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RA-OABC: An Optimal Framework for Resource Assignment in WCDMA Networks Using Oppositional Artificial Bee Colony Algorithm with Repair Strategies

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Abstract

In this paper, we propose a new optimal framework with repair strategy to resolve major issues in the assignment of resources to mobile terminals (plainly to users) in WCDMA networks. The main goal of this proposed approach is to tackle the issues in the assignment of resources such as (1) load factor, (2) total capacity, (3) power, (4) channelization codes and (5) user’s not including any of the service. Our proposed RA-OABC approach adopts the repair strategy for the replacement of resource which violates the weight factor condition (i.e. Φ ≤ 1). The resource replacement is practiced just by removing the unfeasible resource and substituting it with new feasible resource (repaired versions). The oppositional artificial bee colony (OABC) algorithm acts well on the groups (assignment of users to the base stations) in a very efficient manner. Moreover, our proposed approach also exhibits a superior performance than that of the conventional technique by means of users receiving the requested services with increased availability of resources. The experimental study for the proposed RA-OABC approach is effectively carried out on various scenarios: the different number of users, user’s profiles, effects on the distributions of different number of user’s and so on.

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Authors and Affiliations

  1. Department of Computer Science & Engineering, Calcutta Institute of Technology, Kolkata, India

    Safikul Alam S & Sourabh Chandra

  2. Department of Computer Science & Engineering, Jadavpur University, Kolkata, India

    Swapan Bhattacharya

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  1. Safikul Alam S
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  2. Sourabh Chandra
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  3. Swapan Bhattacharya
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Safikul Alam S, Chandra, S. & Bhattacharya, S. RA-OABC: An Optimal Framework for Resource Assignment in WCDMA Networks Using Oppositional Artificial Bee Colony Algorithm with Repair Strategies. Wireless Pers Commun 103, 1535–1562 (2018). https://doi.org/10.1007/s11277-018-5867-2

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