TY - JOUR
T1 - A low-complexity cell clustering algorithm in dense small cell networks
AU - Seno, Ryuma
AU - Ohtsuki, Tomoaki
AU - Jiang, Wenjie
AU - Takatori, Yasushi
N1 - Publisher Copyright:
© 2016, The Author(s).
PY - 2016/12/1
Y1 - 2016/12/1
N2 - Clustering plays an important role in constructing practical network systems. In this paper, we propose a novel clustering algorithm with low complexity for dense small cell networks, which is a promising deployment in next-generation wireless networking. Our algorithm is a matrix-based algorithm where metrics for the clustering process are represented as a matrix on which the clustering problem is represented as the maximization of elements. The proposed algorithm simplifies the exhaustive search for all possible clustering formations to the sequential selection of small cells, which significantly reduces the clustering process complexity. We evaluate the complexity and the achievable rate with the proposed algorithm and show that our algorithm achieves almost optimal performance, i.e., almost the same performance achieved by exhaustive search, while substantially reducing the clustering process complexity.
AB - Clustering plays an important role in constructing practical network systems. In this paper, we propose a novel clustering algorithm with low complexity for dense small cell networks, which is a promising deployment in next-generation wireless networking. Our algorithm is a matrix-based algorithm where metrics for the clustering process are represented as a matrix on which the clustering problem is represented as the maximization of elements. The proposed algorithm simplifies the exhaustive search for all possible clustering formations to the sequential selection of small cells, which significantly reduces the clustering process complexity. We evaluate the complexity and the achievable rate with the proposed algorithm and show that our algorithm achieves almost optimal performance, i.e., almost the same performance achieved by exhaustive search, while substantially reducing the clustering process complexity.
KW - Cell clustering algorithm
KW - Small cell networks
UR - http://www.scopus.com/inward/record.url?scp=84995655537&partnerID=8YFLogxK
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U2 - 10.1186/s13638-016-0765-3
DO - 10.1186/s13638-016-0765-3
M3 - Article
AN - SCOPUS:84995655537
VL - 2016
JO - Eurasip Journal on Wireless Communications and Networking
JF - Eurasip Journal on Wireless Communications and Networking
SN - 1687-1472
IS - 1
M1 - 262
ER -