arXiv subjects

Sebastian Schiessl

Publications and source records attributed to Sebastian Schiessl.

7 recordsLinked to original sources

arXiv2020

Coordinates-based Resource Allocation Through Supervised Machine Learning

Appropriate allocation of system resources is essential for meeting the increased user-traffic demands in the next generation wireless technologies. Traditionally, the system relies on channel state information (CSI) of the users for optimizing the resource allocation, which becomes costly for fast-varying channel conditions. Considering that future wireless technologies will be based on dense network deployment, where the mobile terminals are in line-of-sight of the transmitters, the position information of terminals provides an alternative to estimate the channel condition. In this work, we propose a coordinates-based resource allocation scheme using supervised machine learning techniques, and investigate how efficiently this scheme performs in comparison to the traditional approach under various propagation conditions. We consider a simplistic system set up as a first step, where a single transmitter serves a single mobile user. The performance results show that the coordinates-based resource allocation scheme achieves a performance very close to the CSI-based scheme, even when the available coordinates of terminals are erroneous. The proposed scheme performs consistently well with realistic-system simulation, requiring only 4 s of training time, and the appropriate resource allocation is predicted in less than 90 microseconds with a learnt model of size less than 1 kB.

cs.LG↗

arXiv2019

NOMA in the Uplink: Delay Analysis with Imperfect CSI and Finite-Length Coding

We study whether using non-orthogonal multiple access (NOMA) in the uplink of a mobile network can improve the performance over orthogonal multiple access (OMA) when the system requires ultra-reliable low-latency communications (URLLC). To answer this question, we first consider an ideal system model with perfect channel state information (CSI) at the transmitter and long codewords, where we determine the optimal decoding orders when the decoder uses successive interference cancellation (SIC) and derive closed-form expressions for the optimal rate when joint decoding is used. While joint decoding performs well even under tight delay constraints, NOMA with SIC decoding often performs worse than OMA. For low-latency systems, we must also consider the impact of finite-length channel coding, as well as rate adaptation based imperfect CSI. We derive closed-form approximations for the corresponding outage or error probabilities and find that those effects create a larger performance penalty for NOMA than for OMA. Thus, NOMA with SIC decoding may often be unsuitable for URLLC.

cs.IT↗

arXiv2018

Delay Performance of the Multiuser MISO Downlink under Imperfect CSI and Finite Length Coding

We use stochastic network calculus to investigate the delay performance of a multiuser MISO system with zero-forcing beamforming. First, we consider ideal assumptions with long codewords and perfect CSI at the transmitter, where we observe a strong channel hardening effect that results in very high reliability with respect to the maximum delay of the application. We then study the system under more realistic assumptions with imperfect CSI and finite blocklength channel coding. These effects lead to interference and to transmission errors, and we derive closed-form lower and upper bounds on the resulting error probability. Compared to the ideal case, imperfect CSI and finite length coding cause massive degradations in the average transmission rate. Surprisingly, the system nevertheless maintains the same qualitative behavior as in the ideal case: as long as the average transmission rate is higher than the arrival rate, the system can still achieve very high reliability with respect to the maximum delay.

cs.IT↗

arXiv2018

On the Reliability of LTE Random Access: Performance Bounds for Machine-to-Machine Burst Resolution Time

Random Access Channel (RACH) has been identified as one of the major bottlenecks for accommodating massive number of machine-to-machine (M2M) users in LTE networks, especially for the case of burst arrival of connection requests. As a consequence, the burst resolution problem has sparked a large number of works in the area, analyzing and optimizing the average performance of RACH. However, the understanding of what are the probabilistic performance limits of RACH is still missing. To address this limitation, in the paper, we investigate the reliability of RACH with access class barring (ACB). We model RACH as a queuing system, and apply stochastic network calculus to derive probabilistic performance bounds for burst resolution time, i.e., the worst case time it takes to connect a burst of M2M devices to the base station. We illustrate the accuracy of the proposed methodology and its potential applications in performance assessment and system dimensioning.

cs.IT↗

arXiv2018

Delay Performance of the Multiuser MISO Downlink

We analyze a MISO downlink channel where a multi-antenna transmitter communicates with a large number of single-antenna receivers. Using linear beamforming or nonlinear precoding techniques, the transmitter can serve multiple users simultaneously during each transmission slot. However, increasing the number of users, i.e., the multiplexing gain, reduces the beamforming gain, which means that the average of the individual data rates decreases and their variance increases. We use stochastic network calculus to analyze the queueing delay that occurs due to the time-varying data rates. Our results show that the optimal number of users, i.e., the optimal trade-off between multiplexing gain and beamforming gain, depends on incoming data traffic and its delay requirements.

cs.IT↗

arXiv2017

Delay Performance of Wireless Communications with Imperfect CSI and Finite Length Coding

With the rise of critical machine-to-machine applications, next generation wireless communication systems must be designed with strict constraints on the latency and reliability. A key question in this context relates to channel state estimation, which allows the transmitter to adapt the code rate to the channel. In this work, we characterize the trade-off between the estimation sequence length and data codeword length: shorter channel estimation leaves more time for the actual payload transmission but reduces the estimation accuracy and causes more decoding errors. Using lower coding rates can mitigate this effect, but may result in a higher backlog of data at the transmitter. We analyze this trade-off using queueing analysis on top of accurate models of the physical layer, which also account for the finite blocklength of the channel code. Based on a novel closed-form approximation for the error probability given the rate, we show that finding the optimal rate adaptation strategy becomes a convex problem. The optimal rate adaptation strategy and the optimal training sequence length, which both depend on the latency and reliability constraints of the application, can improve the delay performance by an order of magnitude, compared to suboptimal strategies that do not consider those constraints.

cs.IT↗

arXiv2016

On the Delay Performance of Interference Channels

A deep understanding of the queuing performance of wireless networks is essential for the advancement of future wireless communications. The stochastic nature of wireless channels in general gives rise to a time varying transmission rate. In such an environment, interference is increasingly becoming a key constraint. Obtaining an expressive model for offered service of such channels has major implications in the design and optimization of future networks. However, interference channels are not well-understood with respect to their higher layer performance. The particular difficulty for handling interference channels arises from the superposition of random fading processes for the signals of the transmitters involved (i.e., for the signal of interest and for the signals of the interferers). Starting from the distribution of the signal-to-interference-plus-noise ratio (SINR), we derive a statistical characterization of the underlying service process in terms of its Mellin transform. Then, we adapt a recent stochastic network calculus approach for fading channels to derive measures of the queuing performance of single- and multi-hop wireless interference networks. Special cases of our solution include noise-limited and interference-limited systems. A key finding of our analysis is that for a given average signal and average sum interference power, the performance of interfered systems not only depends on the relative strength of the sum interference with respect to the signal-of-interest power, but also on the interference structure (i.e., the number of interferers) as well as the absolute levels.

cs.NI↗