An Optimization-based Approach to Flow Control and Resource Allocation Problem in Satellite Communication Systems

Author(s):  
Gun Akkor ◽  
John Baras ◽  
Michael Hadjitheodosiou
2020 ◽  
Vol 2020 ◽  
pp. 1-10
Author(s):  
Guomei Gan ◽  
Yanhu Huang ◽  
Qiang Wang

Device to device (D2D) communication has recently attracted a lot of attentions since it can significantly improve the system throughput and reduce the energy consumption. Indeed, the devices can communicate with each other in a D2D system, and the base station (BS) can share the spectrum with D2D users, which can efficiently improve the spectrum and energy efficiency. Nevertheless, spectrum sharing also raises the difficulty of resource allocation owing to the serious cochannel interference. To reduce the interference, the transmit power of the D2D pairs and BS to cellular users should be further optimized. In this paper, we consider the resource allocation problem of D2D networks involving the power allocation and subcarrier assignment. The resource allocation problem is formulated as a mixed integer programming problem which is difficult to solve. To reduce the computational complexity, the original problem is decomposed as two subproblems in terms of the subcarrier assignment and power allocation. For the subcarrier assignment problem, the particle swarm optimization (PSO) is adopted to solve it since the subcarrier assignment is an integer optimization problem, and it is difficult to be tackled using the traditional optimization approach. When the subcarrier assignment is fixed, there are only the power allocation variables in the original resource allocation problem. The difference of convex functions (DC) programming is adopted to solve the power allocation problem. Simulation results demonstrate the effectiveness of the proposed resource allocation scheme of D2D networks.


2016 ◽  
Vol 12 (1) ◽  
pp. 103-113 ◽  
Author(s):  
Mohammed Ibrahim ◽  
Haider AlSabbagh

A considerable work has been conducted to cope with orthogonal frequency division multiple access (OFDMA) resource allocation with using different algorithms and methods. However, most of the available studies deal with optimizing the system for one or two parameters with simple practical condition/constraints. This paper presents analyses and simulation of dynamic OFDMA resource allocation implementation with Modified Multi-Dimension Genetic Algorithm (MDGA) which is an extension for the standard algorithm. MDGA models the resource allocation problem to find the optimal or near optimal solution for both subcarrier and power allocation for OFDMA. It takes into account the power and subcarrier constrains, channel and noise distributions, distance between user's equipment (UE) and base stations (BS), user priority weight – to approximate the most effective parameters that encounter in OFDMA systems. In the same time multi dimension genetic algorithm is used to allow exploring the solution space of resource allocation problem effectively with its different evolutionary operators: multi dimension crossover, multi dimension mutation. Four important cases are addressed and analyzed for resource allocation of OFDMA system under specific operation scenarios to meet the standard specifications for different advanced communication systems. The obtained results demonstrate that MDGA is an effective algorithm in finding the optimal or near optimal solution for both of subcarrier and power allocation of OFDMA resource allocation.


2012 ◽  
Vol 2012 ◽  
pp. 1-10 ◽  
Author(s):  
Shahaf I. Wayer ◽  
Arie Reichman

The high cost of frequency bandwidth in satellite communication emphasizes the need for good algorithms to cope with the resource allocation problem. In systems using DVB-S2 links, the optimization of resource allocation may be related to the classical multi-knapsack problem. Resource management should be carried out according to the requests of subscribers, their priority levels, and assured bandwidths. A satisfaction measure is defined to estimate the allocation processes. Heuristic algorithms together with some innovative scaling schemes are presented and compared using Monte Carlo simulation based on a traffic model introduced here.


2009 ◽  
Author(s):  
Reza Ahmadi ◽  
Sriram Dasu ◽  
Foaad Iravani

1985 ◽  
Vol 28 (9) ◽  
pp. 994-1004 ◽  
Author(s):  
James R. Slagle ◽  
Henry Hamburger

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