User Scheduling and Power Allocation for Precoded Multi-Beam High Throughput Satellite Systems with Individual Quality of Service Constraints
For extensive coverage areas, multi-beam high throughput satellite (MB-HTS) communication is a promising technology that plays a crucial role in delivering broadband services to many users with diverse Quality of Service (QoS) requirements. This paper focuses on MB-HTS systems where all beams reuse...
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Main Authors | , , , , |
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Format | Journal Article |
Language | English |
Published |
06.10.2021
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Subjects | |
Online Access | Get full text |
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Summary: | For extensive coverage areas, multi-beam high throughput satellite (MB-HTS)
communication is a promising technology that plays a crucial role in delivering
broadband services to many users with diverse Quality of Service (QoS)
requirements. This paper focuses on MB-HTS systems where all beams reuse the
same spectrum. In particular, we propose a novel user scheduling and power
allocation design capable of providing guarantees in terms of the individual
QoS requirements while maximizing the system throughput under a limited power
budget. Precoding is employed in the forward link to mitigate mutual
interference at the users in multiple-access scenarios over different coherence
time intervals. The combinatorial optimization structure from user scheduling
requires an extremely high cost to obtain the global optimum even when a
reduced number of users fit into a time slot. Therefore, we propose a heuristic
algorithm yielding good trade-off between performance and computational
complexity, applicable to a static operation framework of geostationary (GEO)
satellite networks. Although the power allocation optimization is signomial
programming, non-convex on a standard form, the solution can be lower bounded
by the global optimum of a geometric program with a hidden convex structure. A
local solution to the joint user scheduling and power allocation problem is
consequently obtained by a successive optimization approach. Numerical results
demonstrate the effectiveness of our algorithms on large-scale systems by
providing better QoS satisfaction combined with outstanding overall system
throughput. |
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DOI: | 10.48550/arxiv.2110.02525 |