Student Work

Energy Efficiency (EE) has become a key performance indicator for sustainable 5G networks due to the growth of next-generation mobile devices connected to the network and applications with the requirements to preserve energy resources. The relevance of EE increases for Industrial Internet of Things (IIoT) devices, which run on limited energy supported by the batteries not replaced over the lifetime.

Therefore, the development of methods to increase the energy efficiency on the device side has received the attention of academia and industry research. Reducing the continuous monitoring of the PDCCH channels is considered a key factor in increasing the device energy efficiency, especially considering the limited resources.

In this thesis, the student shall focus on the implementation and evaluation of a conditional device paging DRX mechanism to reduce the PDCCH channel monitoring. The mechanism will be evaluated through a 5G based simulator.

• Good knowledge of Python and Matlab.
• Knowledge of mobile networks.

Energy efficiency is one of the key performance requirements in the 5G network to ensure user experience. A portion of devices, especially the Industrial Internet of Things (IIoT), run on limited energy, supported by the batteries not placed over the lifetime.

Therefore, the estimation of the power consumption and battery lifetime has recently received increased attention. Multiple context parameters, such as mobility and traffic arrivals, impact the device's power consumption.

In this thesis, the student shall focus on analysing the impact of different traffic models on the power consumption of user equipment. Different source and aggregated traffic models will be implemented depending on the number of devices n the scenario. The implemented traffic models will be evaluated based on a context-aware power consumption model for the user equipment.

• Good knowledge of Python and Matlab programming.
• Good mathematical background.
• Knowledge mobile networks.

The Wireless Sensor Networks lab offers the opportunity to develop software solutions for the wireless sensor networking system, targeting innovative applications. For the next semester, a position is available to assist the participants in learning the programming environment and during the project development phase. The lab is planned to be held on-site every Tuesday and Thursday from 15:00 to 17:00.

The work can also be carried out remotely if necessary

• Solid knowledge in Wireless Communication: PHY, MAC, and network layers.
• Solid programming skills: C/C++.
• Linux knowledge.
• Experience with embedded systems and microcontroller programming knowledge is preferable.

Due to the rapid increase in the number of mobile phones and other handheld devices, an enormous pressure is placed on the already overloaded cellular networks to provide the required Quality of Service. Heterogeneous networks, with multiple coexisting and collaborating technologies like 5G, WiFi, and LiFi, have emerged as a good solution to increase capacity. 

In order to guarantee optimal coverage, avoid interference and minimize costs, the cellular base stations and WiFi/LiFi access points have to be placed optimally in the environment.

• Working knowledge of Python
• Sound knowledge of Wireless Communication
• Interest to learn new communication technologies
• Experience with optimization problems is an advantage

hansini.vijayaraghavan@tum.de

In this position, the student will evaluate the performance of different 5G Core implementations that will be orchestrated with Kubernetes.

- General knowledge about Mobile Networks (RAN & Core).

- Kubernetes knowledge is a must.

- As projects are written in different language, knowledge of GoLang or C++ is a must. Being familiar with both is a plus.

For this thesis, the student will consider different scenarios for the functional split of the 5G Core VNFs and the impact they have on the overall performance of the Mobile Core Network. 

- General knowledge about Mobile Networks (RAN & Core).

- Strong programming skills. Knowledge of Go (https://golang.org/) is a plus.

The 5G cellular networks are the state-of-the-art cellular networks for the coming 10 years. One of the critical network functions in the 5G core system is the evolved packet gateway or User Plane Function (UPF). The UPF is responsible for carrying the users' packets from the base stations to the data network (like the internet). 

On the other hand, P4 is a promising language for programming packet processors. It can be used to program different networking devices (Software/FPGAs/ASICs/...).

Using P4 to implement the UPF has many advantages in terms of flexibility and scalability. In this work, the student will realize/implement the UPF in P4 language. Then, the advantages of this approach, especially in terms of performance gains, will be evaluated.

-Good programming skills

-Basic Linux knowledge

-Motivation and critical thinking

-Knowledge about LTE, 5G, or P4 is a plus.

Implement a quantized neural network in P4 and evaluate the throughput of feed-forward networks and networks with attention mechanisms on P4 hardware.

The goals of this bachelor’s thesis are:

- Implement a Round-Robin (RR) scheduler

- Implement Maximum Carrier to Interference ratio (Max C/I) scheduler

- Implement Proportional Fair (PF) scheduler

- Evaluate their performance based on the target parameters

- Create a basic GUI for easier evaluation and visualization

Artificial Agents are able to reliably navigate in continuous euclidean spaces. Navigation is a crucial skill for artificial agents on discrete structures, as well. The goal of this thesis is to learn navigation on discrete structures. To task of the student is to adapt existing approaches to navigation on euclidean spaces to discrete graphs. The student should design, train and evaluate a Recurrent Neural Network. The student should perform a qualitative and quantitative evaluation of how well the agent can navigate on the graph. Further, the student should evaluate the firing pattern of neurons in the neural network.

