On the efficiency of retransmission schemes for the open area mm-wave device-to-device environment
Description
TitleOn the efficiency of retransmission schemes for the open area mm-wave device-to-device environment
Date Created2020
Other Date2020-10 (degree)
Extent1 online resource (xv, 119 pages) : illustrations
DescriptionOne of the differentiating characteristics of the next generation of wireless networks is its operation in the mm-wave bands. Technology developers aim to accomplish data rates of up to ten gigabits per second with an overall latency of less than 1 ms by leveraging the abundant bandwidth in the mm-wave spectrum. However, relative to the spectrum in use today, this comes with two major challenges.
Firstly, mm-wave signals suffer from a greater propagation loss. This can be addressed by beamforming to provide directional gains. Secondly, mm-waves are susceptible to penetration loss due to the presence of buildings, vehicles, foliage, or humans in the environment. Such a loss in the signal quality due to environmental objects is collectively referred to as the blockage effect. Link outage due to the blockage effect can impact several mechanisms such as beam setup, beamtracking, modulation, and coding. Restoring the link quality may become prohibitively expensive in such scenarios, especially for the 5G NR use cases requiring sub-millisecond latency.
Communication in the mm-wave spectrum amidst blockages raises the question: Is a line-of-sight (LOS) connection between the transmitter and the receiver possible? To investigate and study the mm-wave channel, we implement the spatial channel model (SCM) specified by 3GPP for 5G new radio (NR). Mm-wave cluster propagation mechanism motivated the analysis of the impact of practical issues such as beam misalignment in the presence of blockages. Further, we leverage the blockage modeling procedures specified to derive an approximate empirical model for the probability of LOS in the outdoor Urban Microcell-Street Canyon (UMi-SC) scenario. However, obtaining the LOS probability alone is not sufficient to model the small scale fading characteristics of the channel. To model small scale fading in a tractable manner, we provide a stochastic blockage model that not only gives the probability of LOS but also gives the approximate average signal attenuation as a soft metric that quantifies the extent of the blockage.
To model the blockage effect, we utilize the 2D homogeneous Poisson Point Process inside a circular spatial geometry. Blocker presence in a circular geometry can be directly applied to an environment where blockers are randomly placed around the receiver in all directions. Such an environment is commonly found in application scenarios that fall under the 3GPP use cases of massive Machine Type Communication (mMTC) and direct device-to-device (D2D) communication for 5G NR. Examples are public safety networks, warehouse and industrial robotics, wearable technology, and tactical networks. Due to the scalable nature of the circular geometry, our approach also lends itself to the modeling of reflections in the environment of operation. The loss due to a blocker is approximated using a double knife edge diffraction (DKED) method. The accuracy of the approximate and tractable analytical model is confirmed with the help of Monte Carlo simulations for real-world blocker placement in the environment.
The model is applied to analyze the impact of blockages on two Hybrid Automatic Repeat reQuest (HARQ) retransmission schemes, namely, Chase combining (CC) and Incremental Redundancy (IR). A trade-off between the beamforming accuracy (expressed in terms of beam misalignment) and the efficiency (expressed in terms of throughput) is presented. Thus providing insight into the choice of beamwidth as a function of the blockage effect for the environment in which the system is deployed.
NotePh.D.
NoteIncludes bibliographical references
Genretheses, ETD doctoral
LanguageEnglish
CollectionSchool of Graduate Studies Electronic Theses and Dissertations
Organization NameRutgers, The State University of New Jersey
RightsThe author owns the copyright to this work.
Statistical Profile