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# Neighbor Discovery and Tracking in mm-Wave Networks

## Introduction

During the summer term 2014 the project 'Neighbor Discovery and Tracking in mm-Wave Networks' was conducted in the Department of Telecommunication Systems. The goal was to investigate theoretically communication stations using mm-waves. Based on physical facts a simulation was developed with MatLab in which different discovery and tracking strategies can be tested.

## Physical Aspects

For a few years mm-waves are a popular research topic in communication technology because a successful use would make very high transfer rates possible. The interesting frequencies of mm-waves are located between 30 GHz and 300 GHz. At 60 GHz a license-free band is available where the attenuation is relatively high. Therefore the range is limited.

## Directional Communication

An introduced concept is directed communication. Steerable Antennas are able radiate the electromagnetic Power in one direction only. On one hand energy is concentrated in that region so that the range is increasing. On the other hand it is no longer possible to cover an area omnidirectionally. A new concept for an algorithm covering all directions appropriately is required. The simple omnidirectional neighbor discovery is also no longer possible whereby new mechanisms must be introduced. Mainly a controlled sending and listening order in different direction must be established. Then efficient detection of partners and high transfer rates can be realized.

## Beamforming

A technology to realize directed communication is called beamforming. Due to the Huygens–Fresnel principle an antenna array with a certain input signal will cause a constructive superposition of the waves in the desired steer direction.

Theoretically the far field differs from the near field but in our approach it is considered to be the same. To reach thin and accurate beams the number of antennas will be increased. The received power will be higher in the steer direction as a result and therefore the link quality is better.

## Neighbor Discovery

Detection describes the recognition of another communication station. In our case the detection is complete when the direction of the partner is determined in the most accurate beam pattern. Also both partners have to listen/send with pointing their beams at each other simultaneously.

## Tracking

During the project another aspect was investigated. After the first detection of a communication partner a priori knowledge can be used in the next detection step. Under certain circumstances the search can be reduced to a small sector around the old position. As a result a fractional amount of steps is required to find the partner again. But there is also the risk, that the partner could 'escape' from that window. The simulation shows a compromise between fullscans and tracking is the best way.

## Signal Power

The received signal power is calculated with the formula:
$P(R)=\frac{P(T) \cdot G(T) \cdot G(R)}{PL}$ (in dB: $P(R)=P(T)+G(T)+G(R)-PL)$
where $P(T)$ is the transmitted power, $G(T)$ and $G(R)$ are the antenna gains and $PL$ is the path loss.

## Results

The simulation shows that a compromise between full scans and tracking is most promising. If the full scans are repeated too frequently time slots will be used without significant quality gain. If the frequency is too low the quality of link can collapse due to rotation of a station or reflection at walls. The right balance between both modes has to be determined. Adaptive approaches should also be considered as an alternative. In that case the algorithm would analyze the situation and choose an appropriate full scan frequency.