Optimal Cell Clustering and Activation for Energy Saving in Load-Coupled Wireless Networks
Optimizing activation and deactivation of base station transmissions provides an instrument for improving energy efficiency in cellular networks. In this paper, we study the problem of performing cell clustering and setting the activation time of each cluster, with the objective of minimizing the su...
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Veröffentlicht in: | IEEE transactions on wireless communications 2015-11, Vol.14 (11), p.6150-6163 |
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creator | Lei, Lei Yuan, Di Ho, Chin Keong Sun, Sumei |
description | Optimizing activation and deactivation of base station transmissions provides an instrument for improving energy efficiency in cellular networks. In this paper, we study the problem of performing cell clustering and setting the activation time of each cluster, with the objective of minimizing the sum energy, subject to a time constraint of serving the users' traffic demand. Our optimization framework accounts for inter-cell interference, and, thus, the users' achievable rates depend on cluster formation. We provide mathematical formulations and analysis, and prove the problem's NP hardness. For problem solution, we first apply an optimization method that successively augments the set of variables under consideration, with the capability of approaching global optimum. Then, we derive a second solution algorithm to deal with the trade-off between optimality and the combinatorial nature of cluster formation. Numerical results demonstrate that our solutions achieve more than 40% energy saving over existing schemes, and that the solutions we obtain are within a few percent of deviation from global optimum. |
doi_str_mv | 10.1109/TWC.2015.2449295 |
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In this paper, we study the problem of performing cell clustering and setting the activation time of each cluster, with the objective of minimizing the sum energy, subject to a time constraint of serving the users' traffic demand. Our optimization framework accounts for inter-cell interference, and, thus, the users' achievable rates depend on cluster formation. We provide mathematical formulations and analysis, and prove the problem's NP hardness. For problem solution, we first apply an optimization method that successively augments the set of variables under consideration, with the capability of approaching global optimum. Then, we derive a second solution algorithm to deal with the trade-off between optimality and the combinatorial nature of cluster formation. Numerical results demonstrate that our solutions achieve more than 40% energy saving over existing schemes, and that the solutions we obtain are within a few percent of deviation from global optimum.</description><identifier>ISSN: 1536-1276</identifier><identifier>ISSN: 1558-2248</identifier><identifier>EISSN: 1558-2248</identifier><identifier>DOI: 10.1109/TWC.2015.2449295</identifier><identifier>CODEN: ITWCAX</identifier><language>eng</language><publisher>New York: IEEE</publisher><subject>Activation energy ; Algorithms ; cell activation ; cell clustering ; Clustering ; Clusters ; column generation ; Energy conservation ; energy minimization ; Formations ; Indexes ; Interference ; load coupling ; Mathematical model ; Mathematical models ; Optimization ; Quality of service ; Resource management ; Scheduling ; Signal to noise ratio</subject><ispartof>IEEE transactions on wireless communications, 2015-11, Vol.14 (11), p.6150-6163</ispartof><rights>Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) Nov 2015</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c404t-3916a18da098b74e1a79f40d834a487530b42af14dc1ab803c70a1771e194b8e3</citedby><cites>FETCH-LOGICAL-c404t-3916a18da098b74e1a79f40d834a487530b42af14dc1ab803c70a1771e194b8e3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/7132788$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>230,314,552,780,784,796,885,27923,27924,54757</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/7132788$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc><backlink>$$Uhttps://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-123331$$DView record from Swedish Publication Index$$Hfree_for_read</backlink></links><search><creatorcontrib>Lei, Lei</creatorcontrib><creatorcontrib>Yuan, Di</creatorcontrib><creatorcontrib>Ho, Chin