A Comparison between Stand-Alone and Distributed Architectures for Spectrum Hole Detection

Abstract

Abstract-In this paper two different cognitive radio architectures, i.e. stand-alone and distributed, are proposed for spectrum sensing purposes. In particular, both architectures implement a fast and reliable algorithm based on cyclic features extraction which allows to identify spectrum holes. The performances of such systems are compared in detecting primary users' presence in a monitored area classifying the used transmission standards, IEEE 802.11a and IEEE 802.16e. The considered scenario is challenging since both standards use the OFDM transmission technique, are designed to have the same bandwidth and use the same frequency band. A set of numerical simulations have been carried out to compare the performances of the proposed systems in a heavy multipath scenario and their advantages and disadvantages are discussed.

A comparison among cooperative spectrum sensing approaches for cognitive radios

“…In particular, cognitive (secondary) users can be allowed to opportunistically access to licensed frequency bands if legacy (primary) users are not using it and without causing interference [2], [7].…”

“…One of the main challenges in this context is to perform a fast and reliable spectrum sensing phase, which should allow to determine if a given channel is occupied by a primary user and what is the employed transmission standard [2], [7]. Such information can be useful not only to permit a real time identification of the so called spectrum holes [1], but also to predict the length of the possible unused parts of the spectral resource, by estimating key parameters (e.g.…”

“…The reliability represents a key feature of the spectrum sensing phase, since harmful interferences to primary users should be avoided in the CR approach [1], [2] and as a consequence, the so called "probability of false opportunity detection" should be minimized [7]. Although a high number of different spectrum sensing techniques have been proposed in the open literature, e.g.…”

“…Although a high number of different spectrum sensing techniques have been proposed in the open literature, e.g. energy detection, matched filters or feature detection [7], [8], many issues still persist, to find out a fast and trustworthy spectrum sensing algorithm remains a challenging task [2], [9] in the CR context.…”

“…Moreover, in real environments, the signal received by the secondary terminals is often corrupted by channel distortions. In particular, path loss, multipath fading and shadowing effects can cause a significant signal impairment [7], [9]. Such variation in the power of the received signal due to, as an example, a sudden deep fade, lead to a probable undesirable primary user missed detection [9] and, as a consequence, to a misleading identification of a spectrum hole [7], [8].…”