MITSUBISHI Project B:
Title

Optimization of wireless base station placement as an essential foundation for our future IoTsociety
Industrial Partner: Information Technology R&D Center of Mitsubishi Electric Corp.
Mitsubishi Electric is a world leader in the manufacture and sales of electrical andelectronic products and systems used in a broad range of fields and applications. As aglobal leader among green companies, our technologies are being applied to contribute toand support society and daily life around the world. The Information Technology R&D
Center is actively creating new businesses through basic research and development in thefields of information technology, media intelligence, electro-optics microwaves, andcommunication technologies. We are also seeking technologies that reinforce our positionon the leading edge of progress, with work to renew existing businesses through the fruitsof our R&D in the field of IT.
Industry Mentors

Takahiro Hashimoto, Mitsubishi Electric Corp.
Kenya Shimizu, Mitsubishi Electric Corp.

Introduction

Continuous development of wireless communication technologies has led to creation ofvarious IoT applications [1]. Among them, 5G technology [2] is the most promising. The
generation of a mobile communication standard has been upgraded almost every decade.
Now, the 5G wireless communication standard has been launched with numerous attractive
features: enhanced mobile broadband (eMBB), massive machine type communications(mMTC), and ultra-reliable and low latency communications (URLLC). These features will
establish 5G technology as a firm foundation for future IoT society.
For 5G, the radio frequency band is to be licensed not only to mobile operators but also
to private system developers such as manufacturers. That transformation will alter theindustry structure, creating a wide range of business opportunities in automobiles, industrialequipment, home security, and smart meters. That is one reason why we are keenly
developing wireless technology.

Construction of an efficient system demands the smooth and rapid development anddeployment of new wireless systems. The basic requirements of wireless systems are fewerbase stations, complete coverage, and broad band throughput. Most importantly, to use
limited radio frequency resources efficiently, such systems must not interfere with othersystems. Accurate placement design is important, but the coverage evaluation of a realenvironment requires great costs and time.
Expectations

The purpose of the project is creation of an efficient and reliable optimization algorithm

to ascertain the positions and directions of wireless base stations to reduce the costs andtime for designing wireless systems. The optimization algorithm accepts the spatial
distribution of radio signal strength (RSS) to evaluate the cost function. Therefore, we provide
a propagation model that can predict the RSS. Participants can change the propagation
model input parameters such as the base station position, direction, transmitting power, andthe design environment geometry. Then, the propagation model predicts RSS considering
the transmission loss which occurs when radio waves pass through walls and when multiple
reflections of radio waves occur on the wall.
The design dimensions largely determine the problem difficulty. Base stations arerestricted in a one-dimensional space in wireless train control systems [3,4], whereas thepositions are in two- or three-dimensional space for general placement design [5]. Typically,
the target number of base stations is a few hundred for train control systems, or a few dozen
for general placement design. Because of the curse of dimensionality, solving optimization
problems becomes extremely difficult as the parameter space increases. We encourage
participants to create an algorithm for two- or three-dimensional design space, which is morechallenging and worth trying in terms of larger parameter space. For example, the resulting
method can be applicable to wireless design for large indoor areas (e.g. factories) or foroutdoor areas (e.g. urban environments).
Conventional methods have typically used combinational optimization. In recent years,
several studies have examined analytical methods using topology (e.g. persistent homology)[6] or graph theory [7]. We encourage participants to propose formulation using thesemathematical structures of coverage and interference and efficient optimization algorithms
that are applicable to larger parameter spaces.

Requirements

We welcome students who are motivated to tackle application-oriented and practicalproblems encountered by manufacturers. Students must have knowledge of optimization. In
addition, it is desirable that they have the following knowledge.
Programming (e.g. Python, MATLAB)

TopologyGraph theory

References[1] Internet of Things (IoT),
https://internetofthingsagenda.techtarget.com/definition/Internet-of-Things-IoT.
[2] Mitsubishi Electric Begins Demonstrating Local 5G System in Japan,
https://emea.mitsubishielectric.com/en/news/releases/global/2020/0518-a/index.html, May
18, 2020.
[3] Wikipedia, Communication-based train control
https://en.wikipedia.org/wiki/Communications-based_train_control[4] N. Sood, et al., "Integrating Physics-Based Wireless Propagation Models and Network
Protocol Design for Train Communication Systems," in IEEE Transactions on Antennas andPropagation, vol. 66, no. 12, pp. 6635-6645, Dec. 2018.
[5] E. Arribas, et al., "Coverage Optimization with a Dynamic Network of Drone Relays," inIEEE Transactions on Mobile Computing, vol. 19, no. 10, pp. 2278-2298, 1 Oct. 2020.
[6] Coverage in sensor networks via persistent homology,
https://www2.math.upenn.edu/~ghrist/preprints/persistent.pdf[7] M. Lin, Q. Ye and Y. Ye, "Graph theory based mobile network insight analysis framework,"
2016 IEEE 7th Annual Ubiquitous Computing, Electronics & Mobile Communication
Conference (UEMCON), New York, NY, 2016, pp. 1-7.