Keong</creatorcontrib><creatorcontrib>Sun, Sumei</creatorcontrib><title>Optimal Cell Clustering and Activation for Energy Saving in Load-Coupled Wireless Networks</title><title>IEEE transactions on wireless communications</title><addtitle>TWC</addtitle><description>Optimizing activation and deactivation of base station transmissions provides an instrument for improving energy efficiency in cellular networks. In this paper, we study the problem of performing cell clustering and setting the activation time of each cluster, with the objective of minimizing the sum energy, subject to a time constraint of serving the users' traffic demand. Our optimization framework accounts for inter-cell interference, and, thus, the users' achievable rates depend on cluster formation. We provide mathematical formulations and analysis, and prove the problem's NP hardness. For problem solution, we first apply an optimization method that successively augments the set of variables under consideration, with the capability of approaching global optimum. Then, we derive a second solution algorithm to deal with the trade-off between optimality and the combinatorial nature of cluster formation. Numerical results demonstrate that our solutions achieve more than 40% energy saving over existing schemes, and that the solutions we obtain are within a few percent of deviation from global optimum.</description><subject>Activation energy</subject><subject>Algorithms</subject><subject>cell activation</subject><subject>cell clustering</subject><subject>Clustering</subject><subject>Clusters</subject><subject>column generation</subject><subject>Energy conservation</subject><subject>energy minimization</subject><subject>Formations</subject><subject>Indexes</subject><subject>Interference</subject><subject>load coupling</subject><subject>Mathematical model</subject><subject>Mathematical models</subject><subject>Optimization</subject><subject>Quality of service</subject><subject>Resource management</subject><subject>Scheduling</subject><subject>Signal to noise ratio</subject><issn>1536-1276</issn><issn>1558-2248</issn><issn>1558-2248</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2015</creationdate><recordtype>article</recordtype><sourceid>RIE</sourceid><sourceid>D8T</sourceid><recordid>eNpd0UtLxDAUBeAiCj73gpuAGzcdc5O0SZdDHR8w6MIXuAlpeztEa1OTVvHfm2HEhZski-9ecjhJcgx0BkCL84fncsYoZDMmRMGKbCvZgyxTKWNCba_fPE-ByXw32Q_hlVKQeZbtJS93w2jfTUdK7OLRTWFEb_sVMX1D5vVoP81oXU9a58miR7_6Jvfmcw1sT5bONGnppqHDhjxbjx2GQG5x_HL-LRwmO63pAh793gfJ4-XiobxOl3dXN-V8mdaCijHlBeQGVGNooSopEIwsWkEbxYURSmacVoKZFkRTg6kU5bWkBqQEhEJUCvlBkm72hi8cpkoPPgby39oZqy_s01w7v9KdnTQwzjlEf7bxg3cfE4ZRv9tQx_imRzcFHXcrmolcqEhP_9FXN_k-pomKcwYFlXlUdKNq70Lw2P59Aahel6NjOXpdjv4tJ46cbEYsIv5xCZxJpfgPiImJhg</recordid><startdate>20151101</startdate><enddate>20151101</enddate><creator>Lei, Lei</creator><creator>Yuan, Di</creator><creator>Ho, Chin Keong</creator><creator>Sun, Sumei</creator><general>IEEE</general><general>The Institute of Electrical and Electronics Engineers, Inc. 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In this paper, we study the problem of performing cell clustering and setting the activation time of each cluster, with the objective of minimizing the sum energy, subject to a time constraint of serving the users' traffic demand. Our optimization framework accounts for inter-cell interference, and, thus, the users' achievable rates depend on cluster formation. We provide mathematical formulations and analysis, and prove the problem's NP hardness. For problem solution, we first apply an optimization method that successively augments the set of variables under consideration, with the capability of approaching global optimum. Then, we derive a second solution algorithm to deal with the trade-off between optimality and the combinatorial nature of cluster formation. 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subjects | Activation energy Algorithms cell activation cell clustering Clustering Clusters column generation Energy conservation energy minimization Formations Indexes Interference load coupling Mathematical model Mathematical models Optimization Quality of service Resource management Scheduling Signal to noise ratio |
title | Optimal Cell Clustering and Activation for Energy Saving in Load-Coupled Wireless Networks |
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