Beam Selection and Discrete Power Allocation in Opportunistic Cognitive Radio Systems With Limited Feedback Using ESPAR Antennas

Abstract

We consider an opportunistic cognitive radio (CR) system consisting of a primary user (PU), secondary transmitter (SUtx), and secondary receiver (SUrx), where SUtx is equipped with an electrically steerable parasitic array radiator (ESPAR) antenna with beam steering capability for sensing and communication, and there is a limited feedback channel from SUrx to SUtx. Taking a holistic approach, we develop a framework for integrated sector-based spectrum sensing and sector-based data communication. Upon sensing the channel busy, SUtx determines the beam corresponding to PU's orientation. Upon sensing the channel idle, SUtx transmits data to SUrx, using the selected beam corresponding to the strongest channel between SUtx and SUrx. We formulate a constrained optimization problem, where SUtx-SUrx link ergodic capacity is maximized, subject to average transmit power and interference constraints, and the optimization variables are sensing duration, thresholds of channel quantizer at SUrx, and transmit power levels at SUtx. Since this problem is non-convex we develop a suboptimal computationally efficient iterative algorithm to find the solution. Our numerical results quantify the capacity improvement provided by the ESPAR antenna and demonstrate that our CR system yields lower outage and symbol error probabilities, compared with a CR system that its SUtx has an omni-directional antenna.Index Terms-Beam selection, cognitive radio, constrained ergodic capacity maximization, discrete power allocation, ESPAR antenna, imperfect channel sensing, error-free bandwidth limited feedback channel, reconfigurable antennas.

Spectrum Sensing for Cognitive Radio: Recent Advances and Future Challenge

“…In this context, joint sensing and localization of PU becomes of high importance since the localization of PU transmitter may facilitate the mission of SUs in identifying the beam and thus to diagnose the spatiotemporal availability of the spectrum [200,201]. Recently, some work has been introduced to enable spatial SS by identifying the PU's location and adjusting the SU's beam using the received power at SUs surrounding the PU [200,202]. In this regard, estimation techniques have to be more developed in order to estimate the PU beam blindly or in the case where little information about PU transmission is available [203][204][205].…”

Power Adaptation for Distributed Detection in Energy Harvesting WSNs with Finite-Capacity Battery

“…We obtain α (0) n,l,k using Algorithm 1. Then, we calculate Ψ (1) n , ∀n using (7). We iteratively find Ψ (t) n and α (t) n,l,k until the convergence is reached, i.e., when the following criteria is met max k |ψ t n,k − ψ t+1 n,k | < ǫ 2 , ∀n.…”

“…while max k |ψ q n,k − ψ q+1 n,k | > ǫ 2 , ∀n, do 1: Calculate optimal α * (q+1) n,l,k using Algorithm.1. 2: Update Ψ (q+1) n using (7). 3: Set q = q + 1. show J-divergence versus P tot , confirming that it has the same trend as P F C D versus P tot .…”

“…Unlike traditional battery-powered systems, where transmission is often subject to a constant power constraint, the energy available to an energy harvesting system is modeled as a random process [5]. For transmitters that are powered by energy harvesters, unlike conventional communication devices that are subject only to a power constraint or a sum energy constraint, they, in addition, subject to other energy harvesting constraints [6], [7].…”

Source Localization and Tracking for Dynamic Radio Cartography using Directional Antennas

“…In [10], [11] the RSS and DoA of a PU is estimated using energy measurements from a sectorized antenna and the performance and theoretical bounds of DoA/RSS estimation are studied. The orientation of a PU with respect to SU's location is determined in [12], [13] based on the RSS where an SU is equipped with a reconfigurable antenna. The signal received at an antenna array is sparse in the spatial domain and compressive sensing can be employed for DoA estimation using less number of radio frequency (RF) chains [14].…”