Abstract:
Recently, 3GPP has introduced licensed-assisted access (LAA) for long-term evolution (LTE) operation in 5 GHz unlicensed band to meet ever-increasing data traffic in cell...Show MoreMetadata
Abstract:
Recently, 3GPP has introduced licensed-assisted access (LAA) for long-term evolution (LTE) operation in 5 GHz unlicensed band to meet ever-increasing data traffic in cellular networks. However, the link adaptation scheme of the conventional LTE, adaptive modulation and coding (AMC), cannot operate well in unlicensed band due to intermittent collisions. Intermittent collisions make LAA eNB lower modulation and coding scheme (MCS) for the subsequent transmission and such unnecessarily lowered MCS significantly degrades spectral efficiency. To address this problem, we propose a collision-aware link adaptation algorithm (COALA). COALA exploits k- means unsupervised clustering algorithm to discriminate channel quality indicator (CQI) reports which are measured with collision interference and selects the most suitable MCS for the next transmission. By prototype-based experiments, we demonstrate that COALA detects collisions accurately, and by conducting ns-3 simulations in various scenarios, we also show that COALA achieves up to 74.9% higher user perceived throughput than AMC.
Published in: 2018 15th Annual IEEE International Conference on Sensing, Communication, and Networking (SECON)
Date of Conference: 11-13 June 2018
Date Added to IEEE Xplore: 28 June 2018
ISBN Information:
Electronic ISSN: 2155-5494