Dynamic Power Allocation for Broadband Multi-Beam Satellite Communication Networks

Destounis, Apostolos; Panagopoulos, Athanasios D.

doi:10.1109/lcomm.2011.020111.102201

Cited by 54 publications

(38 citation statements)

References 6 publications

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“…Fig. 2 shows the number of rainy users served for the algorithm in [1], proposed algorithm and the maximum number of users (optimum solution) that can be served, for several different values of net available power. The number of groups i.e.…”

Section: Simulation Resultsmentioning

confidence: 99%

“…We will consider the same system and channel model as described in [1]. Consider a communication satellite that employs M beams for providing broadcast services to N geographically separated users, where N M. Every user requires a minimum threshold power for being served and without loss of generality let it be same for all the users and denote it as P thr .…”

Section: System and Channel Modelmentioning

confidence: 99%

“…The attenuations A c,ij due to clouds, fog, gases and melting layer absorption show very little variation with time and are assumed to be constant [1]. For any user i served by beam j, the condition h ij P s,j ≥ P thr must hold for reliable operation.…”

Section: System and Channel Modelmentioning

confidence: 99%

“…Thus exhaustive search can provide a solution to the optimization problem defined in (7) and (8) but its computational complexity will be O(( N M ) m ) which is very high as N M . The algorithm in [1] employs a greedy approach. The greedy approach forms a set by sorting all the users in increasing order of their power requirement without any consideration of the beam from which they are being served.…”

Section: System and Channel Modelmentioning

confidence: 99%

“…Subsequently, in [12], the trade off between maximum total capacity and proportional fairness was considered. Recently in [1], the problem of maximizing the number of users served has been addressed. It has been shown that using a stochastic model for rain attenuation prediction and a simple dynamic power allocation algorithm, more number of users can be served than the existing static techniques.…”

Section: Introductionmentioning

confidence: 99%

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Flexible and Dynamic Power Allocation in Broadband Multi-Beam Satellites

Srivastava

Chaturvedi

2013

IEEE Commun. Lett.

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For multi-beam broadband satellites operating at 10 GHz and above frequencies, rain attenuation is the dominant impairment factor. Using a stochastic model for rain attenuation prediction and a greedy approach, dynamic power allocation has been recently shown to increase the number of users served than the static technique. This letter proposes a new dynamic power allocation algorithm the novelty of which lies in treating users with similar power requirement as a group, instead of individuals. Thus, without resorting to exhaustive search we are able to serve more number of users than the existing technique.Index Terms-Multi-beam antennas, rain attenuation, satellite communications.

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Section: Simulation Resultsmentioning

confidence: 99%

Section: System and Channel Modelmentioning

confidence: 99%

Section: System and Channel Modelmentioning

confidence: 99%

Section: System and Channel Modelmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Flexible and Dynamic Power Allocation in Broadband Multi-Beam Satellites

Srivastava

Chaturvedi

2013

IEEE Commun. Lett.

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Cognitive beamhopping for spectral coexistence of multibeam satellites

Sharma

Chatzinotas

Ottersten

2014

Satell Commun Network

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SUMMARYHerein, the spectral coexistence scenario of two multibeam satellites over a common coverage area is studied where a primary satellite produces larger beams while a secondary satellite has smaller beams. A novel cognitive beamhopping satellite system is proposed assuming that the secondary gateway is aware of the primary's beamhopping pattern. The performance of the proposed system is evaluated and compared with that of conventional multibeam and beamhopping systems in terms of throughput. It is shown that the proposed system significantly enhances the Spectral Efficiency (SE) in comparison to other systems. Furthermore, a power control technique is applied on the secondary transmission in order to adhere to the primary's interference constraint. It is noted that the total SE increases with the number of secondary users in the full frequency reuse approach. Moreover, the Exclusion Zone (EZ) principle is applied to exploit the regions in which the secondary system can operate without causing harmful interference to the primary system. It is shown that the EZ radius of 8.5 dB is sufficient to protect the primary system perfectly with a significant gain in SE. Finally, it is shown that power control and the EZ methods are suitable for lower and higher values of secondary aggregated interference respectively.

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An online power allocation algorithm based on deep reinforcement learning in multibeam satellite systems

Zhang

Wang

et al. 2020

Satell Commun Network

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SummaryDynamic power allocation (DPA) is the key technique to improve the system throughput by matching the offered capacity with that required among distributed beams in multibeam satellite systems. Existing power allocation studies tend to adopt the metaheuristic optimization algorithms such as the genetic algorithm. The achieved DPA cannot adapt to the dynamic environments due to the varying traffic demands and the channel conditions. To solve this problem, an online algorithm named deep reinforcement learning‐based dynamic power allocation (DRL‐DPA) algorithm is proposed in this paper. The key idea of the proposed DRL‐DPA lies in the online power allocation decision making other than the offline way of the traditional metaheuristic methods. Simulation results show that the proposed DRL‐DPA algorithm can improve the system performance in terms of system throughput and power consumption in multibeam satellite systems.

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Dynamic Power Allocation for Broadband Multi-Beam Satellite Communication Networks

Cited by 54 publications

References 6 publications

Flexible and Dynamic Power Allocation in Broadband Multi-Beam Satellites

Flexible and Dynamic Power Allocation in Broadband Multi-Beam Satellites

Cognitive beamhopping for spectral coexistence of multibeam satellites

An online power allocation algorithm based on deep reinforcement learning in multibeam satellite systems

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