Performance and configuration of link adaptation algorithms with mobile speed

Link Adaptation is an adaptive radio link technique that selects a transport mode, from a set of predefined modes of varying robustness, depending on the channel quality conditions and dynamics. Previous work has shown the need to adapt the configuration of the Link Adaptation algorithm to certain operating conditions such as the system load. Since the channel quality dynamics are also influenced by the user speed, this paper investigates the impact of the mobile speed on the performance and configuration of Link Adaptation algorithm

On the importance of using appropriate link-to-system interfaces for the study of link adaptation

Link Adaptation is an adaptive radio link technique that selects a transport mode, from a set of predefined modes of varying robustness, depending on the channel quality conditions and dynamics. It is therefore very important, when analysing the performance and operation of Link Adaptation, to properly capture such conditions and dynamics. In this context, this paper investigates the effect that different link-to-system level interfaces have on the study of Link Adaptation, in particular on its throughput performance and associated signalling cost

Link level modelling techniques for analysing the configuration of link adaptation algorithms in mobile radio networks

The operation of Link Adaptation algorithms is based on channel quality estimates. It is therefore important to analyse the performance of such algorithms with link level models that properly capture the channel conditions and dynamics. Previous research [1] concluded that the use of simple link level models does not give an accurate prediction of the estimated performance of Link Adaptation algorithms. Following this previous work, this paper shows that the link level model considered for the study of Link Adaptation algorithms can also influence the decisions regarding the optimum configuration of the algorithm

Evaluation, Modeling and Optimization of Coverage Enhancement Methods of NB-IoT

Narrowband Internet of Things (NB-IoT) is a new Low Power Wide Area Network (LPWAN) technology released by 3GPP. The primary goals of NB-IoT are improved coverage, massive capacity, low cost, and long battery life. In order to improve coverage, NB-IoT has promising solutions, such as increasing transmission repetitions, decreasing bandwidth, and adapting the Modulation and Coding Scheme (MCS). In this paper, we present an implementation of coverage enhancement features of NB-IoT in NS-3, an end-to-end network simulator. The resource allocation and link adaptation in NS-3 are modified to comply with the new features of NB-IoT. Using the developed simulation framework, the influence of the new features on network reliability and latency is evaluated. Furthermore, an optimal hybrid link adaptation strategy based on all three features is proposed. To achieve this, we formulate an optimization problem that has an objective function based on latency, and constraint based on the Signal to Noise Ratio (SNR). Then, we propose several algorithms to minimize latency and compare them with respect to accuracy and speed. The best hybrid solution is chosen and implemented in the NS-3 simulator by which the latency formulation is verified. The numerical results show that the proposed optimization algorithm for hybrid link adaptation is eight times faster than the exhaustive search approach and yields similar latency

Outage-based ergodic link adaptation for fading channels with delayed CSIT

Link adaptation in which the transmission data rate is dynamically adjusted according to channel variation is often used to deal with time-varying nature of wireless channel. When channel state information at the transmitter (CSIT) is delayed by more than channel coherence time due to feedback delay, however, the effect of link adaptation can possibly be taken away if this delay is not taken into account. One way to deal with such delay is to predict current channel quality given available observation, but this would inevitably result in prediction error. In this paper, an algorithm with different view point is proposed. By using conditional cdf of current channel given observation, outage probability can be computed for each value of transmission rate $R$. By assuming that the transmission block error rate (BLER) is dominated by outage probability, the expected throughput can also be computed, and $R$ can be determined to maximize it. The proposed scheme is designed to be optimal if channel has ergodicity, and it is shown to considerably outperform conventional schemes in certain Rayleigh fading channel model