Shree Krishna Sharma

Cognitive Radio Techniques Under Practical Imperfections: A Survey

Cognitive radio (CR) has been considered as a potential candidate for addressing the spectrum scarcity problem of future wireless networks. Since its conception, several researchers, academic institutions, industries, and regulatory and standardization bodies have put their significant efforts toward the realization of CR technology. However, as this technology adapts its transmission based on the surrounding radio environment, several practical issues may need to be considered. In practice, several imperfections, such as noise uncertainty, channel/interference uncertainty, transceiver hardware imperfections, signal uncertainty, and synchronization issues, may severely deteriorate the performance of a CR system. To this end, the investigation of realistic solutions toward combating various practical imperfections is very important for the successful implementation of cognitive technology. In this direction, first, this survey paper provides an overview of the enabling techniques for CR communications. Subsequently, it discusses the main imperfections that may occur in the most widely used CR paradigms and then reviews the existing approaches toward addressing these imperfections. Finally, it provides some interesting open research issues.

Satellite cognitive communications: Interference modeling and techniques selection

Due to increasing demand of high speed data rate for satellite multimedia and broadcasting services and spectrum scarcity problem in satellite bands, exploring new techniques for enhancing spectral efficiency in satellite communication has become an important research challenge. In this aspect, satellite cognitive communication can be considered as a promising solution to solve spectrum scarcity problem. In this paper, different cognitive techniques such as underlay, overlay, interweave and database related techniques are discussed by reviewing the current state of art. Exact beam patterns of a multi-beam satellite are plotted over the Europe map and interference modeling between terrestrial Base Station (BS) and satellite terminal is carried out on the basis of interference power level. Furthermore, suitable cognitive techniques are proposed in high and low interference regions in the context of satellite cognitive communication.

Interference alignment for spectral coexistence of heterogeneous networks

The coexistence of heterogeneous networks within the same spectrum for enhancing the spectrum efficiency has attracted large interest lately in the research community. Furthermore, the research interest towards the deployment of small cells and multibeam satellites is increasing due to high capacity, easier deployment and higher energy efficiency. However, due to the scarcity of available spectrum and the requirement of additional spectrum for these systems, small cells need to coexist with macrocells and multibeam satellites need to coexist with monobeam satellites within the same spectrum. In this context, this contribution investigates an underlay spectral coexistence mechanism which exploits an interference alignment (IA) technique in order to mitigate the interference of cognitive transmitters towards the primary receivers in a normal uplink mode. More specifically, three types of IA techniques, namely static, uncoordinated and coordinated are investigated. The performance of the IA technique is evaluated and compared with primary only, resource division and no-mitigation techniques in terms of sum-rate capacity, primary to secondary rate ratio and primary rate protection ratio. It is shown that the coordinated IA technique perfectly protects the primary rate in both terrestrial and satellite coexistence scenarios.

Eigenvalue-Based Sensing and SNR Estimation for Cognitive Radio in Presence of Noise Correlation

Herein, we present a detailed analysis of an eigenvalue-based sensing technique in the presence of correlated noise in the context of a cognitive radio (CR). We use standard-condition-number (SCN)-based decision statistics based on asymptotic random matrix theory (RMT) for the decision process. First, the effect of noise correlation on eigenvalue-based spectrum sensing (SS) is analytically studied under both the noise-only and signal-plus-noise hypotheses. Second, new bounds for the SCN are proposed to achieve improved sensing in correlated noise scenarios. Third, the performance of fractional-sampling (FS)-based SS is studied, and a method to determine the operating point for the FS rate in terms of sensing performance and complexity is suggested. Finally, a signal-to-noise ratio (SNR) estimation technique based on the maximum eigenvalue of the covariance matrix of the received signal is proposed. It is shown that the proposed SCN-based threshold improves sensing performance in correlated noise scenarios, and SNRs up to 0 dB can be reliably estimated with a normalized mean square error (MSE) of less than 1% in the presence of correlated noise without the knowledge of noise variance.

Spectrum sensing in dual polarized fading channels for cognitive SatComs

Next generation networks are moving towards the convergence of mobile, fixed and broadcasting services in one standard platform, which requires the co-existence of satellite and terrestrial networks in the same spectrum. This framework has motivated the concept of cognitive Satellite Communication (SatComs). In this aspect, the problem of exploiting Spectrum Sensing (SS) techniques for a dual polarized fading channel is considered. In this paper, the performance of Energy Detection (ED) technique is evaluated in the context of a co-existence scenario of a satellite and a terrestrial link. Diversity combining techniques such as Equal Gain Combining (EGC) and Selection Combining (SC) are considered to enhance the SS efficiency. Furthermore, analytical expressions for probability of detection (Pd) and probability of false alarm (Pf) are presented for these techniques in the considered fading channel and the sensing performance is studied through analytical and simulation results. Moreover, the effect of Cross Polar Discrimination (XPD) on the sensing performance is presented and it is shown that SS efficiency improves for low XPD.

