Scheduling in Centralized Cognitive Radio Networks for Energy Efficiency

Bayhan, Suzan; Alagöz, Fatíh

doi:10.1109/tvt.2012.2225650

Cited by 107 publications

(67 citation statements)

References 22 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Authors in [10] study the problem of heterogeneous coexistence between TDM and CSMA networks in TV White Space (TVWS) spectrum and address hidden terminal problem with a beacon transmission mechanism. Centralized scheduling in cognitive radio networks is studied in [15,16]. Our work is different because in our scenario, neither the scheduled nor the uncoordinated nodes rely on cognitive radio principles to enhance coexistence.…”

Section: Coexistence Of Heterogeneous Mac Schemesmentioning

confidence: 99%

Neighbors-Aware Proportional Fair scheduling for future wireless networks with mixed MAC protocols

Katila

Buratti

Abrignani

et al. 2017

J Wireless Com Network

View full text Add to dashboard Cite

In this paper, we consider a beyond-5G scenario, where two types of users, denoted as scheduled and uncoordinated nodes, coexist on the same set of radio resources for sending data to a base station. Scheduled nodes rely solely on a centralized scheduler within the base station for the assignment of resources, while uncoordinated nodes use an unslotted Carrier Sense Multiple Access (CSMA) protocol for channel access. We propose and evaluate through simulations: (a) a novel centralized resource scheduling algorithm, called Neighbors-Aware Proportional Fair (N-PF) and (b) a novel packet length adaptation algorithm, called Channel-Aware (CA) Packet Length Adaptation algorithm for the scheduled nodes. The N-PF algorithm considers the uplink channel state conditions and the number of uncoordinated nodes neighboring each scheduled node in the aggregate scheduling metric, in order to maximize packet transmission success probability. The CA algorithm provides an additional degree of freedom for improving the performance, thanks to the fact that scheduled nodes with lower number of hidden terminals, i.e., having higher packet capture probability, are assigned longer packet transmission opportunities. We consider two benchmark schemes: Proportional Fair (PF) algorithm, as a resource scheduling algorithm, and a discrete uniform distribution (DUD) scheme for packet lengths distribution. Simulation results show that the proposed schemes can result in significant gain in terms of network goodput, without compromising fairness, with respect to two benchmark solutions taken from the literature.Keywords: Proportional Fair, Neighbors-Aware, Scheduling, Unslotted CSMA, Packet delivery rate, Fairness, Packet length adaptation BackgroundIn future wireless systems, such as 5G and beyond, the current dominating human-centric communication systems will be complemented by a tremendous increase in the number of smart devices, i.e., things, equipped with radio devices, possibly sensors, and uniquely addressable [1]. This will result in explosion of wireless traffic volume [2] and consequently exponential growth in demand of radio spectrum. However, the radio spectrum resource will remain limited, and thus, efficient radio resource utilization techniques, such as advanced medium access control (MAC) schemes, will be of paramount importance.*Correspondence: charlesjumaa.katila@unibo.it Electrical, Electronics and Information Engineering Department, University of Bologna, Bologna, Italy Based on the above motivation, we envision a novel scenario, where some users (hereafter denoted as scheduled nodes), synchronized and coordinated by a base station (BS), coexist on the same set of radio resources with some other users (hereafter denoted as uncoordinated nodes), asynchronous with the BS and among them. As shown in Fig. 1, scheduled nodes could be user equipment (i.e., cellular users), while uncoordinated nodes could be things of the Internet of Things (IoT) paradigm, i.e., cars, machines, buildings [3].In wireless networks, MAC prot...

show abstract

Section: Coexistence Of Heterogeneous Mac Schemesmentioning

confidence: 99%

Neighbors-Aware Proportional Fair scheduling for future wireless networks with mixed MAC protocols

Katila

Buratti

Abrignani

et al. 2017

J Wireless Com Network

View full text Add to dashboard Cite

show abstract

“…In such a case, transmit power [1,27,34,35,40,45], signal-to-interference-plus-noise ratio (SINR) threshold [22], frequency bands/subcarriers [9,25,44,49], and/or packet length [38] are optimized separately or jointly in order to improve the CR system energy efficiency.…”

Section: Sensing-less Energy-aware Resource Allocationmentioning

confidence: 99%

Energy-Aware Cognitive Radio Systems

Bedeer

Amin

Dobre

et al. 2016

Energy Management in Wireless Cellular and Ad-Hoc Networks

View full text Add to dashboard Cite

The concept of energy-aware communications has spurred the interest of the research community in the most recent years due to various environmental and economical reasons. It becomes indispensable for wireless communication systems to shift their resource allocation problems from optimizing traditional metrics, such as throughput and latency, to an environmental-friendly energy metric. Although cognitive radio systems introduce spectrum efficient usage techniques, they employ new complex technologies for spectrum sensing and sharing that consume extra energy to compensate for overhead and feedback costs. Considering an adequate energy efficiency metric-that takes into account the transmit power consumption, circuitry power, and signaling overhead-is of momentous importance such that optimal resource allocations in cognitive radio systems reduce the energy consumption. A literature survey of recent energy-efficient based resource allocations schemes is presented for cognitive radio systems. The energy efficiency performances of these schemes are analyzed and evaluated under power budget, co-channel and adjacentchannel interferences, channel estimation errors, quality-of-service, and/or fairness constraints. Finally, the opportunities and challenges of energy-aware design for cognitive radio systems are discussed.

show abstract

“…It is known that high-level energy consumption has a profound influence on the wireless terminals due to the limit of battery capacity. Therefore, it is very important to reduce energy consumption of the wireless terminals and increase energy efficiency (EE) [1][2][3]. Recently, a lot of advanced wireless communication techniques, such as relay technique [4,5] and small cells [6], have been adopted to provide a significant capacity improvement and reduce the energy consumption.…”

Section: Introductionmentioning

confidence: 99%

Adaptive wireless transmission strategy for maximizing energy efficiency

Cai

Qiu

Jiang

et al. 2017

J Wireless Com Network

View full text Add to dashboard Cite

In a traditional wireless transmission system, studies about energy efficiency (EE) are usually for a fixed transmission mode. In this paper, we propose an adaptive wireless transmission (AWT) strategy with consideration of circuit power. In this AWT strategy, the transmission mode is switched between the direct transmission (DT) mode and the two-way relay transmission (TWRT) mode. The switch strategy is based on a transmission rate threshold R th which makes the EEs of the DT mode and the TWRT mode equal. Furthermore, we propose a transmission rate threshold determining (TRTD) algorithm with a bisection method to find the threshold R th . The simulation results also show that our AWT strategy has the maximum EE at a reasonable range of transmission rate.

show abstract

Scheduling in Centralized Cognitive Radio Networks for Energy Efficiency

Cited by 107 publications

References 22 publications

Neighbors-Aware Proportional Fair scheduling for future wireless networks with mixed MAC protocols

Neighbors-Aware Proportional Fair scheduling for future wireless networks with mixed MAC protocols

Energy-Aware Cognitive Radio Systems

Adaptive wireless transmission strategy for maximizing energy efficiency

Contact Info

Product

Resources

About