Ankit Kaushik

Sensing-Throughput Tradeoff for Interweave Cognitive Radio System: A Deployment-Centric Viewpoint

Secondary access to the licensed spectrum is viable only if the interference is avoided at the primary system. In this regard, different paradigms have been conceptualized in the existing literature. Among these, interweave systems (ISs) that employ spectrum sensing have been widely investigated. Baseline models investigated in the literature characterize the performance of the IS in terms of a sensing-throughput tradeoff, however, this characterization assumes perfect knowledge of the involved channels at the secondary transmitter, which is unavailable in practice. Motivated by this fact, we establish a novel approach that incorporates channel estimation in the system model, and consequently investigate the impact of imperfect channel knowledge on the performance of the IS. More particularly, the variation induced in the detection probability affects the detectors performance at the secondary transmitter, which may result in severe interference at the primary receivers. In this view, we propose employing average and outage constraints on the detection probability, in order to capture the performance of the IS. Our analysis reveals that with an appropriate choice of the estimation time determined by the proposed approach, the performance degradation of the IS can be effectively controlled, and subsequently the achievable secondary throughput can be significantly enhanced.

Estimation-throughput tradeoff for Underlay cognitive radio systems

Understanding the performance of cognitive radio systems is of great interest. To perform dynamic spectrum access, different paradigms are conceptualized in the literature. Of these, Underlay System (US) has caught much attention in the recent past. According to US, a power control mechanism is employed at the Secondary Transmitter (ST) to constrain the interference at the Primary Receiver (PR) below a certain threshold. However, it requires the knowledge of channel towards PR at the ST. This knowledge can be obtained by estimating the received power, assuming a beacon or a pilot channel transmission by the PR. This estimation is never perfect, hence the induced error may distort the true performance of the US. Motivated by this fact, we propose a novel model that captures the effect of channel estimation errors on the performance of the system. More specifically, we characterize the performance of the US in terms of the estimation-throughput tradeoff. Furthermore, we determine the maximum achievable throughput for the secondary link. Based on numerical analysis, it is shown that the conventional model overestimates the performance of the US.

Spectrum sharing for 5G wireless systems (Spectrum sharing challenge)

Understanding the performance of a spectrum sharing system by means of a hardware deployment is a challenging task. Motivated by this fact, we propose a prototype of a secondary system that co-exists with a primary system and simultaneously sustains the constraints defined by the regulatory. In this paper, we propose several key-techniques for the secondary system, which will be deployed on a hardware.

On the Performance Analysis of Underlay Cognitive Radio Systems: A Deployment Perspective

We study the performance of a cognitive underlay system (US) that employs a power control mechanism at the secondary transmitter (ST) from a deployment perspective. Existing baseline models considered for performance analysis either assume the knowledge of involved channels at the ST or retrieve this information by means of a band manager or a feedback channel; however, such situations rarely exist in practice. Motivated by this fact, we propose a novel approach that incorporates estimation of the involved channels at the ST in order to characterize the performance of the US in terms of interference power received at the primary receiver and throughput at the secondary receiver (or secondary throughput). Moreover, we apply an outage constraint that captures the impact of imperfect channel knowledge, particularly on the uncertain interference. Besides this, we employ a transmit power constraint at the ST to classify the operation of the US in terms of an interference-limited regime and a power-limited regime. In addition, we characterize the expressions of the uncertain interference and the secondary throughput for the case where the involved channels encounter Nakagami-m fading. Finally, we investigate a fundamental tradeoff between the estimation time and the secondary throughput depicting an optimized performance of the US.

Sensing-Throughput Tradeoff for Cognitive Radio Systems with Unknown Received Power

Understanding the performance of the cognitive radio systems is of great interest. Different paradigms have been extensively analyzed in the literature to perform secondary access to the licensed spectrum. Of these, Interweave System (IS) has been widely investigated for performance analysis. According to IS, sensing is employed at the Secondary Transmitter (ST) that protects the Primary Receiver (PR) from the interference induced. Thus, in order to control the interference at the PR, it is required to sustain a certain level of probability of detection. In this regard, the ST requires the knowledge of the received power. However, in practice, this knowledge is not available at the ST. Thereby performing analysis considering the prior knowledge of the received power is too idealistic, thus, do not depict the actual performance of the IS. Motivated by this fact, an estimation model that includes received power estimation is proposed. Considering a sensing-throughput tradeoff, we apply this model to characterize the performance of the IS. Most importantly, the proposed model captures the estimation error to determine the distortion in the system performance. Based on analysis, it is illustrated that the ideal model overestimates the performance of the IS. Finally, it is shown that with an appropriate choice of the estimation time, the severity in distortion can be effectively regulated.