References: https://pubmed.ncbi.nlm.nih.gov/29743670/

- Deep Learning

- Machine Learning

Software-Defined Radio Access Network (SD-RAN) is receiving a lot of attention in 5G networks, since it offers means for a more flexible and programmable mobile network architecture.

The heart of the SD-RAN architecture are the so called SD-RAN controllers. Currently, initial prototypes have been developed and used in commercial and academic testbeds. However, most of the solutions only contain a single SD-RAN controller. Nonetheless, a single controller becomes also a single point of failure for a system, not only due to potential controller failures but also due to a high load induced from the devices in the data plane.

To this end a multi-controller control plane often becomes a reasonable choice. However, a multi-controller control plane renders the communication among the controllers more challenging, since they need to often exchange control information with each other to keep an up to date network state. Unfortunately, currently there is no protocol available for such a communication.

The aim of this work is the development and implementation of an East/West API for SD-RAN controller communication according to 5G stardardization. The protocol should enable the exchange of infromation among the SD-RAN controllers regarding UEs, BSs, wireless channel state and allow for control plane migration among controllers.

• Experience with programming languages Python/C++.
• Experience with socket programming.
• Knowledge about SDN is a must.
• Knowledge about 4G/5G networks is a plus.

Goal is to implement a probabilistic graphical model to represent weighted graphs with overlapping communities.

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Das Thema dieser Bachelorthesis ist die Entwicklung, Optimierung und Evaluation des proprietären Brandmeldebussystems LSNi1 der Firma Bosch Sicherheitssysteme GmbH in Grasbrunn.

Brandmeldeanlagen sind ein bestehender notwendiger Teil der Gebaudetechnik und sollen fur neue vernetzte IoT-Dienste verwendet werden. Aufgrund immer höheren Anforderungen dieser Dienste soll die Datenrate uber den Brandmeldebus gesteigert werden. Zur Zeit wird das Bussystem zur verhaltnismäßig datenarmen Alarmabfrage und Antwort der Netzelemente verwendet. Ein wichtiger Punkt ist dabei, die Systemcharakteristika des Brandmeldesystems nicht zu verschlechtern. Solche Netzwerke sind als Sicherheitssysteme deklariert und mussen daher äußerst zuverlässig in Sachen Ausfallsicherheit und Fehlererkennung sein.

Die Aufgabe besteht darin, eine neue Übertragungstechnik mit höherer Datenrate auf der physikalischen Schicht des Busses zu finden und diese mit Hilfe eines Prototypen umzusetzen. Die Optimierung des Prototypen soll durch Berechnung und Experimentieren mit Systemelementen ausgearbeitet werden. Daraufhin werden verschiedene Testaufbauten, im firmeneigenen Labor getestet. Die dabei aufgenommenen Daten werden über ein entwickeltes Matlab-Evaluierungsprogramm ausgewertet, um eindeutige Aussagen über die Funktionalitat des Systems zu geben. Eine besondere Herausforderung bei Systemen dieser Art sind die hohen Kabellängen und die große Anzahl an Systemelementen auf dem Bus. Mit den ausgewerteten Ergebnissen soll überpruft werden, in welchem Umfang die Datenrate auf dem Bus gesteigert werden kann.

The master’s thesis project “MAC Algorithms for Radio Communication Systems” at Rohde & Schwarz is part of the development of a future wireless aeronautical communication system and includes the following aspects and topics:

• Extension and enhancement of MAC-algorithms for wireless communication with directed antennas and distributed reservation.
• Optimization of throughput and coordination between the users.
• Investigation of the performance w.r.t. protocols of higher layers like TCP and UDP.
• Implementation of these algorithms with interfaces to the network simulator OMNEST/OMNET++.
• Investigation of the performance by simulation.

In the Radio Access Network (RAN), the MAC scheduler is largely inherited across generations in the past, to fit to new networking goals and service requirements. The rapid deployment of new 5G technologies will make upgrading of current ones extremely complicated and difficult to improve and maintain. Therefore, finding new solutions for efficient Radio Resource Scheduling (RRS) is necessary to meet the new KPI targets. 5G networks and beyond use the concept of network slicing by forging virtual instances (slices) of its physical infrastructure. A heterogeneous network requires a more optimized and dynamic RRS approach. In view of the development of SD-RAN controllers and artificial intelligence, new promising tools such as reinforcement learning can be proven useful for such a problem.

