorithm are applied for the autonomous tracking and identification of potential collision threats. A DPMM-based clustering mechanism does not rely upon any a priori target scene assumptions and facilitates online multivariate data clustering/classification for an arbitrary number of targets. Furthermore, this radar system utilizes a cognitive mechanism to select efficient chaotic waveforms to facilitate enhanced target detection and discrimination. We formulate the CP mechanism for the online tracking of target trajectories, which present a collision threat to the UAV navigation; thus, we supplement the conventional Kalman-filter-based tracking. Simulation results demonstrate a significant performance improvement for the DPMM-CP-assisted detection as compared with direct generalized likelihood-ratio-based detection. Specifically, we observe a 4-dB performance gain in target detection over conventional fixed UWB waveforms and superior collision avoidance capability offered by the joint DPMM-CP mechanism.

The performance analysis of a relaying system implementing modulation diversity is investigated in this work. Our relaying system is quite novel, since, we assume that the relay always transmits during the relaying phase, i.e., is never silent. Whereas in the other related works assume that the relay first decodes its received signal and upon a successful decoding, transmits to the destination, i.e., the relay is silent upon an unsuccessful decoding. Modulation diversity creates diversity by transforming the angle of a classical modulation to create signal points with distinct components, followed by subsequent interleaving over the components. Assuming transmission over independent Rayleigh fading channels and maximum likelihood detection on the reordered signals at the receiver, the analysis starts with finding the probability density function of the end-to-end signal-to-noise (SNR) ratio. Then, a tight upper-bound expression for the error probability is obtained. Following that, we achieve the exact outage probability of the relaying system under-study. Then, exact and upper-bound expressions for the system capacity are presented. Finally, numerical results and comparisons with Monte Carlo simulations are presented.

To realize opportunistic spectrum access, spectrum sensing is applied to detect the presence of spectrum holes. If secondary radios (SRs) randomly or sequentially sense the channels until a spectrum hole is detected, significant amount of the scarce spectrum resource will be wasted, since SRs transmit only after a decision has been made. On the other hand, with the use of an intelligent predictive method, SRs can learn from the past activities of each channel to predict the next channel state. By prioritizing the order in which channels are sensed according to the channels availability likelihoods, the probability that an SR gets a channel upon its first attempt significantly increases, and thus reduces the possible waste. This paper introduces a learning-based hidden Markov model (HMM) to predict the channel activities. Simulation results show that the proposed HMM can predict the channel activities with high accuracy after sufficient training. Our algorithm predicts the availability of the channels by only making use of the current state of the spectrum. Furthermore, by incorporating the outcome of the actual channel sense, our algorithm is able to make self-regulation before next decision, so that errors will not propagate.

In this paper results of mathematical analysis supported by simulation are used to find a theoretical limit for cell size reduction in mobile communication systems. Information capacity approach is used for the analysis. Attention is given to the active co-channel interfering cells. Because at microwave frequencies beyond 2 GHz, co-channel interfering cells beyond the first tier becomes dominant as the cell size reduces. We show that when the cell size limit is reached any further reduction in cell size will not increase the information capacity of the cellular network. A formula is derived for calculating the number of co-channel cells in subsequent tiers.

In this paper we demonstrate the application of Hidden Markov Models (HMM) for localization and tracking in ultra wide band (UWB) radar networks. To improve localization, a Voronoi region based approach is utilized to form a HMM for detection and tracking of mobile target. The observations used for the HMM localization are obtained from the power delay profile of the received signals. In UWB systems the use of entire power delay profiles instead of the total power only, allows to reach higher localization accuracy. This is due to the power delay profile being a measure of the power as well as the time of arrival. Simulation results suggest a performance gain of 7dB over the maximum likelihood estimation for localization in presence of path loss at intermediate values of signal to noise ratio (SNR).

In this paper, the performance of vector precoding in multiple input multiple output broadcast channels (MIMO BC) is investigated and compared with other channel decomposition techniques utilized for implementing zero forcing (ZF) preceding. It is a known result that ZF precoding requires pseudo inversion of the channel matrix, where this operation is only optimum when the transmitter power is unconstrained. The problem when the transmitter is subject to average or maximum power constraints is well known, where results published have indicated that ZF precoding approaches the maximum capacity bound if the dimensionality of the system is greater than the number of transmitter antennas. A vector precoding technique for MIMO BC channels is investigated in this paper where pseudo inversion is circumvented by employing joint co-operation between transmitter and receiver for all users. This technique adopts a time scheduling approach to service the users which facilitates decentralized multi-user detection at the receiver. This approach yields an improvement to the bit error rate probability by approximately an order of magnitude as compared to the ZF approach utilizing other channel decomposition techniques. The scheme also enables an increase in the capacity of the MIMO BC, with less computational complexity as compared to the techniques employing Moore-Penrose pseudo inverse.