Application of Compressive Sensing in Cognitive Radio Communications: A Survey

Compressive sensing (CS) has received much attention in several fields such as digital image processing, wireless channel estimation, radar imaging, and cognitive radio (CR) communications. Out of these areas, this survey paper focuses on the application of CS in CR communications. Due to the under-utilization of the allocated radio spectrum, spectrum occupancy is usually sparse in different domains such as time, frequency, and space. Such a sparse nature of the spectrum occupancy has inspired the application of CS in CR communications. In this regard, several researchers have already applied the CS theory in various settings considering the sparsity in different domains. In this direction, this survey paper provides a detailed review of the state of the art related to the application of CS in CR communications. Starting with the basic principles and the main features of CS, it provides a classification of the main usage areas based on the radio parameter to be acquired by a wideband CR. Subsequently, we review the existing CS-related works applied to different categories such as wideband sensing, signal parameter estimation and radio environment map (REM) construction, highlighting the main benefits and the related issues. Furthermore, we present a generalized framework for constructing the REM in compressive settings. Finally, we conclude this survey paper with some suggested open research challenges and future directions.

Cognitive Radio Techniques for Satellite Communication Systems

The usable satellite spectrum is becoming scarce due to continuously increasing demand for broadcast, multimedia and interactive services. In this context, cognitive satellite communications has received important attention lately in the research community. Exploring efficient spectrum sharing techniques for enhancing spectral efficiency in satellite communication has become an important research challenge. In this paper, we study the main aspects of satellite cognitive communications and present possible practical scenarios for hybrid/dual cognitive satellite systems. Furthermore, suitable cognitive techniques for the considered scenarios are identified. More specifically, Spectrum Sensing (SS), interference modeling, and beamforming techniques are discussed for hybrid cognitive scenario and SS, interference alignment, and cognitive beamhopping techniques are discussed for dual satellite systems. This paper concludes by providing interesting open research issues in this domain.

Resource Allocation for Cognitive Satellite Communications With Incumbent Terrestrial Networks

The lack of available unlicensed spectrum together with the increasing spectrum demand by multimedia applications has resulted in a spectrum scarcity problem, which affects satellite communications (SatCom) as well as terrestrial systems. The goal of this paper is to propose resource allocation (RA) techniques, i.e., carrier, power, and bandwidth allocation, for a cognitive spectrum utilization scenario where the satellite system aims at exploiting the spectrum allocated to terrestrial networks as the incumbent users without imposing harmful interference to them. In particular, we focus on the microwave frequency bands 17.7-19.7 GHz for the cognitive satellite downlink and 27.5-29.5 GHz for the cognitive satellite uplink, although the proposed techniques can be easily extended to other bands. In the first case, assuming that the satellite terminals are equipped with multiple low block noise converters (LNB), we propose a joint beamforming and carrier allocation scheme to enable cognitive space-to-Earth communications in the shared spectrum where fixed service (FS) microwave links have priority of operation. In the second case, however, the cognitive satellite uplink should not cause harmful interference to the incumbent FS system. For the latter, we propose a joint power and carrier allocation (JPCA) strategy followed by a bandwidth allocation scheme, which guarantees protection of the terrestrial FS system while maximizing the satellite total throughput. The proposed cognitive satellite exploitation techniques are validated with numerical simulations considering realistic system parameters. It is shown that the proposed cognitive exploitation framework represents a promising approach for enhancing the throughput of conventional satellite systems.

SNR Estimation for Multi-dimensional Cognitive Receiver under Correlated Channel/Noise

In addition to Spectrum Sensing (SS) capability required by a Cognitive Radio (CR), Signal to Noise Ratio (SNR) estimation of the primary signals at the CR receiver is crucial in order to adapt its coverage area dynamically using underlay techniques. In practical scenarios, channel and noise may be correlated due to various reasons and SNR estimation techniques with the assumption of white noise and uncorrelated channel may not be suitable for estimating the primary SNR. In this paper, firstly, we study the performance of different eigenvalue-based SS techniques in the presence of channel or/and noise correlation. Secondly, we carry out detailed theoretical analysis of the signal plus noise hypothesis to derive the asymptotic eigenvalue probability distribution function (a.e.p.d.f.) of the received signals covariance matrix under the following two cases: (i) correlated channel and white noise, and (ii) correlated channel and correlated noise, which is the main contribution of this paper. Finally, an SNR estimation technique based on the derived a.e.p.d.f is proposed in the presence of channel/noise correlation and its performance is evaluated in terms of normalized Mean Square Error (MSE). It is shown that the PU SNR can be reliably estimated when the CR sensing module is aware of the channel/noise correlation.

Spatial Filtering for Underlay Cognitive SatComs

Herein, we study an underlay beamforming technique for the coexistence scenario of satellite and terrestrial networks with the satellite return link as primary and the terrestrial uplink as secondary. Since satellite terminals are unique in that they always point towards the geostationary satellite, interference received by the terrestrial Base Station (BS) is concentrated in a specific angular sector. The priori knowledge that all the geostationary satellite terminals are facing south for the European coverage can be used in designing a beamformer at the terrestrial BS. Based on this concept, we propose a receive beamformer at the BS to maximize the Signal to Interference plus Noise Ratio (SINR) towards the desired user and to mitigate the interference coming from the interfering satellite terminals. The performances of Minimum Variance Distortionless (MVDR) and Linear Constrained Minimum Variance (LCMV) beamformers are compared for our considered scenario. It is shown that LCMV beamformer is better suited in rejecting interference even in case of Direction of Arrival (DoA) uncertainty of interfering satellite terminals as long as DoA range of the interfering sector is known to the beamformer. Furthermore, it is noted that MVDR beamformer is suitable for a large number of interferers.