We take a fresh look at the non-coherent communication scenario in which the coherence time of the channel spans one time slot. We show that, in agreement with established information-theoretic results, the symbol error rate (SER) achieved with scalar signalling constellations saturates beyond a rate-dependent signal-to-noise ratio. More interestingly, we show that the SER saturation value is monotonically decreasing with the number of receive antennas, establishing that practical efficient communication over this, traditionally unpopular, channel is possible. In addition to additive Gaussian noise, we assume that the received signal is also contaminated by an additive non-Gaussian jamming signal. The impact of such jamming is considered under various channel conditions and detection techniques, which include optimal maximum likelihood and detection based on Gaussian approximations. Analytical findings are supported by numerical simulations.

We propose a low-complexity downlink channel covariance matrix estimation for massive multiple-input multiple-output systems in which the base station (BS) is equipped with a uniform rectangular antenna array (URA). This scheme can be expressed in the form of an affine transformation which depends only on the uplink and downlink carrier frequencies, and the BS array configurations. An upper bound on the estimation error is derived, which shows that the accuracy of the proposed scheme increases with the number of URA antennas and the compactness and differentiability class of the periodic extension of a non-linearly transformed version of the angular power spread. The performance superiority of the proposed scheme over its existing counterparts is confirmed through simulations.

We consider a scenario in which a transmitter sends complex multidimensional symbols to a receiver in the presence of a proactive continuous jammer emitting a zero-mean complex Gaussian signal over an unknown complex Gaussian channel. The complex Gaussian signal transmitted over the unknown complex Gaussian channel induces a non-Gaussian signal at the receiver. We develop the optimal maximum likelihood (ML) detector for cases in which the receiver has full channel state information (CSI), full channel distribution information (CDI), or partial CDI about the transmitter channel. The jammer CDI is either partially or fully available at the receiver. We identify cases in which the non-Gaussian signals resulting from the jammer's transmission can be approximated by Gaussian signals to reduce the computational cost without compromising optimality of detection. Furthermore, we identify cases in which the Gaussian approximation ML detector is not equivalent to the exact ML detector. In these cases, we show that the advantage of the exact ML detector over the Gaussian approximation one can be significant.

Mobile Ad hoc networks (MANETs) are gaining increased interest as the technology that potentially will make mobile computing a tangible reality. The self-control, selforganization, topology dynamism, and bandwidth limitation of the wireless communication channel make MANETs' implementation a challenging task. The Connected Dominating Set (CDS), a.k.a. virtual backbone or spine, has been proposed to facilitate routing, broadcasting, and establishing a dynamic infrastructure for distributed location databases in MANETs. Minimizing the CDS cardinality simplifies the MANET's abstracted topology and allows for using shorter routes. Since finding the minimum size CDS (MCDS) is NP-complete, approximation algorithms and heuristics are used to tackle this problem. It has been reported that localized CDS creation algorithms run fast and generate light signaling overhead; examples of these algorithms are Wu and Li algorithm and its Stojmenovic variant, the MPR algorithm, and Alzoubi algorithm. Some theoretical performance analysis of these algorithms is presented in the literature; however, this analysis has not been validated across any physical or at least simulation-based measures. Moreover, the presented theoretical performance analysis has overlooked the cost of maintaining the CDS in the presence of topology changes. In this paper, a simulation-based evaluation of the performance of these algorithms is conducted using the ns-2 network simulator. Moreover, the effects of mobility rates and network size on the performance of each algorithm is investigated.

Mobile ad hoc networks (MANETs) are gaining increased interest as the technology that potentially will make the nowadays illusion of mobile computing a tangible reality. vehicular ad-hoc networks (VANETs) are the special kind of MANETs that aims at providing communications among vehicles on the roads. The connected dominating set (CDS), a.k.a. virtual backbone or spine, has been proposed to facilitate routing, broadcasting, and establishing a dynamic infrastructure for distributed location databases in VANETs. Minimizing the CDS cardinality simplifies the VANETpsilas abstracted topology and allows for using shorter routes. Since, it is NP-complete to find the minimum size CDS (MCDS), approximation algorithms and heuristics are used to tackle this problem. It has been reported that localized CDS creation algorithms run fast and generate light signaling overhead. Some theoretical performance analysis of these algorithms is presented in the literature; however, this analysis has not been validated across any physical or at least simulation-based measures. Moreover, the cost of maintaining the CDS in the presence of topology changes is an important cost that is overlooked most of the time. In this paper, a simulation-based comparison between the performance of these algorithms is conducted using the ns2 network simulator. Moreover, the effect of mobility rate and network size on the performance of each algorithm is investigated.