Energy Detection Algorithm For Spectrum Research Articles

Spectrum Sensing of Noncooperative Beam Signals

In this paper, we investigate the issue of spectrum sensing of noncooperative beam signals that are emitted by a multiantenna transmitter. When the sampling period of the sensing node includes the whole process of beam scanning, that is, spectrum sensing is performed in an ideal situation, we use the traditional energy detection algorithm for spectrum sensing and get good results; for multiantenna beam scanning spectrum sensing in nonideal situation, the performance of traditional energy detection algorithm is seriously degraded. To deal with this problem, a sensing period selection (SPS) algorithm is proposed. The simulation results show that the proposed algorithm can effectively improve the performance of spectrum sensing in the multiantenna array beam scanning scenario.

Energy Detection Algorithm for Spectrum Sensing Using Three Consecutive Sensing Events

An energy detection (ED) algorithm, which takes into consideration three consecutive sensing events, is introduced in this letter. This algorithm, named three-event ED (3EED), takes the decision in one sensing event, considering also the event immediately before and the one immediately after it. We design the proposed algorithm to exploit the knowledge of the primary user (PU) activity duty cycle value for tracking the changes of the PU state and we prove that 3EED becomes independent of the PU model parameters for a low duty cycle. In this letter, we demonstrate that 3EED has better detection performance compared to the conventional ED (CED) algorithm, providing a correct detection probability (CDP) gain of more than 7% for a false-alarm probability (FAP) of 0.1. Also, we compare 3EED with other algorithms in terms of detection performance and complexity.

Sensing Performance Evaluation over Multihop System with Composite Fading Channel

Cognitive radio has been demonstrated for improved spectrum utilization by secondary users in the presence of spectrum holes. In this paper, a Cognitive Radio (CR) network is implemented over the cooperative multihop wireless link. A multihop network is a collection of relay nodes within transmitter and receiver. A fixed infrastructure based multihop architecture is assumed for the performance analysis of energy detection algorithm for spectrum sensing in CR. System performance estimation against channel impairments dominated by fading and shadowing effects is one of the prerequisite for performance analysis of such networks. An effort has been made for exact performance analysis of multihop wireless network over composite fading channels. The investigation lead to the findings i.e., for a given value of fading or shadowing parameter, the preferable detection probability is always dependent upon the optimum number of hops. Depending upon SNR a three- or five- hop link may perform better. For severe fading conditions, the one-hop link performs best.

Wavelet Based Dynamic Spectrum Sensing for Cognitive Radio under Noisy Environment

Optimum utilization of available spectra is a major issue of concern in the field of wireless communication technology. Ever growing demand of wireless services poses the problem of frequency scarcity. To improve the spectrum efficiency in order to accumulate more and more users researchers have proposed cognitive radio technology. Cognitive radio, due their adaptive nature adapt themselves as per the available spectrum their by enhancing data transmission, without disturbing other users. The charm of cognitive radio is the spectrum reuse functionality. For cognitive radio environment the primary task is the sensing and identification of spectrum holes in wireless environment. This paper develop a wavelet based efficient spectrum sensing technique for noisy channel with high probability of detection and reduced probability of false triggering. To the best of our knowledge, it is first time that someone has applied the wavelet as a de-nosing tool for improvisation in existing energy detection algorithm for spectrum sensing.