Online frequency allocation in cellular networks

Chan, Joseph; Chin, F.; Ye, Deshi; Zhang, Yong

doi:10.1145/1248377.1248418

Cited by 22 publications

(37 citation statements)

References 20 publications

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“…In the online frequency assignment problem, when a call request arrives, the network must immediately assign a frequency to this call without any interference. There are mainly three strategies: Fixed Allocation [6], Greedy Assignment [2], and Hybrid Assignment [4]. If the duration of each call is infinity and the assigned frequency cannot be changed, the hybrid algorithm gave the best result for the online frequency assignment, i.e., a 2-competitive algorithm for the absolute performance and a 1.9126-competitive algorithm for the asymptotic performance.…”

Section: Related Workmentioning

confidence: 99%

Online call control in cellular networks revisited

Zhang

Chin

Ting

et al. 2012

Information Processing Letters

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Wireless Communication Networks based on Frequency Division Multiplexing (FDM in short) play an important role in the field of communications, in which each request can be satisfied by assigning a frequency. To avoid interference, each assigned frequency must be different from the neighboring assigned frequencies. Since frequencies are scarce resources, the main problem in wireless networks is how to fully utilize the given bandwidth of frequencies. In this paper, we consider the online call control problem. Given a fixed bandwidth of frequencies and a sequence of communication requests arriving over time, each request must be either satisfied immediately after its arrival by assigning an available frequency, or rejected. The objective of the call control problem is to maximize the number of accepted requests. We study the asymptotic performance of this problem, i.e., the number of requests in the sequence and the bandwidth of frequencies are very large. In this paper, we give a 7/3-competitive algorithm, say CACO, for the call control problem in cellular networks, improving the previous 2.5-competitive result, and show that CACO is best possible among a class of HYBRID algorithms.

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Section: Related Workmentioning

confidence: 99%

Online call control in cellular networks revisited

Zhang

Chin

Ting

et al. 2012

Information Processing Letters

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“…As in this paper we focus only on the asymptotic ratio, we will skip the word "asymptotic" (unless ambiguity can arise), and simply use terms "R-competitive" and "competitive ratio" instead. Following the terminology in the literature (see [5,6]), we will say that the competitive ratio is absolute when the additive constant λ is equal 0.…”

Section: Introductionmentioning

confidence: 99%

Better Bounds for Incremental Frequency Allocation in Bipartite Graphs

Chrobák

Jeż

Sgall

2011

Algorithms – ESA 2011

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We study frequency allocation in wireless networks. A wireless network is modeled by an undirected graph, with vertices corresponding to cells. In each vertex we have a certain number of requests, and each of those requests must be assigned a different frequency. Edges represent conflicts between cells, meaning that frequencies in adjacent vertices must be different as well. The objective is to minimize the total number of used frequencies.The offline version of the problem is known to be NP-hard. In the incremental version, requests for frequencies arrive over time and the algorithm is required to assign a frequency to a request as soon as it arrives. Competitive incremental algorithms have been studied for several classes of graphs. For paths, the optimal (asymptotic) ratio is known to be 4/3, while for hexagonal-cell graphs it is between 1.5 and 1.9126. For ξ-colorable graphs, the ratio of (ξ + 1)/2 can be achieved.In this paper, we prove nearly tight bounds on the asymptotic competitive ratio for bipartite graphs, showing that it is between 1.428 and 1.433. This improves the previous lower bound of 4/3 and upper bound of 1.5. Our proofs are based on reducing the incremental problem to a purely combinatorial (equivalent) problem of constructing set families with certain intersection properties.

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“…For the online version, there are mainly three strategies, which have been well studied: the fixed allocation assignment (FAA) [11], the greedy algorithm (Greedy) [5] and the hybrid algorithm [4]. FAA partitions cells into independent sets which are each assigned a separate set of frequencies.…”

Section: Introductionmentioning

confidence: 99%

“…Chan et al [3] closed the gap and proved that Greedy is 17/7-competitive. Furthermore, Chan et al [4] gave a 2-competitive algorithm, say hybrid, which can be regarded as a combination of FAA and Greedy. Since the lower bound of competitive ratio of frequency allocation in cellular networks is also 2, hybrid is optimal.…”

Section: Introductionmentioning

confidence: 99%

A 1-Local Asymptotic 13/9-Competitive Algorithm for Multicoloring Hexagonal Graphs

2008

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In the frequency allocation problem, we are given a mobile telephone network, whose geographical coverage area is divided into cells, wherein phone calls are serviced by assigning frequencies to them so that no two calls emanating from the same or neighboring cells are assigned the same frequency. The problem is to use the frequencies efficiently, i.e., minimize the span of frequencies used. The frequency allocation problem can be regarded as a multicoloring problem on a weighted hexagonal graph. In this paper, we give a 1-local asymptotic 4/3-competitive distributed algorithm for multicoloring a triangle-free hexagonal graph, which is a special case of hexagonal graph. Based on this result, we then propose a 1-local asymptotic 13/9-competitive algorithm for multicoloring the (general-case) hexagonal graph, thereby improving the previous 1-local 3/2-competitive algorithm.

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Online frequency allocation in cellular networks

Cited by 22 publications

References 20 publications

Online call control in cellular networks revisited

Online call control in cellular networks revisited

Better Bounds for Incremental Frequency Allocation in Bipartite Graphs

A 1-Local Asymptotic 13/9-Competitive Algorithm for Multicoloring Hexagonal Graphs

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