A Clustering-Based Approach for Low-Complexity Adaptive Profile Selection in DOCSIS 3.1

Mahdi Ben Ghorbel, Ebrahim Bedeer Mohamed, Jahangir Hossain, Colin Howlett, Brian Berscheid, Julian Cheng

Research output: Contribution to conferencePaper

Abstract

We introduce a low complexity downlink bit-loading for each subcarrier of a large number of cable modems (CMs) in DOCSIS 3.1. Although different modulations between subcarriers are allowed in DOCSIS 3.1, the number of different bit-loading per subcarrier assignments, called profiles, is limited for computational complexity. Thus, an efficient method of determining the best profile to be used by each CM is needed. The proposed approach is based on a two-step algorithm. In the first step, users are clustered into groups based on their signal-to-noise ratio (SNR) while in the second step, the profile per group (i.e., the bit-loading per sub-carrier) is selected. Two different criteria are investigated for this step. The first one considers the average SNR among the users in the cluster to determine the bit-loading while the second one is more conservative and considers the worst SNR among the users in order to guarantee the targeted BER for all the users in the cluster. Through numerical results, we show the efficiency of the two-step approach and compare the two proposed criteria for bit-loading.

Conference

ConferenceConference: 28th Biennial Symposium on Communications (BSC 2016)
CountryCanada
CityKelowna
Period5/06/167/06/16

Fingerprint

Signal to noise ratio
Modems
Cables
Computational complexity
Modulation

Keywords

  • Adaptive Modulation
  • clustering
  • data over cable networks
  • profile optimization.

Cite this

Ben Ghorbel, M., Mohamed, E. B., Hossain, J., Howlett, C., Berscheid, B., & Cheng, J. (Accepted/In press). A Clustering-Based Approach for Low-Complexity Adaptive Profile Selection in DOCSIS 3.1. Paper presented at Conference: 28th Biennial Symposium on Communications (BSC 2016), Kelowna, Canada.
Ben Ghorbel, Mahdi ; Mohamed, Ebrahim Bedeer ; Hossain, Jahangir ; Howlett, Colin ; Berscheid, Brian ; Cheng, Julian. / A Clustering-Based Approach for Low-Complexity Adaptive Profile Selection in DOCSIS 3.1. Paper presented at Conference: 28th Biennial Symposium on Communications (BSC 2016), Kelowna, Canada.
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abstract = "We introduce a low complexity downlink bit-loading for each subcarrier of a large number of cable modems (CMs) in DOCSIS 3.1. Although different modulations between subcarriers are allowed in DOCSIS 3.1, the number of different bit-loading per subcarrier assignments, called profiles, is limited for computational complexity. Thus, an efficient method of determining the best profile to be used by each CM is needed. The proposed approach is based on a two-step algorithm. In the first step, users are clustered into groups based on their signal-to-noise ratio (SNR) while in the second step, the profile per group (i.e., the bit-loading per sub-carrier) is selected. Two different criteria are investigated for this step. The first one considers the average SNR among the users in the cluster to determine the bit-loading while the second one is more conservative and considers the worst SNR among the users in order to guarantee the targeted BER for all the users in the cluster. Through numerical results, we show the efficiency of the two-step approach and compare the two proposed criteria for bit-loading.",
keywords = "Adaptive Modulation, clustering, data over cable networks, profile optimization.",
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Ben Ghorbel, M, Mohamed, EB, Hossain, J, Howlett, C, Berscheid, B & Cheng, J 2016, 'A Clustering-Based Approach for Low-Complexity Adaptive Profile Selection in DOCSIS 3.1' Paper presented at Conference: 28th Biennial Symposium on Communications (BSC 2016), Kelowna, Canada, 5/06/16 - 7/06/16, .

A Clustering-Based Approach for Low-Complexity Adaptive Profile Selection in DOCSIS 3.1. / Ben Ghorbel, Mahdi; Mohamed, Ebrahim Bedeer; Hossain, Jahangir; Howlett, Colin; Berscheid, Brian; Cheng, Julian.

2016. Paper presented at Conference: 28th Biennial Symposium on Communications (BSC 2016), Kelowna, Canada.

Research output: Contribution to conferencePaper

TY - CONF

T1 - A Clustering-Based Approach for Low-Complexity Adaptive Profile Selection in DOCSIS 3.1

AU - Ben Ghorbel, Mahdi

AU - Mohamed, Ebrahim Bedeer

AU - Hossain, Jahangir

AU - Howlett, Colin

AU - Berscheid, Brian

AU - Cheng, Julian

PY - 2016/4/30

Y1 - 2016/4/30

N2 - We introduce a low complexity downlink bit-loading for each subcarrier of a large number of cable modems (CMs) in DOCSIS 3.1. Although different modulations between subcarriers are allowed in DOCSIS 3.1, the number of different bit-loading per subcarrier assignments, called profiles, is limited for computational complexity. Thus, an efficient method of determining the best profile to be used by each CM is needed. The proposed approach is based on a two-step algorithm. In the first step, users are clustered into groups based on their signal-to-noise ratio (SNR) while in the second step, the profile per group (i.e., the bit-loading per sub-carrier) is selected. Two different criteria are investigated for this step. The first one considers the average SNR among the users in the cluster to determine the bit-loading while the second one is more conservative and considers the worst SNR among the users in order to guarantee the targeted BER for all the users in the cluster. Through numerical results, we show the efficiency of the two-step approach and compare the two proposed criteria for bit-loading.

AB - We introduce a low complexity downlink bit-loading for each subcarrier of a large number of cable modems (CMs) in DOCSIS 3.1. Although different modulations between subcarriers are allowed in DOCSIS 3.1, the number of different bit-loading per subcarrier assignments, called profiles, is limited for computational complexity. Thus, an efficient method of determining the best profile to be used by each CM is needed. The proposed approach is based on a two-step algorithm. In the first step, users are clustered into groups based on their signal-to-noise ratio (SNR) while in the second step, the profile per group (i.e., the bit-loading per sub-carrier) is selected. Two different criteria are investigated for this step. The first one considers the average SNR among the users in the cluster to determine the bit-loading while the second one is more conservative and considers the worst SNR among the users in order to guarantee the targeted BER for all the users in the cluster. Through numerical results, we show the efficiency of the two-step approach and compare the two proposed criteria for bit-loading.

KW - Adaptive Modulation

KW - clustering

KW - data over cable networks

KW - profile optimization.

M3 - Paper

ER -

Ben Ghorbel M, Mohamed EB, Hossain J, Howlett C, Berscheid B, Cheng J. A Clustering-Based Approach for Low-Complexity Adaptive Profile Selection in DOCSIS 3.1. 2016. Paper presented at Conference: 28th Biennial Symposium on Communications (BSC 2016), Kelowna, Canada.