A survey on spectrum sensing algorithms for cognitive radio

Patil, Vilaskumar; Patil, Siddarama R.

doi:10.1109/hmi.2016.7449196

Cited by 44 publications

(10 citation statements)

References 9 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…It essentially allows secondary users (SU s) to know whether and when a licensed band is available prior to using it so as to avoid harming primary users (PU s). Due to its vital role, over the last decade or so, a tremendous amount of research has focused on developing techniques and approaches that enable efficient spectrum sensing [3,4]. Most of the focus has, however, been on singleband spectrum sensing, and the focus on wideband spectrum sensing is more recent and has received lesser attention [5].…”

Section: Introductionmentioning

confidence: 99%

Exploiting wideband spectrum occupancy heterogeneity for weighted compressive spectrum sensing

Khalfi¹,

Hamdaoui²,

Guizani³

2017

2017 IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS)

View full text Add to dashboard Cite

Compressive sampling has shown great potential for making wideband spectrum sensing possible at sub-Nyquist sampling rates. As a result, there have recently been research efforts that aimed to develop techniques that leverage compressive sampling to enable compressed wideband spectrum sensing. These techniques consider homogeneous wideband spectrum, where all bands are assumed to have similar PU traffic characteristics. In practice, however, wideband spectrum is not homogeneous, in that different spectrum bands could have different PU occupancy patterns. In fact, the nature of spectrum assignment, in which applications of similar types are often assigned bands within the same block, dictates that wideband spectrum is indeed heterogeneous, as different application types exhibit different behaviors. In this paper, we consider heterogeneous wideband spectrum, where we exploit this inherent, block-like structure of wideband spectrum to design efficient compressive spectrum sensing techniques that are well suited for heterogeneous wideband spectrum. We propose a weighted ℓ1−minimization sensing information recovery algorithm that achieves more stable recovery than that achieved by existing approaches while accounting for the variations of spectrum occupancy across both the time and frequency dimensions. Through intensive numerical simulations, we show that our approach achieves better performance when compared to the state-of-the-art approaches.Index Terms-Wideband spectrum sensing; compressive sampling; Heterogeneous wideband spectrum occupancy.

show abstract

Section: Introductionmentioning

confidence: 99%

Exploiting wideband spectrum occupancy heterogeneity for weighted compressive spectrum sensing

Khalfi¹,

Hamdaoui²,

Guizani³

2017

2017 IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS)

View full text Add to dashboard Cite

show abstract

“…The main constraint for the secondary cognitive radios is to guarantee that the interference caused to the PU's needs to be below tolerable threshold . To this end, spectrum sensing is an imponent of the DSA architecture. In the geographical area, spectrum sensing is the task of obtaining awareness about the existence of PUs and the spectrum usage.…”

Section: Network Efficiencymentioning

confidence: 99%

The role of caching in next generation cellular networks: A survey and research outlook

Kabir

Rehman

Gilani

et al. 2019

Trans Emerging Tel Tech

View full text Add to dashboard Cite

Mobile applications and social networks tend to enhance the needs for high‐quality content access. To address the expeditious growing demand for data services in 5G cellular networks, it is important to develop distribution techniques and an efficient content caching, aiming to significantly reduce redundant data transmission and, thus, improve the efficiency of the networks. In modern communication systems, caching has emerged as a vital tool for reducing peak data rates. It is anticipated that energy harvesting and self‐powered small base stations are the fundamental part of next‐generation cellular networks. However, uncertainties in energy are the main reason to adopt energy efficient power control schemes to reduce SBS energy consumption and ensure the quality of services for users. Using the edge cooperative caching such as energy efficient design can also be achievable, which reduces the usage of the capacity limited SBSs backhaul and the energy consumption. To support the huge power demand of cellular network, renewable energy harvesting technologies can be leveraged. In addition to this, power supply to the infrastructures is the main challenge to the mobile network operators (MNOs) especially in terms of economic optimum, sustainability, and green energy in developing countries for the growth of cellular networks. Renewable energy–based solutions for MNOs not only reduce the overall carbon dioxide emissions but also provide numerous profits.

show abstract

“…However, in such coexistence environments, communication quality deteriorates because wireless networks do not assume that they coexist with other kinds of wireless networks on the same frequency band (e.g., unlicensed band). Therefore, an effective interference mitigation mechanism is needed [8]- [10].…”

Section: Introductionmentioning

confidence: 99%