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  4. Fractional Programming for Communication Systems—Part II: Uplink Scheduling via Matching - 2018
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Category: MTech DSP Projects
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MTech Projects
28.Nov
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Fractional Programming for Communication Systems—Part II: Uplink Scheduling via Matching - 2018

PROJECT TITLE :

Fractional Programming for Communication Systems—Part II: Uplink Scheduling via Matching - 2018

ABSTRACT:

This two-half paper develops novel methodologies for using fractional programming (FP) techniques to design and optimize communication systems. Part I of this Project proposes a new quadratic remodel for FP and treats its application for continuous optimization problems. In this Half II of the paper, we have a tendency to study discrete issues, like those involving user scheduling, which are considerably additional difficult to resolve. Unlike the continuous issues, discrete or mixed discrete-continuous problems normally can't be recast as convex issues. In contrast to the common heuristic of relaxing the discrete variables, this work reformulates the original drawback in an FP type amenable to distributed combinatorial optimization. The paper illustrates this technique by tackling the necessary and challenging downside of uplink coordinated multicell user scheduling in wireless cellular systems. Uplink scheduling is additional difficult than downlink scheduling, as a result of uplink user scheduling choices considerably have an effect on the interference pattern in nearby cells. Furthermore, the discrete scheduling variable wants to be optimized jointly with continuous variables like transmit power levels and beamformers. The main plan of the proposed FP approach is to decouple the interaction among the interfering links, thereby allowing a distributed and joint optimization of the discrete and continuous variables with provable convergence. The paper shows that the well-known weighted minimum mean-sq.-error (WMMSE) algorithm can additionally be derived from a specific use of FP; however our proposed FP-primarily based method considerably outperforms WMMSE when discrete user scheduling variables are concerned, both in term of run-time potency and optimizing results.

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