Abstract
The relentlessly increasing number of small-sized devices with limited powering and computational capabilities requires the adoption of new approaches to spectrum access. In this paper, we analyze an underlay cooperative cognitive wireless system based on available statistical channel state information (CSI) that is applicable to the cognitive system with limited computational resources due to its low complexity. We considered the scenario where the primary and the cognitive network coexist in the same spectrum band, under the constraints of interference threshold and maximal tolerable outage permitted by the primary user. The communication in the secondary decode-and-forward (DF) relaying system is established via a self-sustainable relay, which harvests energy from both cognitive and primary transmitters. The closed-form expressions for the outage probability of the cognitive network are derived, which are valid for both time-switching relaying (TSR) and power-splitting relaying (PSR) protocols. We analyze the influence of both cognitive and primary systems as well as the impact of channel parameters on the cognitive system outage performance. The derived analytical results are corroborated by an independent simulation method.
Highlights
Recent advances in telecommunication concepts have resulted in ubiquitous connectivity, as well as a variety of possible services of improved quality
The number of primary transmitters is set to N = 1 in all simulations, except in the case of the results presented in Figure 6, where it is considered that the number of primary transmitters is N = 2
The self-sustainable relay harvests energy from both cognitive and primary transmitters based on time-switching relaying (TSR) and power-splitting relaying (PSR) energy-harvesting protocols
Summary
Recent advances in telecommunication concepts have resulted in ubiquitous connectivity, as well as a variety of possible services of improved quality. It is envisioned that forthcoming networks will satisfy a wide range of requirements regarding different types of services, so spectrum access should be adjusted with the aim to maximize overall spectrum utilization. This is especially important for the Internet of Things (IoT) systems that have an exceptionally important role in transforming the way communications are used in everyday life. As IoT systems imply a huge number of spatially distributed connected devices and sensors with modest powering and computational capabilities, access to spectrum resources needs to be provided in a manner that is adapted to their characteristics and limitations [1,2]
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