OPE2: Advanced Wireless and Network Solutions for 5G
Thursday, 10 June 2021, 9:30-11:00, Zoom Room
Session Chair:Jean-Marie Gorce (INSA Lyon, France)
Anika Seufert and Florian Wamser (University of Wuerzburg, Germany); Stefan Wunderer (Nokia Solutions and Networks, Germany); Andrew Hall (Tutela Technologies Ltd., Canada); Tobias Hoßfeld (University of Würzburg, Germany)
Network operators, regulators, and big data companies use crowdsourced measurements to study the performance of mobile networks on a large scale. Such a type of measurement is defined as the collection and processing of data measured by the crowd, here the crowd of mobile subscribers. Crowdsourced network measurements make it relatively easy and inexpensive to obtain large amounts of network data that also reflect the quality actually received by the end user. However, this measurement method also involves some uncertainties, since, for example, it is not possible to precisely control when, where and with which devices measurements are taken. Thus, there is a trade-off between the reliability of the individual measurement and the scope of the measurements. Therefore, how data of this type is analyzed is particularly important in order to obtain valid results. To address this issue, our paper defines concepts and guidelines for analyzing the validity of crowdsourced mobile network measurements. In particular, we address precision, for example the number of measurements needed to make valid statements, and also representativeness, for example the spatial and temporal distribution of the data. In addition to the formal definition of these two aspects, we illustrate the issue and possible evaluation approaches with the help of an extensive example data set. This data set consists of more than 11.7M crowdsourced mobile measurements from all over France, measured by a commercial mobile data provider. In the end, we provide an evaluation guideline and two possible use cases.
Sung Woo Choi, Seung Nam Choi, Dae-Soon Cho and Junhyeong Kim (ETRI, Korea (South)); Gosan Noh (Electronics and Telecommunications Research Institute, Korea (South)); Jung Pil Choi (Mobile Communications Research Lab., Electronics and Telecommunications Research Institute, Korea (South)); Hee Sang Chung (ETRI, Korea (South))
This paper presents test results of a wireless backhaul technology, Moving Network(MN), in highway environment. The MN has been developed to enhance passengers’ Internet speed in buses. It uses a wide bandwidth of 600 MHz in 22 GHz frequency to achieve higher data rate but suffers from worse wireless channel condition. In this paper, specific features of the MN technology are briefly summarized, and then highway test environment and test method are introduced. Testbed includes a central office, a terminal equipment and 5 base-stations along about 3 km route. Test results show that the maximum data rate is 2.7 Gbps and structural conditions of the road are an important factor of system performance.
Kim Pettersson (Karlstad University & Ericsson Research, Sweden); Ali Parichehreh and Joel Berglund (Ericsson Research, Sweden); Anna Brunstrom (Karlstad University, Sweden)
The 5G wireless networks support diverse use-cases particularly ultra-reliable low-latency communications (URLLC). One of the key challenges in supporting URLLC services is to enhance the performance of the random access procedure to guarantee the stringent latency requirements. This is not only challenging for URLLC services but any delay sensitive services like voice over LTE (VoLTE) or voice over New Radio (VoNR). The access and mobility procedures rely on the random access procedure. Enhancing this procedure using artificial intelligence can thus support even more stringent latency requirements. In this paper, we present an experimental study aiming at performance evaluation of the access and mobility procedures based on an experimentation and data collection from the Monroe measurement platform. We study the main causes of the latency induced to the access and mobility procedures and evaluate techniques based on machine learning that enable the User Equipment (UE) to take appropriate actions for coping with predicted sub-optimal access or mobility procedures.
Kenichi Takizawa, Ryotaro Suga, Takashi Matsuda and Fumihide Kojima (National Institute of Information and Communications Technology, Japan)
This paper gives an analysis on channel capacity of MIMO communications with radio-frequency (RF) signals in seawater, in which zero-forcing (ZF) is introduced in order to mitigate interference among transmitted data streams. It is shown that, by setting the antenna spacing of both the transmit and receive sides to more than 0.33 of the wavelength determined by electrical characteristics of seawater, MIMO communications brings channel capacity close to upper-bound. Also, it is derived that the MIMO communications is robust on the variance of the electrical conductivity of seawater through evaluation on the channel capacity. Experiment on 2×2 MIMO communications has been conducted in the shallow water. The results of the experiment show that MIMO transmission with bitrate of 1 Mbps at payload has been demonstrated with 64 QAM communications in carrier frequency of 1 MHz.