Name
Abstract | ||
|---|---|---|
The optimal modulation and coding scheme (MCS) for wireless transmission depends on the dynamic wireless channel state. Hence, wireless link adaptation relies on periodically reported channel quality index (CQI) values to select the optimal MCS for each transmission instance. However, to optimize link performance for a given wireless environment, current link adaptation techniques rely on tuning parameters such as a block error rate (BLER) target and algorithm adjustments that are difficult to optimize heuristically. Here, we propose BayesLA, a Bayesian link adaptation scheme that does not require careful parameter tuning for optimal link performance in diverse wireless environments. BayesLA, which is inspired by the Thompson Sampling approach widely used for online learning, efficiently learns the MCS success probabilities conditioned on the reported CQI values. Through numerical simulations for a Rayleigh fading wireless channel and a typical cellular link configuration, we demonstrate that BayesLA outperforms state-of-the-art outer loop link adaptation (OLLA) approach in terms of the realized link throughput for a given BLER target. |
Year | DOI | Venue |
|---|---|---|
2020 | 10.1109/SPAWC48557.2020.9154253 | 2020 IEEE 21st International Workshop on Signal Processing Advances in Wireless Communications (SPAWC) |
Keywords | DocType | ISSN |
BayesLA,MCS success probabilities,reported CQI values,typical cellular link configuration,state-of-the-art outer loop link adaptation approach,realized link throughput,given BLER target,optimal modulation,coding scheme,wireless transmission,dynamic wireless channel state,wireless link adaptation,periodically reported channel quality index,optimal MCS,transmission instance,given wireless environment,current link adaptation techniques,algorithm adjustments,Bayesian link adaptation scheme,careful parameter tuning,optimal link performance,diverse wireless environments | Conference | 1948-3244 |
ISBN | Citations | PageRank |
978-1-7281-5479-4 | 1 | 0.38 |
References | Authors | |
5 | 2 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Vidit Saxena | 1 | 25 | 4.61 |
| Joakim Jalden | 2 | 243 | 21.59 |