In this thesis, a data-driven MAC slice scheduler will be implemented, that maximizes user utility, while learning the optimal slice partitioning ratio. A deep reinforcement learning technique will be used to evaluate the radio resource scheduling and slicing in RAN. The results will be compared with traditional schedulers from the state-of-the-art.

yle="margin-bottom: 11px;">In this thesis, the student will extend a framework developed for managing and orchestrating a cloud environment incorporating P4 programmable devices. The following directions will be explored:

yle="margin-bottom: 11px;">- The routing of flows with given network function chains is considered in the problem formulation.

yle="margin-bottom: 11px;">-Allowing multiple network functions to share the same P4 constructs can also be allowed to further optimize the utilization of the environment.

yle="margin-bottom: 11px;">-The objective function can also penalize placing different NFs belonging to the same chain over different devices because of PCI traversal.

yle="margin-bottom: 11px;"> -Moreover, a hybrid environment, which also includes non-programmable P4 devices, can also be considered.

- Knowledge related to P4 and combinatorial optimization.

Traffic Classification based on Machine Learning becomes more important as encryption becomes more prevalent in communication networks. Training machine learning models requires realistic data. Acquisition of this data is often a manual task. Automation frameworks exist but are difficult to use, are detected and blocked by website operators, and produce qualitatively bad data, i.e., models trained on this data do not generalize.

The task of the student is to develop a Reinforcement Learning based system for data acquisition. The goal is to collect qualitatively good data in an automated manner.

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Technology sovereignty has been defined as the ability of a state or a federation of states to provide the technologies it deems critical for its welfare, competitiveness, and ability to act, and to be able to develop these or source them from other economic areas without one-sided structural dependency [1].

Technology sovereignty is part of innovation and economic sovereignty. It has been classified in two categories: static and dynamic technology sovereignty.

• Static aims at preserving or protecting current technology sovereignty (e.g., be crisis-proof).
• Dynamic aims at assuming an active role in evolving processes and development pathways to proactively shape future developments.

Let us focus on the static technology sovereignty and applied to a data center.

The goal of this thesis is to design a data center able to manage “crisis”. E.g.,

• 1.       unavailability of a component provider –government does not allow a particular provider-,

• 2.       insufficient power –supplying country decreases/stops power delivery-,

• yle="mso-bidi-font-weight: normal;">3.       yle="mso-bidi-font-weight: normal;">untrusted component –misbehaviour of a component-, [5]

• 4.       disconnection from users – problem with network provider(s)

• 5.       etc.

The proposed steps, mainly focused on “crisis 3” are:

• 1.       Modeling of a data center (DC):

yle="margin-left: 72.0pt; mso-add-space: auto; text-indent: -18.0pt; mso-list: l2 level2 lfo2;">a.       Architecture

yle="margin-left: 72.0pt; mso-add-space: auto; text-indent: -18.0pt; mso-list: l2 level2 lfo2;">b.       Servers

yle="margin-left: 72.0pt; mso-add-space: auto; text-indent: -18.0pt; mso-list: l2 level2 lfo2;">c.       Switches

• 2.       Starting with a DC architecture (e.g., fat-tree,  spine-leaf)

yle="margin-left: 72.0pt; mso-add-space: auto; text-indent: -18.0pt; mso-list: l2 level2 lfo2;">a.       For different demands and DC sizes (# servers, # access / TOR switches), find the max. number of failing servers that allow the DC to work as expected. [3] For this purpose, traffic modeling is required for both inter- and intra-DC traffic. The “failures” can be based on the manufacturer (e.g., country, availability, price), on the technology, etc.

yle="margin-left: 72.0pt; mso-add-space: auto; text-indent: -18.0pt; mso-list: l2 level2 lfo2;">b.       We may have to consider multipath TPC ([4]) and also add priorities.

• 3.       Starting at the server level, how to evaluate the sovereignty. Using reliability methods such as RBD modeling, petri nets or Markov Chains evaluate the impact of different server models by adding components, changing interconnections, etc.

• 4.       Extend study and evaluation of different switch architectures

[1] “Technology sovereignty: From demand to concept” HHI report July 2020

[2] “SOVEREIGNTY IN INFORMATION TECHNOLOGY" by SECURITY, SAFETY AND FAIR MARKET ACCESS BY OPENNESS AND CONTROL OF THE SUPPLY CHAIN SOVEREIGNTY IN INFORMATION  TECHNOLOGY WHITE PAPER V1.0, MARCH 2018

[3] K. Bilal et al. “On the Characterization of the Structural Robustness of Data Center Networks”IEEE TRANSACTIONS ON CLOUD COMPUTING, Jan 2013

[4] C. Raiciu et al. “Improving Datacenter Performance and Robustness with Multipath TCP” Sigcomm2011

[5] P. Gill “Understanding Network Failures in Data Centers: Measurement, Analysis, and Implications” Sigcomm2011

[6] G. Wang et al. “What Can We Learn from Four Years of Data Center Hardware Failures?” International Conference on Dependable Systems and Networks (DSN 2017)

Increased interference is one of the main drawbacks of cell densification, which is an important strategy for 5G networks to achieve higher data rates. Function centralization has been proposed as a strategy to counter this problem, by letting the physical or scheduling functions coordinate among one another. The more functions are coordinated, the better their mutual interference can be avoided. Several techniques exist in this regard, ranging from coordinated scheduling to joint transmission and reception. However, experiments showing the effectiveness of implemented interference mitigation techniques under a dynamic functional split adaptation are still missing in the literature. In this thesis, the student will implement, evaluate, and optimize different strategies for mitigating interference in a mobile testbed that changes its functional split at runtime. The student will be provided with a minimally working testbed, which she/he will improve and implement the interference-mitigating techniques on.

