Dynamic downlink resource allocation for wireless networks with inter-cell interference

Karthik, P; Kumaran, G.

doi:10.1109/icices.2014.7033941

Cited by 2 publications

(3 citation statements)

References 11 publications

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“…Gang et al [17] proposed a proportional fair scheduling based on the radio resource allocation method for the multi-cell orthogonal frequency division multiple access system. Karthik et al [18] proposed a greedy power allocation method, which achieved significant performance improvement for cell-edge users and desirable performance for cell-centre users. Unlike these prior works that only considered real-time resource allocation, we perform the RR before the resource allocation process, which reserves the channel resource for each BS according to the predicted maximum number of the existing services.…”

Section: Related Workmentioning

confidence: 99%

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Virtual resource mapping in inter‐cell interference‐constrained ultra‐dense networks

et al. 2021

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Ultra-dense networking is considered an effective solution to achieve high capacity in 5G networks. However, the densely distributed base stations (BSs) in ultra-dense networks (UDNs) make the inter-cell interference much more serious than that in traditional cellular networks. Therefore, it is important to mitigate inter-cell interference in the UDNs to improve network performance. To tackle this problem, we propose a novel virtual resource mapping algorithm that includes a resource reservation (RR) algorithm and a real-time resource embedding (RE) algorithm. Specifically, according to the number of services predicted by a dynamic service model, the RR algorithm is proposed to determine the sets of multiplexing BSs in the next time cycle and reserve channel resource required by each BS. Then, to further reduce inter-cell interference, the real-time RE algorithm is proposed to allocate the channel resource in real time. Finally, simulation results show that the proposed algorithm has better performance in terms of signal-to-interference-plus-noise ratio and acceptance ratio, compared to the existing algorithms, such as the frequency reuse channel allocation algorithm and inter-cell interference coordination algorithm.

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Section: Related Workmentioning

confidence: 99%

“…To mitigate the inter-cell interference, several existing works [14][15][16][17][18] studied different resource allocation methods. Lopez-Perez et al [14] proposed autonomous and coordinated resource allocation algorithms combined with the selforganisation rule and the resource allocation limits.…”

Section: Related Workmentioning

confidence: 99%

Virtual resource mapping in inter‐cell interference‐constrained ultra‐dense networks

et al. 2021

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“…Bai et al [16] proposal allocates resources in an environment with different quality of service demands (streams with different sizes and latencies); Keerthana & Vinoth [17] propose to allocate resources in two phases: in the first one, they use the geographical location of users to build a graph to mitigate interference, and in the second one, they allocate frequency resources by using said graph. With respect to formulating the optimization model: Feshke et al [13] , propose optimizing spectral efficiency by using a profit function; Keertana & Vinoth [17] , Rajamannar & Vijaya [18] , and Karthik & Kumaran [19] , formulate a model to maximize throughput for users at the edge of the cell, subject to throughput fulfillment of users close to the base station. This formulation punishes users at the edge of the cell, because they are not offered full service guarantees, thus its fairness is questionable.…”

Section: Problem Formulationsmentioning

confidence: 99%

Mid-Term frequency domain scheduler for resource allocation in wireless mobile communications systems

Pachón

García-Palomares

2017

Computer Communications

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This article approaches the dynamic resource allocation problem for the downlink of a wireless mobile communication system (WMCS). The article defines the architecture and functions of the global resource scheduler, as well as the quality index for scheduling, the signal to interference-plus-noise ratio (SINR). The proposed approach divides the scheduling task into two components: a distributed one, with local, short-term scope; and a centralized one, with global, medium-term scope. The optimization model considers a set of slack variables for guaranteeing feasibility. This allows the service provider to fully satisfy the users' service demands. The model type is mixed, non-linear, which demands large computational power for an exact solution. So an approximate strategy is used, in order to decouple the search space

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Dynamic downlink resource allocation for wireless networks with inter-cell interference

Cited by 2 publications

References 11 publications

Virtual resource mapping in inter‐cell interference‐constrained ultra‐dense networks

Virtual resource mapping in inter‐cell interference‐constrained ultra‐dense networks

Mid-Term frequency domain scheduler for resource allocation in wireless mobile communications systems

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