Traffic-load aware spectrum allocation in cloud assisted cognitive radio networks

Bhuiyan, Najmun Nahar; Ratri, Roza Tabassum; Anjum, Iffat; Razzaque, Md. Abdur

doi:10.1109/r10-htc.2017.8289031

Cited by 6 publications

(5 citation statements)

References 8 publications

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“…Two powerful channel assignments for the FDMA have been proposed. For the first, the adaptive channel assignment of FDMA for maximizing a SPD has been proposed [27], [28], where the SPD is the ratio of the number of packets successfully sent to the fusion center to the total number of packets. For the second, a random assignment between each sensor and channel has been proposed [22].…”

Section: Numerical Resultsmentioning

confidence: 99%

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Adaptive Channel Assignment With Predictions of Sensor Results and Channel Occupancy Ratio in PhyC-SN

et al. 2019

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Applications related to the Internet of Things are widely diversified and require both low latency and the access of massive sensors to wireless sensor networks. In physical wireless parameter conversion sensor networks (PhyC-SN), a fusion center (FC) can recognize information from all sensors on the frequency spectrum of the received signals via conversion from sensor information to signal frequency. The higher resolution of sensor information of PhyC-SNs requires securing more frequency bandwidth. Therefore, spectrum sharing between PhyC-SNs and other systems is essential. For this study, we assume that primary systems (PSs) refer to other wireless systems and that secondary systems (SSs) refer to the PhyC-SN. The SS detects any access from the PS and immediately stops access to an FC. This results in a loss of sensor information. Thus, the accuracy of the gathered sensor information by an FC is degraded. This paper proposes an adaptive channel assignment based on two predictions; sensor information and channel occupancy rate. In the proposed method, the predicted error caused by the cessation of channel access is calculated and the assignment is constructed by minimizing this predicted error. Since the sensor can select channels in accordance with the error of an instantaneous sensor result, the proposed channel assignment can utilize awareness of the instantaneous sensor result. The proposed method achieves high accuracy of gathered sensor information while delivering less frequent sensor information to the FC, thereby improving the utilization efficiency of frequency channels.

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Section: Numerical Resultsmentioning

confidence: 99%

“…The optimal channel assignment subject to cumulative interference for maximizing the availability of a channel is considered [27]. In addition, channel assignment based on the COR of a PS assisted by a cloud server for maximizing the future availability of access channels is considered [28].…”

Section: Related Workmentioning

confidence: 99%

Adaptive Channel Assignment With Predictions of Sensor Results and Channel Occupancy Ratio in PhyC-SN

et al. 2019

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“…Drones have been deployed to extend communications range in different critical operations [24]- [26]. The drone deployment problem on disaster-struck areas is mainly divided into two categories: a) Finding the drone's optimal location and altitude to maximize the coverage of the network [1], [7] and b) determining the bandwidth or time location scheme to maximize the network usage [3], [7], [27], [28].…”

Section: Related Workmentioning

confidence: 99%

“…We compare our proposed system (RESTORE) with existing drone-assisted emergency communications schemes in terms of the total number of drones needed to serve the disasterstruck area, the total number of served stations, the aggregated data rate, and the energy consumption of a drone during downlink transmissions. The existing schemes are the traffic load awareness (TLA) [27], pathloss awareness (PLA) [28], and profit maximization (PMA) schemes [3]. These three schemes use RF communications in the front-haul and FSOC in the back-haul.…”

Section: Comparative Analysismentioning

confidence: 99%

RESTORE: Low-Energy Drone-Assisted NLoS-FSO Emergency Communications

Esubonteng

Rojas‐Cessa

2022

IEEE Access

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Drones are becoming an alternative for the rapid but temporary deployment of datacommunication infrastructure in disaster-struck areas. A drone may be equipped with radio-frequency (RF) communication equipment to provide network connectivity for stranded users and first responders. However, the drone service time is greatly limited by the power consumption from propulsion and communications, and by the limited battery capacity. Rather than improving rate-allocation strategies and flight paths, we dramatically reduce the consumed power by 100 fold or more with the adoption of no-line-of-sight freespace optical communications (NLOS-FSOC). NLOS-FSOC uses diffuse reflectors to make the optical signal detectable to stations with line-of-sight to the diffuse reflector and not necessarily with the transmitter. We also propose a heuristic scheme, called RESTORE, to determine the drone's optimal flying altitude that provides the largest coverage. We analyze the proposed system by evaluating its performance and compare it to existing leading drone-assisted emergency communications and show that the proposed approach not only dramatically reduces energy consumption but also provides 130% more aggregated data rates and serves more than 100% of users than existing communications systems.INDEX TERMS free-space optical communications, optical wireless communications, nondirect optical communications, diffuse reflection, Lambertian diffusion, emergency communications, drone-assisted communication, disaster-struck areas.

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“…Further, the authors of [8] proposed a joint subcarrier and power allocation method based on the access mechanism. Furthermore, in [9], the authors developed a traffic-load aware channel allocation mechanism for secondary users with respect to their applications' QoS requirements. Besides, the authors of [10] proposed a new dynamic spectrum allocation algorithm to resolve channel conflict problems in channel switching in the vehicle network.…”

Section: B Related Workmentioning

confidence: 99%

Approaches to Improve Millimeter-Wave Spectrum Utilization Using Indoor Small Cells in Multi-Operator Environments Toward 6G

Saha

2020

IEEE Access

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In this paper, we propose two spectrum utilization improvement approaches (SUIAs), namely SUIA 1 and SUIA 2, based on whether or not the licensed 28 GHz millimeter-wave (mmWave) spectrum is allocated equally to each mobile network operator (MNO) in a country. Principally, SUIA 1 concerns with improving spectrum utilization if the 28 GHz spectrum is allocated equally to each MNO statically, also termed as static licensed spectrum allocation (SLSA). Whereas, SUIA 2 concerns with improving spectrum utilization if the spectrum is allocated unequally to each MNO in a flexible manner, also termed as flexible licensed spectrum allocation (FLSA). Since sharing and reusing of the licensed spectrum allocated to each MNO using either SLSA or FLSA can be exploited, and the secondary spectrum trading is required only in case of SLSA to redistribute the assigned spectra among MNOs, SUIA 1 employs SLSA, spectrum trading, spectrum sharing, and spectrum reusing techniques, whereas SUIA 2 employs FLSA, spectrum sharing, and spectrum reusing techniques. We present mathematical models for each technique and derive average capacity, spectral efficiency (SE), and energy efficiency (EE) metrics for SUIA 1 and SUIA 2. Extensive numerical and simulation results and analyses for SUIA 1 and SUIA 2 are carried out. It is shown that the spectrum reusing technique influences mostly SE and EE performances. Moreover, SE and EE performances of an MNO in SUIA 1 do not differ considerably from that in SUIA 2 such that depending on the spectrum allocation policies and practices in a country, either SUIA 1 or SUIA 2 can be employed. Finally, it is shown that by applying both SUIA 1 and SUIA 2, the prospective average SE and average EE requirements for sixth-generation (6G) mobile networks can be satisfied.

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Traffic-load aware spectrum allocation in cloud assisted cognitive radio networks

Cited by 6 publications

References 8 publications

Adaptive Channel Assignment With Predictions of Sensor Results and Channel Occupancy Ratio in PhyC-SN

Adaptive Channel Assignment With Predictions of Sensor Results and Channel Occupancy Ratio in PhyC-SN

RESTORE: Low-Energy Drone-Assisted NLoS-FSO Emergency Communications

Approaches to Improve Millimeter-Wave Spectrum Utilization Using Indoor Small Cells in Multi-Operator Environments Toward 6G

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