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5G Networks are anticipated to support the tremendous growth in the traffic demands and the heterogeneity of future applications. In that regard network slicing paves the way towards programmable and flexible networks. On the other hand, delay critical applications require an additional boost on the performance which solutions like Mobile Edge Computing (MEC) or network caching can provide. 

In this thesis the student shall focus on the algorithmic part of the joint network slicing and edge caching. A solution to efficiently manage the resources in order to provide the required performance is needed. To this aim, learning approaches could potentially be utilized for the resource allocation in order to further improve the performance.

• Good knowledge of simulation environments such as Matlab, Python.
• Good mathematical background. Basic knowledge of network slicing and optimization algorithms is a plus.

In this thesis student will focus on designing and implementing a hierarchical SDN solution for industrial multi-domain TSN network.

kostas.katsalis@huawei.com

LiFi (Light-fidelity) is becoming an increasingly important technology as the unlicensed ISM band gets overcrowded. LiFi, with its high data rates, emerges as a promising solution to provide connectivity using LED lights thereby reducing the interference with other wireless technologies. Due to the unique properties of a visible light communication system, the position of the access points/LEDs/Optical front end (OFE) has a significant effect on the network coverage and illumination level in an indoor area.

The placement of these OFEs is a 3D placement problem. This work involves optimizing the placement of the OFEs given a set of requirements eg. throughput, luminance, etc. Given these requirements the goal is to find the optimal placement such that, for example, throughput is maximized.

Related Reading:-

• H. Haas, L. Yin, Y. Wang and C. Chen, "What is LiFi?," in Journal of Lightwave Technology, vol. 34, no. 6, pp. 1533-1544, 15 March15, 2016, doi: 10.1109/JLT.2015.2510021.

• Uluturk, I., Uysal, I., & Chen, K. C. (2019, January). Efficient 3d placement of access points in an aerial wireless network. In 2019 16th IEEE Annual Consumer Communications & Networking Conference (CCNC) (pp. 1-7). IEEE.

• Python 
• Sound knowledge of Wireless Communication
• Interest to learn new communication technologies
• Experience with optimization problems is an advantage

Congestion control (CC) can help achieve the requirements of today's and future generation data center networks (DCNs): namely high bandwidth, ultra-low latency and stability. There are several state-of-the-art proposals but there is no optimal CC scheme yet. Categorizing the CC schemes into end-host control and in-network scheduling, we at Huawei Munich Research Center believe that in-network scheduling provides faster convergence of transmission rate towards the fair rate of the network as compared to end-host control. A novel in-network scheduling CC algorithm together with an optimal load balancing scheme has been designed for RoCEv2 (RDMA over Converged Ethernet version 2) transport. The proposed CC algorithm leverages in-network telemetry (INT) to estimate link load information and pace traffic accordingly, thereby, reducing congestion. It has optimal packet level scheduling and is traffic insensitive, thus fair to all flows (like that of Processor Sharing). The algorithm is also simple (in terms of simple operations on packet arrival) and can be deployed in the DCN switches. The goal of the algorithm is to minimize the FCT (flow completion time) of large flows and provide a bounded delay for short flows. The load balancing scheme built on top of the optimal scheduling scheme aims to optimize the overall network performance, achieving higher network utilization while guaranteeing the performance of individual flows. We intend to compare this algorithm by simulation in Omnet++ simulator with some state-of-the-art algorithms from which the algorithm derives its motivation.

Age of Information(AoI) is defined as the elapsed time since the generation of the most recent packet. It has been used as a cross-layer metric in remote monitoring and controlling scenarios.

AoI-aware networking & protocol design requires the modification within the communication stack. To that end, our department has set up a testbed that consists of multiple software-defined radios (SDRs) programmed in GNU Radio. This enables us to develop our own solutions, e.g., MAC protocol, routing algorithms etc. to improve e.g. AoI performance at the application layer.

