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

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 the capability of choosing one beam among M beams 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 and interference power 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 results demonstrate that our CR system yields a significantly higher capacity, and lower outage and symbol error probabilities, compared with a CR system that its SUtx has an omni-directional antenna.Comment: This paper has been submitted to IEEE Transactions on Cognitive Communications and Networkin

A Game-theoretic Model for Regulating Freeriding in Subsidy-Based Pervasive Spectrum Sharing Markets

Cellular spectrum is a limited natural resource becoming scarcer at a worrisome rate. To satisfy users\u27 expectation from wireless data services, researchers and practitioners recognized the necessity of more utilization and pervasive sharing of the spectrum. Though scarce, spectrum is underutilized in some areas or within certain operating hours due to the lack of appropriate regulatory policies, static allocation and emerging business challenges. Thus, finding ways to improve the utilization of this resource to make sharing more pervasive is of great importance. There already exists a number of solutions to increase spectrum utilization via increased sharing. Dynamic Spectrum Access (DSA) enables a cellular operator to participate in spectrum sharing in many ways, such as geological database and cognitive radios, but these systems perform spectrum sharing at the secondary level (i.e., the bands are shared if and only if the primary/licensed user is idle) and it is questionable if they will be sufficient to meet the future expectations of the spectral efficiency. Along with the secondary sharing, spectrum sharing among primary users is emerging as a new domain of future mode of pervasive sharing. We call this type of spectrum sharing among primary users as pervasive spectrum sharing (PSS) . However, such spectrum sharing among primary users requires strong incentives to share and ensuring a freeriding-free cellular market. Freeriding in pervasively shared spectrum markets (be it via government subsidies/regulations or self-motivated coalitions among cellular operators) is a real techno-economic challenge to be addressed. In a PSS market, operators will share their resources with primary users of other operators and may sometimes have to block their own primary users in order to attain sharing goals. Small operators with lower quality service may freeride on large operators\u27 infrastructure in such pervasively shared markets. Even worse, since small operators\u27 users may perceive higher-than-expected service quality for a lower fee, this can cause customer loss to the large operators and motivate small operators to continue freeriding with additional earnings from the stolen customers. Thus, freeriding can drive a shared spectrum market to an unhealthy and unstable equilibrium. In this work, we model the freeriding by small operators in shared spectrum markets via a game-theoretic framework. We focus on a performance-based government incentivize scheme and aim to minimize the freeriding issue emerging in such PSS markets. We present insights from the model and discuss policy and regulatory challenges