Performance analysis of hybrid cognitive radio systems with imperfect channel knowledge

In this paper, we study the performance of hybrid cognitive radio systems that combine the benefits of interweave and underlay systems by employing a spectrum sensing and a power control mechanism at the Secondary Transmitter (ST). Existing baseline models considered for performance analysis assume perfect knowledge of the involved channels at the ST, however, such situations hardly exist in practical deployments. Motivated by this fact, we propose a novel approach that incorporates channel estimation at the ST, and consequently characterizes the performance of Hybrid Systems (HSs) under realistic scenarios. To capture the impact of imperfect channel knowledge, we propose outage constraints on the detection probability at the ST and on the interference power received at the primary receiver. Our analysis reveals that the baseline model overestimates the performance of the HS in terms of achievable secondary user throughput. Finally, based on the proposed estimation-sensing-throughput tradeoff, we determine suitable estimation and sensing durations that effectively capture the effect of imperfect channel knowledge and subsequently enhance the achievable secondary user throughput.

Experimental Study of an Underlay Cognitive Radio System: Model Validation and Demonstration

Cognitive radio is one of the potential contenders that address the problem of spectrum scarcity by making efficient use of the currently allocated spectrum below 6 GHz. A secondary access to the licensed spectrum is only possible, if the cognitive radio systems restrict the interference to the primary systems. However, the performance analysis of such a cognitive radio system is a challenging task. Currently, performance evaluation of underlay systems is limited to theoretical analysis. Most of the existing theoretical investigations make certain assumptions in order to sustain analytical tractability, which could be unrealistic from the deployment perspective. Motivated by this fact, in this work, we validate the performance of an underlay system by means of laboratory measurements, and consequently propose a hardware demonstrator of such a system. Moreover, we present a graphical user interface to provide insights to the working of the proposed demonstrator and highlight the main issues faced during this experimental study. (This work was partially supported by the National Research Fund, Luxembourg under the CORE projects “SeMIGod” and “SATSENT”.)

On the estimation of channel state transitions for cognitive radio systems

Coexistence by means of shared access is a cognitive radio application. The secondary user models the slotted primary users channel access as a Markov process. The model parameters, i.e, the state transition probabilities (α,β) help secondary user to determine the channel occupancy, thereby enables secondary user to rank the primary user channels. These parameters are unknown and need to be estimated by secondary users for each channel. To do so, the secondary users have to sense all the primary user channels in every time slot, which is unrealistic for a large and sparsely allocated primary user spectrum. With no other choice left, the secondary user has to sense a channel at random time intervals and estimate the parametric information for all the channels using the observed slots.

Operating characteristics of underlay cognitive relay networks

Understanding the performance of cognitive relay networks (CRNs) is of great interest. Recently, stochastic geometry is being used to model and characterize the performance of CRNs. It is a known fact that sensing is an integral part of the CRN, however, in most cases it is not perfect. Moreover, the model inaccuracies caused by simplifications and/or approximations when deriving the analytical expressions for characterizing CRNs may distort their true performance. With no sensing in the system, we determine a lower performance bound (LPB) that can be used to judge the reliability of other systems that include sensing and model approximations. Based on the LPB, the operating characteristics (OC) for the CRN are obtained, which determine the joint performance of the primary and secondary system. Finally, OC are used to investigate the system performance under different scenarios.

Performance Analysis of Interweave Cognitive Radio Systems with Imperfect Channel Knowledge over Nakagami Fading Channels

Knowledge of interacting channels is essential for characterizing the performance of a cognitive radio system in terms of interference power received by a primary receiver and throughput at a secondary receiver. Baseline models considered for the performance characterization assume perfect knowledge of the interacting channels. Recently, an analytical framework has been proposed that incorporates channel estimation and subsequently characterizes the performance of cognitive Interweave Systems (ISs). However, the analysis was pertained to the deterministic behaviour of the interacting channels. In this paper, we extend the characterization of the aforementioned framework to investigate the influence of channel fading on the performance of the IS. Our analysis indicate that an inappropriate choice of estimation time can severely degrade the performance of the IS in terms of achievable secondary throughput.