This tasks of this project will consist of:

• Working with the existing setup, that consists of multiple SDRs programmed with GNU Radio / C++
• Scheduling of flows over multi-hop paths between the source and the destination pairs
• Performance analysis and comparison of experimental results to analytical ones from the literature

The project requires:

• Solid C/C++ knowledge and low-level programming
• Python skills are beneficial
• Solid fundamental knowledge in wireless communications
• Having worked with practical implementations of wireless communication devices is a great benefit, such as SDRs or sensor motes (some examples are Telosb Motes, Zolertia Re-motes, ...)

Time Sensitive Networks aim to provide for mechanisms and methods for deterministic delay and jitter in industrial networks. Sources of delay and jitter in a TSN can be numerous, e.g., misconfigured or incorrectly dimensioned TAS schedules, congested egress ports, large clock jitter in distributed time synchronization, congestion at egress / ingress ports of the end-stations, variable switch backplane delays etc. are all possible causes of poor end-to-end performance.

In this work, an existing approach to end-to-end monitoring of transmission delay and jitter will be extended to support for quick identification of source of the anomaly in a TSN scenario (i.e., the root cause). Two or more approaches will be proposed to cater for end-to-end monitoring of TSN streams, relying on:

1) intermediate, pre-placed network TAPs;

2) hardware / software data plane agents capable of telemetry and dynamic re-programming to support the quick identification of anomaly sources for individual streams.

Any resulting overhead of the intermediary monitoring solution will be quantified for consideration in the TSN stream planning. The work will hence implement and validate the monitoring mechanisms in an existing TSN testbed that relies on a Linux-based control plane, and will optionally involve P4-based middlebox devices to serve as intermediate monitoring entities. 

[1] 802.1Qbv - Enhancements for Scheduled Traffic

[2] Improving Network Monitoring and Management with Programmable Data Planes

- Good knowledge of networking concepts and architectures

- Good knowledge and practical experiences with Linux networking

- Good knowledge of Python, C or Rust

- Any prior experience with TSN, P4, SDN is a plus but not mandatory

Industry 4.0 scenarios have introduced the novel requirements for dynamic device-to-device interaction without strict plan-ahead interactions (typical of Industrial Ethernet of the last two decades). For example, the use cases of work piece de-attachment and interacting Automated Guided Vehicles (AGVs) in factory automation impose the need for dynamic inter-connection of distributed industrial applications at runtime [1] without a plan-ahead schedule.

Dynamic TSN stream establishment has been proposed by IEEE802.1 to address scenarios of applications requesting real-time communication services at runtime [2, 3]. TSN schedulers capable of computing the transmission schedules with guaranteed real-time properties (upper-bound constraints on latency, jitter, and guaranteed bandwidth) have accordingly been proposed in the past, however, they have traditionally focused on one-time / offline execution [4].

Combined with the requirement for dynamic and efficient resource (de-)allocation, transmission schedules must generally be adaptable at runtime in order to provide for maximum efficiency in network resource utilization. This work will investigate the runtime adaptation of TSN control and data plane to support for the dynamic stream allocation. Algorithms for adaptation of existing TAS-based schedules with minimal impact on availability (packet loss) and QoS guarantees for running TSN streams will be proposed, implemented, and validated. Novel metrics for stream consistency conservation may need to be proposed by the approach. The resulting approach will eventually be evaluated in NeSTiNg (OMNeT++/INET) simulator and/or a small-scale physical testbed comprising multiple TSN switches and end-stations.

[1] IEC/IEEE 60802 TSN Profile for Industrial Automation - https://1.ieee802.org/tsn/iec-ieee-60802/

[2] P802.1Qdd – Resource Allocation Protocol - https://1.ieee802.org/tsn/802-1qdd/

[3] 802.1Qat - Stream Reservation Protocol -/ http://www.ieee802.org/1/pages/802.1at.html

[4] Dürr et al., No-wait Packet Scheduling for IEEE Time-sensitive Networks (TSN) - https://dl.acm.org/doi/abs/10.1145/2997465.2997494

- Very good knowledge of networking concepts and architectures

- Very good knowledge and practical experiences with Linux networking

- Good knowledge of Python, C, C++ or Rust

- Any prior experience with optimization methods and and tools and OMNeT++  is a plus

- Any prior experience with TSN is a plus

- Any prior experience with SDN is a plus

- Proficient English and/or German communication skills

- Ability to work and pursue solutions under limited supervision

ermin.sakic@siemens.com

blenk@tum.de

andreas.zirkler@siemens.com

Current SD-RAN platforms are only evaluated for small network dimensions due to expensive wireless hardware. However, in order to test the real scalability of the existing solutions a large number of devices needs to be deployed. To this end, an emulation mode for the control and data plane is seen as a potential solution. 

In this work, the student shall deploy a data plane user based simulator that is able to connect to an SD-RAN controller through a control plane channel and report user specific statistics. Considering a distributed SD-RAN control plane, the control handover becomes a crucial aspect that introduces potential delays. In this thesis, the effect on the user perfromance should be measured with respect to the control handover.

