Search

This paper investigates collaborative spectrum sharing (CSS) for which a cognitive secondary transmitter acts as a decode-and-forward (DF) relay for two primary users (PUs) occupying an interfering multiple-access channel. PUs are assumed to send their signals simultaneously; hence, interference between the primary signals exists due to the multiple-access nature. The secondary user (SU) selects and forwards one of the PU's signals to a desired destination, and at the same time, the SU also transmits its own signal only if it is not harmful to PUs. The selection of a primary signal to relay is investigated, depending on SU's knowledge of two primary source–destination channels, for which closed-form outage probabilities for PUs and SU are provided accordingly. With the help of the closed-form PU's outage probability, an optimal selection strategy between the primary signals and an optimal power allocation between the primary and secondary signals are also obtained in closed form, which minimizes SU's outage probability while keeping the PU's outage performance at an SU-free level. Numerical investigation is used to verify and illustrate the analysis given in this paper. Numerical results also show that the SU's performance can vary significantly according to the amount of channel knowledge that the SU can have. [ABSTRACT FROM PUBLISHER]

This paper proposes a new spectrum sensing technique, referred to as autonomous compressive sensing (CS)-augmented spectrum sensing, which can be developed to provide more efficient spectrum opportunity identification than geolocation database methods. First, we propose an autonomous CS-based sensing algorithm that enables the local secondary users (SUs) to automatically choose the minimum sensing time without knowledge of spectral sparsity or channel characteristics. The compressive samples are collected block-by-block in time, while the spectral is gradually reconstructed until the proposed stopping criterion is reached. Moreover, a CS-based blind cooperating user selection algorithm is proposed to select the cooperating SUs via indirectly measuring the degeneration of the signal-to-noise ratio experienced by different SUs. Numerical and real-world test results demonstrate that the proposed algorithms achieve high detection performance with reduced sensing time and number of cooperating SUs in comparison with the conventional compressive spectrum sensing algorithms. [ABSTRACT FROM AUTHOR]

Reporting channels are essential for implementing cooperative spectrum sensing (CSS) in cognitive radio technology. In this paper, a novel decentralized CSS scheme capable of operating in the absence of dedicated reporting channels is presented. Existing schemes which operate in the absence of dedicated reporting channels rely on the transmission of hard decision bits from cooperating secondary users (CSUs). The proposed scheme supports a mobile spectrum sensor termed as the leading secondary sensor node (LSSN) to assist a contending secondary transmitter in spectrum sensing. Unlike existing schemes, the proposed CSS framework offers the freedom of using multiple bits for transmitting a quantized version of the test statistics between secondary user (SU) nodes. In order to reduce energy consumption and system complexity, the CSUs do not take part in sensing but only act as relays for retransmitting the quantized test statistics from LSSN to the contending SU transmitter. The proposed network protocol also assists the SU transmitters in avoiding collisions with each other. Closed form expressions for the probability of false alarm and detection have been derived. Monte-Carlo simulations are used to validate the analytical expressions. The proposed scheme can outperform the recently proposed best-selection reporting scheme when the number of CSUs is less and the contending CSUs and the SU transmitter lie in an area of poor primary signal reception. [ABSTRACT FROM PUBLISHER]

This paper studies the exploitation of the modulation-based dimension in cognitive radio systems to perform cooperative spectrum sharing (CSS). Unlike conventional opportunistic spectrum sharing techniques where a secondary user (SU) system attempts to utilize the spectrum hole in either time, frequency, or spatial dimension created by the primary user (PU) system, this study focuses on finding accessible spectrum spaces created by the structure of modulation constellations. In this novel CSS scheme, by taking advantage of the knowledge on the PU's modulation scheme, the SU superimposes its own modulated signal on the PU's signal. We examine two CSS scenarios: 1) phase-shift-keying (PSK) is used at both the PU and SU and 2) PSK is used at the PU while pulse-amplitude modulation is used at the SU. Interestingly, the proposed superposition approach in CSS Scenario 2 enables a CSS mechanism without either impairing the performance of the primary receiver or requiring a change in its demodulation rule. At the same time, a much better symbol-error-rate (SER) performance is achievable for the SU's receiver in Scenario 2 than in Scenario 1. Theoretical SER performances of both the PU and SU are then thoroughly analyzed and confirmed by numerical simulations. [ABSTRACT FROM AUTHOR]

Spectrum sensing and spectrum sharing are two fundamental issues in a cognitive radio network (CRN). The spectrum sensing data falsification (SSDF) attack imposes bad effects on both spectrum sensing and spectrum sharing. To deal with SSDF attacks and to incentivize secondary users (SUs) to behave well, a joint spectrum sensing and resource allocation (JSSRA) scheme in a CRN is proposed in this paper. The JSSRA problem is formulated as a weighted-proportional-fairness-based resource-allocation optimization problem under the constraint that the primary user (PU) network is sufficiently protected. The problem is decomposed into two subproblems, namely, the resource allocation subproblem and cooperative SU number decision subproblem, which are solved by the Lagrangian dual algorithm and the brute-force algorithm, respectively. Moreover, a user-selection method based on reinforcement learning is presented to select reliable SUs for cooperative spectrum sensing (CSS). In addition, the SU's trust degree is updated according to its behavior in CSS and is used in the sensed resource-allocation process. The key point of our proposed scheme is to make SUs improve the sensing reliability and prevent SUs from behaving maliciously by an incentive mechanism. Comprehensive performance evaluation is conducted by computer simulation. It is shown that the proposed JSSRA scheme deals with the SSDF attack well in cooperative sensing process to improve system robustness and achieves a significant system utility gain in resource allocation. [ABSTRACT FROM PUBLISHER]

By cooperative spectrum sharing schemes, a primary network (PN) leases a part of the licensed band to a secondary network (SN). A secondary transmitter (ST) acts as a relay for the primary transmitter (PT) to improve the end-to-end link quality of the PN, and as a reward, the ST gets the opportunity to transmit its own data by superposition coding. In this paper, a new cooperative spectrum sharing (CSS) scheme taking into account malicious eavesdropping (wiretapping) by a PN is proposed. In such scheme, licensed band is a decoy to an SN to wiretap the secondary transmission. Thus, secrecy in secondary transmission becomes critical to the SN. To get achievable secrecy (data) rate in secondary transmission and to fulfill the duty as a relay for primary transmission, the SN looks for a smart power-allocation (SPA) parameter that satisfies both goals. SPA parameter \alpha\mathrm{smart} provides the target secrecy data rate, and the achieved data rate at the PN is greater than or equal to the data rate obtained by the direct transmission (DT). Considering a Rayleigh block-fading channel, the SPA parameter is evaluated for each secondary transmission. Details on the evaluation of the SPA parameter are presented, and theoretical outage probabilities of the PN and the SN are derived and validated by simulations. [ABSTRACT FROM AUTHOR]