Optimal Power Allocation For Multiple Beam Satellite Systems

IEEE RAWCON 2007

Extended Summary

In the past, commercial satellites did not have the ability to support multiple beams on-board. Presently, most of the commercial satellites have the ability to support multiple spot beams enabling services to diverse geographical region. Unfortunately, all the geographical regions do not have the same capacity requirement. Neither does the future demand follow the same progression. This has led to a very interesting problem, namely how do you increase or decrease capacity adaptively based on the increase or decrease in user/service demand? Satellites do have the ability to service large number of users, albeit cumulatively. Satellites, when launched, are engineered to cater to future demands as it is expected to stay in service for at least a few decades. However, many remote areas may not use efficiently the capacity to their maximum due to sparse population, while high demands might come from an urban center. Therefore, it is a real challenge to redistribute the capacity in order to optimize the revenue.

Adaptive power and rate control techniques for satellite communication systems over time-varying satellite channels have been applied to achieve an order of magnitude or more data throughputs. Some attempts have been made to adjust power for an optimal resource allocation in on-board processor, e.g., [1]. In addition, service providers such as Telesat® [2] are investing time and money to adopt innovative solutions to allocate spot beams and to increase revenue. As part of future missions, multiple spot-beam satellites are being launched with the ability to allocate power dynamically and to increase throughput, because on-board resources (e.g., power, bandwidth, transmitters, receivers and spot-beams) are scarce and expensive. It is critical to share them efficiently among as many users as possible.

There are multiple ways to accomplish the end goal of increasing revenue. One of the methods to allocate power is to decrease power in some areas while increasing power in others where there is surge in user demands. Another method is to allocate multiple spot beams over a geographical area allowing timesharing of active downlink beams. A data satellite network would have to support a broad spectrum of bursty unscheduled users with different constraints over time varying atmospheric satellite channels [3, 4]. It is desirable to use agile scanning beam systems, adaptive to service requirements and channel conditions, and time-share a small number of active downlink beams, since onboard resources are expensive and broadband satellite will have many spot beam coverage cells within its service area. The paper [1] proves that there is significant power gain and advantage of fairness with optimized power allocation. In both the cases, the issue of providing efficient resource allocation and channel access should be considered together with system performance guarantees on throughput and delay for individual spot-beams. On the other hand, the extremely long communication propagation distance decreases signal power significantly so that current emerging capacity (or power) allocation schemes for wireless communication systems are not supported by satellite system standard [5].

Currently the conventional schemes provide the excess fixed capacity for multi-spot beam satellite (e.g., TeleSat® ANIK F2) to guarantee any user demands with full resource reservation. However, in addition to guaranteed QoS (Quality of Service) (i.e., defined later), satellite service providers (e.g., our industrial partner TeleSat®) expect to increase the revenue by introducing more subscribers, therefore maximizing limited resource utilization becomes necessary.

In this paper, we would like to optimize bandwidth allocation among multiple spot beams. To achieve this, we set up the formulation of general power allocation optimization problem for multiple beam satellite systems. Then we propose an innovative power allocation algorithm for the system. We use heuristic method to search the Lagrange multiplier and obtain the optimal power allocation for each spot beam in order to meet the total power constraint and individual SLA constraint together. Scilab® simulation demonstrates that our algorithm not only maximizes the power utilization of the satellite, but also guarantees the minimum user demand of each spot beam.

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