The main goal of this work is to investigate the real time deployment of an SD-RAN architecture and identify potential bottlenecks regarding the control plane signaling and its effects on the users in the data plane.

• Mandatory programming skills in Python, C++ is a plus.
• Mandatory knowledge about socket programming.
• Knowledge about mobile networks 4G/5G.
• Knowlegde about event based simulators is a plus.
• Experience with google protobuffers is a plus.

More and more devices communicate wirelessly in the cabin. This includes, seat screens, passenger devices (mobile phones, laptops), sensors and actuators. As of today, the complete unlicensed spectrum is used. In future, 5G-NR-U base station can be deployed in this scenario, to offer new connectivity possiblities. This requires new coexistence mechanisms that do not put further strain on spectrum resources.

The goal of this thesis is to extend a pre-existing enhance a pre-existing simulator (based on matlab) for 5G-NR-U signal demodulation, with the help of pre-existing matlab 5G-NR-U functions. After extending the simulator, different scenarios and channel etimation techniques should be investigated, as well as several Key Performance Indicators such as Bit Error Rate, Signal-to-Interference-to-Noise-Ratio and throughput.

The overall goal is to show that interference cancellation, the underlying concept of Rate Splitting and NOMA is viable even in a challenging environment such as an aircraft cabin where the high density of radio devices is a challenge

Tasks

• Review of related literature
• Extend our simualtion from 4G to 5G
• Compare different channel estimation techniques
• Evaluate of the simulation results

Preferred Qualifications

• Experience in matlab
• Interest in signal modeling
• Interest in new communication technologies

Related Work

Interference Cancelation
https://www.researchgate.net/profile/Cheng-Xiang_Wang/publication/
224083390_Cognitive_radio_networks/links/0fcfd50b57f883862f000000/Cognitive-radio-
networks.pdf
5G-NR-U
https://de.mathworks.com/help/5g/examples/nr-pdsch-throughput.html
Channel Estimation Techniques
https://ieeexplore.ieee.org/document/1033876
http://engold.ui.ac.ir/~sabahi/Advanced%20digital%20communication/Channel%20estimation%20for
%20wireless%20OFDM%20sysytems.pdf

Recently, a scalable load balancing algorithm in the dataplane has been proposed that leverages P4 to estimate the utilization in the network and assign flows to the least utilized path. This approach can be interpreted as a form of Graham's List algorithm.

In this thesis, the student is tasked to investigate how a different online scheduling algorithm called IMBAL performs compared to HULA. A prototype of IMBAL should be implemented in NS3. The tasks of this thesis are:

1. Literature research and overview to online scheduling and traffic engineering in data center networks.
2. Design how IMBAL can be implemented in NS3.
3. Implementation of IMBAL in NS3.
4. Evaluation of the implementation in NS3 with production traffic traces and comparison to HULA (a HULA implementation is provided from the chair and its implementation not part of this thesis).

Next generation mobile networks are envisioned to cope with heterogeneous applications with diverse requirements. To this end, 5G is paving the way towards more scalable and higher performing deployments. This leads to a revised architecture, where the majority of the functionalities are implemented as network functions, which could be scaled up/down depending on the application requirements. 

3GPP has already released the 5G architecture overview, however there exists no actual open source deployment of RAN functionalities. This will be crucial towards the evaluation of the Core network both in terms of scalability and performance. In this thesis, the student shall understand the 5G standardization, especially the control plane communication between the RAN and 5G Core. Further, an initial RAN function compatible with the 5G standards shall be implemented and evaluation of control plane performance will be carried out. 

• Strong knowledge on programming languages Python, C++ or Java.
• Knowledge about mobile networking is necessary.
• Knowlegde about 4G/5G architecture is a plus.

Optical core networks deploy fixed grid in order to accommodate their demands. The trend is however, migrate towards flexgrid networks able to use as much spectrum as required by the demand allowing a better use of the spectrum. However, the Routing and Wavelength Assignment (RWA) paradigm becomes more complex as it has to find the suitable spectrum of the demand.

This thesis will consider different multiplexing alternatives: space division, band division multiplexing, etc.

The objective is to compare the performance, throughput, BoM, etc. of the different alternatives for different networks and demand evolution matrices.

Java programming skills

Basic knowledge of flexible optical networks

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yle="line-height: 1.38; background-color: #ffffff; margin-top: 0pt; margin-bottom: 0pt;" dir="ltr">The topic is related to human blockage modeling in 5G and beyond systems. We would like to model blockages and evaluate their impact on user quality of service because having a line of sight is very important for communication technologies that use high frequencies such as LiFi and mmWaves. The loss of line of sight leads to frequent handovers, which in turn result in a data transmission interruption. 

