Peak to average power ratio based spatial spectrum sensing for cognitive radio systems

The recent convergence of wireless standards for incorporation of spatial dimension in wireless systems has made spatial spectrum sensing based on Peak to Average Power Ratio (PAPR) of the received signal, a promising approach. This added dimension is principally exploited for stream multiplexing, user multiplexing and spatial diversity. Considering such a wireless environment for primary users, we propose an algorithm for spectrum sensing by secondary users which are also equipped with multiple antennas. The proposed spatial spectrum sensing algorithm is based on the PAPR of the spatially received signals. Simulation results show the improved performance once the information regarding spatial diversity of the primary users is incorporated in the proposed algorithm. Moreover, through simulations a better performance is achieved by using different diversity schemes and different parameters like sensing time and scanning interval

The electronically steerable parasitic array radiator antenna for wireless communications : signal processing and emerging techniques

Smart antenna technology is expected to play an important role in future wireless communication networks in order to use the spectrum efficiently, improve the quality of service, reduce the costs of establishing new wireless paradigms and reduce the energy consumption in wireless networks. Generally, smart antennas exploit multiple widely spaced active elements, which are connected to separate radio frequency (RF) chains. Therefore, they are only applicable to base stations (BSs) and access points, by contrast with modern compact wireless terminals with constraints on size, power and complexity. This dissertation considers an alternative smart antenna system the electronically steerable parasitic array radiator (ESPAR) which uses only a single RF chain, coupled with multiple parasitic elements. The ESPAR antenna is of significant interest because of its flexibility in beamforming by tuning a number of easy-to-implement reactance loads connected to parasitic elements; however, parasitic elements require no expensive RF circuits. This work concentrates on the study of the ESPAR antenna for compact transceivers in order to achieve some emerging techniques in wireless communications. The work begins by presenting the work principle and modeling of the ESPAR antenna and describes the reactance-domain signal processing that is suited to the single active antenna array, which are fundamental factors throughout this thesis. The major contribution in this chapter is the adaptive beamforming method based on the ESPAR antenna. In order to achieve fast convergent beamforming for the ESPAR antenna, a modified minimum variance distortionless response (MVDR) beamfomer is proposed. With reactance-domain signal processing, the ESPAR array obtains a correlation matrix of receive signals as the input to the MVDR optimization problem. To design a set of feasible reactance loads for a desired beampattern, the MVDR optimization problem is reformulated as a convex optimization problem constraining an optimized weight vector close to a feasible solution. Finally, the necessary reactance loads are optimized by iterating the convex problem and a simple projector. In addition, the generic algorithm-based beamforming method has also studied for the ESPAR antenna. Blind interference alignment (BIA) is a promising technique for providing an optimal degree of freedom in a multi-user, multiple-inputsingle-output broadcast channel, without the requirements of channel state information at the transmitters. Its key is antenna mode switching at the receive antenna. The ESPAR antenna is able to provide a practical solution to beampattern switching (one kind of antenna mode switching) for the implementation of BIA. In this chapter, three beamforming methods are proposed for providing the required number of beampatterns that are exploited across one super symbol for creating the channel fluctuation patterns seen by receivers. These manually created channel fluctuation patterns are jointly combined with the designed spacetime precoding in order to align the inter-user interference. Furthermore, the directional beampatterns designed in the ESPAR antenna are demonstrated to improve the performance of BIA by alleviating the noise amplification. The ESPAR antenna is studied as the solution to interference mitigation in small cell networks. Specifically, ESPARs analog beamforming presented in the previous chapter is exploited to suppress inter-cell interference for the system scenario, scheduling only one user to be served by each small BS at a single time. In addition, the ESPAR-based BIA is employed to mitigate both inter-cell and intracell interference for the system scenario, scheduling a small number of users to be simultaneously served by each small BS for a single time. In the cognitive radio (CR) paradigm, the ESPAR antenna is employed for spatial spectrum sensing in order to utilize the new angle dimension in the spectrum space besides the conventional frequency, time and space dimensions. The twostage spatial spectrum sensing method is proposed based on the ESPAR antenna being targeted at identifying white spectrum space, including the new angle dimension. At the first stage, the occupancy of a specific frequency band is detected by conventional spectrum-sensing methods, including energy detector and eigenvalue-based methods implemented with the switched-beam ESPAR antenna. With the presence of primary users, their directions are estimated at the second stage, by high-resolution angle-of-arrival (AoA) estimation algorithms. Specifically, the compressive sensing technology has been studied for AoA detection with the ESPAR antenna, which is demonstrated to provide high-resolution estimation results and even to outperform the reactance-domain multiple signal classification

Communication Subsystems for Emerging Wireless Technologies

The paper describes a multi-disciplinary design of modern communication systems. The design starts with the analysis of a system in order to define requirements on its individual components. The design exploits proper models of communication channels to adapt the systems to expected transmission conditions. Input filtering of signals both in the frequency domain and in the spatial domain is ensured by a properly designed antenna. Further signal processing (amplification and further filtering) is done by electronics circuits. Finally, signal processing techniques are applied to yield information about current properties of frequency spectrum and to distribute the transmission over free subcarrier channels

Multiband Spectrum Access: Great Promises for Future Cognitive Radio Networks

Cognitive radio has been widely considered as one of the prominent solutions to tackle the spectrum scarcity. While the majority of existing research has focused on single-band cognitive radio, multiband cognitive radio represents great promises towards implementing efficient cognitive networks compared to single-based networks. Multiband cognitive radio networks (MB-CRNs) are expected to significantly enhance the network's throughput and provide better channel maintenance by reducing handoff frequency. Nevertheless, the wideband front-end and the multiband spectrum access impose a number of challenges yet to overcome. This paper provides an in-depth analysis on the recent advancements in multiband spectrum sensing techniques, their limitations, and possible future directions to improve them. We study cooperative communications for MB-CRNs to tackle a fundamental limit on diversity and sampling. We also investigate several limits and tradeoffs of various design parameters for MB-CRNs. In addition, we explore the key MB-CRNs performance metrics that differ from the conventional metrics used for single-band based networks.Comment: 22 pages, 13 figures; published in the Proceedings of the IEEE Journal, Special Issue on Future Radio Spectrum Access, March 201

Interference Alignment for Cognitive Radio Communications and Networks: A Survey

© 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).Interference alignment (IA) is an innovative wireless transmission strategy that has shown to be a promising technique for achieving optimal capacity scaling of a multiuser interference channel at asymptotically high-signal-to-noise ratio (SNR). Transmitters exploit the availability of multiple signaling dimensions in order to align their mutual interference at the receivers. Most of the research has focused on developing algorithms for determining alignment solutions as well as proving interference alignment’s theoretical ability to achieve the maximum degrees of freedom in a wireless network. Cognitive radio, on the other hand, is a technique used to improve the utilization of the radio spectrum by opportunistically sensing and accessing unused licensed frequency spectrum, without causing harmful interference to the licensed users. With the increased deployment of wireless services, the possibility of detecting unused frequency spectrum becomes diminished. Thus, the concept of introducing interference alignment in cognitive radio has become a very attractive proposition. This paper provides a survey of the implementation of IA in cognitive radio under the main research paradigms, along with a summary and analysis of results under each system model.Peer reviewe