Combinatorial optimization: algorithms and complexity
Combinatorial optimization: algorithms and complexity
An analytical approach to floorplan design and optimization
DAC '90 Proceedings of the 27th ACM/IEEE Design Automation Conference
Network flows: theory, algorithms, and applications
Network flows: theory, algorithms, and applications
Faster approximation algorithms for generalized flow
Proceedings of the tenth annual ACM-SIAM symposium on Discrete algorithms
Faster and Simpler Algorithms for Multicommodity Flow and other Fractional Packing Problems.
FOCS '98 Proceedings of the 39th Annual Symposium on Foundations of Computer Science
Sequential and Parallel Algorithms for Mixed Packing and Covering
FOCS '01 Proceedings of the 42nd IEEE symposium on Foundations of Computer Science
A fast approximation scheme for fractional covering problems with variable upper bounds
SODA '04 Proceedings of the fifteenth annual ACM-SIAM symposium on Discrete algorithms
A Multi-Radio Unification Protocol for IEEE 802.11 Wireless Networks
BROADNETS '04 Proceedings of the First International Conference on Broadband Networks
Characterizing the capacity region in multi-radio multi-channel wireless mesh networks
Proceedings of the 11th annual international conference on Mobile computing and networking
Subcarrier Allocation and Bit Loading Algorithms for OFDMA-Based Wireless Networks
IEEE Transactions on Mobile Computing
A compensation mechanism for bandwidth allocation in IP wireless networks
ICACT'10 Proceedings of the 12th international conference on Advanced communication technology
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We study the resource allocation problem in multi-tone frame based broadband wireless access systems. Frequency and time resources must be allocated by a central controller (Base Station) to a number of users. We consider variations of a resource allocation problem, some of which are difficult to solve. Situations in which only the objective of the Base Station need to be maximized are easily dealt with as are cases where all the users perceive the same channel conditions. Scenarios where both the objectives of the BS as well as those of the end users must be met simultaneously require more complicated solutions since individual users experience different channel conditions. We present linear programming relaxations for the resource allocation problem. While solving the LP using standard techniques like ellipsoidal algorithm can provide optimal allocations for all users, it can be expensive in terms of computing overhead as the number of users in the system increase. Therefore we present an efficient algorithm which performs well even as the number of clients n, and the number of channels m in the system increases. We also present a heuristic based on the interpretation of the linear programming relaxation as a concurrent flow problem. We note that in numerical experiments, the performance of the heuristic closely matches the optimal solution to the linear programming relaxation. Extensions of the basic formulation to scenarios where the clients use simple radios and to network scenarios where the clients can be multi-homed are presented. We discuss how the solution to the LP leads to a realizable schedule in all the above formulations. We also present a Mixed Integer Programming formulation for a scenario in which the signaling overhead incurred due to communication of these computed allocations is reduced, and provide initial directions on the joint power and slot assignment problem.