Link Adaptation Using Dynamically Allocated Thresholds and Power Control

Saha, Jyoti Prasad; Das, Suvra Sekhar; Mukherjee, S. K.

doi:10.1007/s11277-018-5908-x

Cited by 8 publications

(2 citation statements)

References 36 publications

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“…The rest of this paper is structured as follows: In Section II, we highlight the existing LA schemes, summarize their relative advantages and drawbacks, and outline the contributions made in this paper. Next, in Section III, we describe the cellular link model and the link performance 1 Common OLLA implementations often short-circuit the OLM by pre-computing MCS switching thresholds as a function of the SINR [8]- [10]. However, in this paper, we show that exploiting the full power of the OLM can substantially improve the link performance.…”

Section: Introductionmentioning

confidence: 98%

Reinforcement Learning for Efficient and Tuning-Free Link Adaptation

Saxena¹,

Tullberg²,

Jaldén³

2020

Preprint

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Link adaptation (LA) optimizes the selection of modulation and coding schemes (MCS) for a stochastic wireless channel. The classical outer loop LA (OLLA) tracks the channel's signal-to-noiseand-interference ratio (SINR) based on the observed transmission outcomes. On the other hand, recent Reinforcement learning LA (RLLA) schemes sample the available MCSs to optimize the link performance objective. However, both OLLA and RLLA rely on tuning parameters that are challenging to configure.Further, OLLA optimizes for a target block error rate (BLER) that only indirectly relates to the common throughput-maximization objective, while RLLA does not fully exploit the inter-dependence between the MCSs. In this paper, we propose latent Thompson Sampling for LA (LTSLA), a RLLA scheme that does not require configuration tuning, and which fully exploits MCS inter-dependence for efficient learning. LTSLA models an SINR probability distribution for MCS selection, and refines this distribution through Bayesian updates with the transmission outcomes. LTSLA also automatically adapts to different channel fading profiles by utilizing their respective Doppler estimates. We perform simulation studies of LTSLA along with OLLA and RLLA schemes for frequency selective fading channels. Numerical results demonstrate that LTSLA improves the instantaneous link throughout by up to 50% compared to existing schemes.

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Section: Introductionmentioning

confidence: 98%

Reinforcement Learning for Efficient and Tuning-Free Link Adaptation

Saxena¹,

Tullberg²,

Jaldén³

2020

Preprint

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“…Adaptive Modulation and Coding (AMC) is a well-known technique to undergo link adaptation and a vast research has been carried out in this domain where modulation order and code rate are varied w.r.t. the fluctuating channel conditions [15][16][17]. Currently, various AMC algorithms are available for either single carrier based i.e.…”

Section: Introductionmentioning

confidence: 99%

Dynamic Link Adaptation For Filterband Multicarrier In Networks With Diverse Service Quality And Throughput Requirements

Tiwana

Zeeshan

Ashraf

et al. 2021

Preprint

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The fast evolution in wireless communication standards and enhancement in cellular applications has created an exponential rise in the data rate requirement over the past few decades. The next generation wireless standards, therefore, need not only to provide ultra high data rates with minimum latency, but also to support diverse quality-of-service (QoS) requirements. Filterbank multicarrier (FBMC) scheme provides quite a few advantages over the conventional orthogonal frequency division multiplexing (OFDM) for future wire- less networks. In order to achieve adaptive throughput and diverse service quality requirements under varying channel conditions, a link adaptation algorithm for FBMC scheme is proposed in this paper. The aim is to provide the dynamic selection of optimum parameters resulting in diverse modes of operation to ensure the desired and/or best available communication service quality. The proposed link adaptation algorithm incorporates the parameters of required data rate, available channel condition and QoS demand, and dynamically allocates the appropriate FBMC transmission parameters. The proposed scheme has been evaluated for AWGN as well as multipath fading SUI channel models. Simulation results indicate that the proposed algorithm successfully achieves the desired service quality subject to the availability of suitable channel conditions and is also superior to the existing algorithms in terms of block error rate and effective throughput.

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