Tasks:

•     Review of related literature
•     MPTCP+LiFi enabled hardware setup 
•     Evaluate and Compare different schedulers on real linux platform

In this work, a study on implementing 5G UPF in a modular way using P4 will be conducted.

Knowledge related to P4 and 5G Core system are required.

Time-Sensitive Networking (TSN) standards aim at providing stricter quality of service (QoS) guarantees than legacy Ethernet. Using the TAS feature of TSN, a pre-planned transmission schedule with dedicated time slots for critical traffic, very small end-to-end latency, and jitter can be guaranteed. However, it has several drawbacks, such as algorithm complexity to compute a conflict-free schedule, non-trivial re-configuration at runtime, strict requirements on clock synchronization across the whole network.

As many use cases do not need the outstanding performance of a TAS-scheduled network, and many legacy end stations and applications are not capable of sending packets at a pre-planned point in time, the topic of this research internship is to elaborate on the performance of a strict priority-based network – which behaves deterministic, if the traffic patterns, i.e. the amount of data per time interval, is known for all high-priority traffic in the network.

The goal of this internship is to implement and evaluate an algorithm that computes the worst-case delay for given streams, considering the current network topology and data flow already present in the network. 

• Knowledge of TSN, TAS
• Python

In the future, more data will be transmitted wirelessly, especially in aircraft cabins. However, cabin channel models are scarce especially for LiFi. Therefore, we have developed a 3D structure of an aircraft cabin in blender. The next step is to develop a statistical description of channel model by adapting an existing raytracing engine such as LuxCore.

Tasks:

•     Review of related literature
•     Extend existing aircraft 3D model to include lights/LEDs
•     Analyze resulting channel effects
•     Evaluate the model extensively for different scenarios

• Working knowledge of python
• Experience with 3D modeling especially Blender
• Interest in wireless channel models

hansini.vijayaraghavan@tum.de

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Increased interference is one of the main drawbacks of cell densification, which is an important strategy for 5G networks to achieve higher data rates. Function centralization has been proposed as a strategy to counter this problem, by letting the physical or scheduling functions coordinate among one another. Nevertheless, the capacity of the fronthaul network limits the feasibility of this strategy, as the throughput required to connect low level functions is very high. Fortunately, since not every function benefits in the same way from centralization, a more flexible approach can be used. Instead of centralizing all functions, only those providing the highest amount of interference mitigation can be centralized. In addition, the centralization level, or functional split, can be change during runtime according to the instantaneous network conditions. Nonetheless, it is not fully know how costly it is to deploy and operate a network implementing a dynamic functional split.

In this internship, the cost of a radio access network implementing a dynamic functional split will be evaluated. A simulator already developed at LKN will be used and extended to produce network configurations adapted to the instantaneous user position and activity. Then, off-the-shelf cost models will be improved and used to estimate the deployment and operating cost of the network under multiple scenarios. Furthermore, the conditions on which a dynamic functional split is profitable will be investigated. Improvements on the functional-split selection algorithm will be proposed, such that the operator benefits from enhanced performance without operating at exceedingly costly states. Finally, a model that takes into account the cost of finding and implementing a new functional split will be employed and its results compared to the previous results.

The Optical Networking Industry now aims to move into a disaggregated transport network use case, so that operators can reduce operation costs and deploy open solutions for management and control of such networks. SDN controllers based on Open Daylight TransportPCE and OpenROADM Models. 

In this internship, a student will deploy such a testbed integrated with LKN's in-house network planner and then conduct measurements to provide first insights into Online Optical Network Planinng

1. Knowledge of Optical Networks

2. Knowledge of SDN

3. Good to have working knowledge of Java.

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• yle="color: black; mso-margin-top-alt: auto; mso-margin-bottom-alt: auto; mso-list: l0 level1 lfo1; tab-stops: list 36.0pt;">Characterization of Coherent optical high speed modems
• yle="color: black; mso-margin-top-alt: auto; mso-margin-bottom-alt: auto; mso-list: l0 level1 lfo1; tab-stops: list 36.0pt;">Flexible bit rates of 100 Gbps to 600 Gbps with respect to possible standardization of these interfaces

In electronics and telecommunication, jitter is a significant and an undesired factor. The effect of jitter on the signal depends on the nature of the jitter. It is important to sample jitter and noise sources when the clock frequency is especially prone to jitter or when one is debugging failure sources in the transmission of high speed serial signals. Managing jitter is of utmost importance and the methods of jitter decomposition have changed comparably over the past years.

yle="background-image: initial; background-position: initial; background-size: initial; background-repeat: initial; background-origin: initial; background-clip: initial;"> 

yle="background-image: initial; background-position: initial; background-size: initial; background-repeat: initial; background-origin: initial; background-clip: initial;">In a system, jitter has many contributions and it is not an easy job to identify the contributors. It is difficult to get Random Jitter on a spectrogram. The waveforms are initially constant, but the 1/f noise and flicker noise cause a lot of disturbance when it comes to output measurement at particular frequencies in a system. 

yle="background-image: initial; background-position: initial; background-size: initial; background-repeat: initial; background-origin: initial; background-clip: initial;"> 

yle="background-image: initial; background-position: initial; background-size: initial; background-repeat: initial; background-origin: initial; background-clip: initial;">The task is to understand the difference between the jitter calculations based on a step response estimation and the dual dirac model by comparing the jitter algorithms between the R&S oscilloscope and other competition oscilloscopes. Also to understand how well the jitter decomposition and identification is there.

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yle="background-image: initial; background-position: initial; background-size: initial; background-repeat: initial; background-origin: initial; background-clip: initial;">The tasks in detail are as follows.

yle="background-image: initial; background-position: initial; background-size: initial; background-repeat: initial; background-origin: initial; background-clip: initial;">Setup a waveform simulation environment and extend to elaborate test cases

yle="background-image: initial; background-position: initial; background-size: initial; background-repeat: initial; background-origin: initial; background-clip: initial;">Run the generated waveforms through the algorithms

yle="background-image: initial; background-position: initial; background-size: initial; background-repeat: initial; background-origin: initial; background-clip: initial;">Analyze and compare the results:

yle="background-image: initial; background-position: initial; background-size: initial; background-repeat: initial; background-origin: initial; background-clip: initial;">Frequency domain

yle="background-image: initial; background-position: initial; background-size: initial; background-repeat: initial; background-origin: initial; background-clip: initial;">Statistically (histogram, etc)

yle="background-image: initial; background-position: initial; background-size: initial; background-repeat: initial; background-origin: initial; background-clip: initial;">Time domain

yle="background-image: initial; background-position: initial; background-size: initial; background-repeat: initial; background-origin: initial; background-clip: initial;">Consistency of the results

yle="background-image: initial; background-position: initial; background-size: initial; background-repeat: initial; background-origin: initial; background-clip: initial;">Evaluate the estimation of the BER (bit error rate)

yle="background-image: initial; background-position: initial; background-size: initial; background-repeat: initial; background-origin: initial; background-clip: initial;">Identify the limitations of the dual-dirac model

yle="background-image: initial; background-position: initial; background-size: initial; background-repeat: initial; background-origin: initial; background-clip: initial;">Compare dual-dirac model results with a calculation based on the step response estimation

yle="background-image: initial; background-position: initial; background-size: initial; background-repeat: initial; background-origin: initial; background-clip: initial;">Generate new waveforms based on the analysis

yle="background-image: initial; background-position: initial; background-size: initial; background-repeat: initial; background-origin: initial; background-clip: initial;">Summarize findings

As the architecture of the 5G Core has already been standardized and it is fundamentally different from the previous generations, a question rises regarding the efficiency of the communication mechanisms that will be used for the communication between Network Functions (NFs) inside the 5G Core Network.
In this project, the student will evaluate these mechanisms used in an open-source implementation of the 5G Core (https://www.free5gc.org/), and propose improvements that will increase the performance and scalability of the Core Network (e.g., serialization, protocols, etc.).

• General knowledge about Mobile Networks (RAN & Core).
• Motivated to learn more about the communication side of the Mobile Core Networks.
• Strong programming skills. Knowledge of Go (https://golang.org/) is a plus.

endri.goshi@tum.de

3GPP has already released the 5G architecture overview, however there exists no actual open source deployment of RAN functionalities. This will be crucial towards the evaluation of the Core network both in terms of scalability and performance. In this thesis, the student shall understand the 5G standardization, especially the control plane communication between the RAN and 5G Core. Further, an initial RAN function compatible with the 5G standards shall be implemented and evaluation of control plane performance will be carried out. 

• Strong knowledge on programming languages Python, Go.
• Knowledge about mobile networking is necessary.
• Knowlegde about 4G/5G architecture is a plus.

The goal of this thesis is the classification of packet-level traces using Markov- and Hidden Markov Model. The scenario is open-world: Traffic of specific web applications should be distinguished from all possible web-pages (background traffic). In addition, several pages should be differentiated. Examples include: Google Maps, Youtube, Google Search, Facebook, Google Drive, Instagram, Amazon Store, Amazon Prime Video, etc.

This research internship looks at Quanktum Key Distribution exchange in a wide area pan-European network. Different architectures, routing and spectrum allocation methods need to be considered, keeping in mind both technological and economic constraints of such a combined deployment.

This work is helpful for Optical Networking as well as satellite network providers in order to provide secure data transmissions over large region multi-national governmental organizations, banks and security agencies.

In this internship/bachelor thesis, a student will research different lightpath reconfiguration algorithms models and their applications to flexible optical networking. Then, they will create an evaluation framework and finally simulate a network planning study.  The results will be investigated to draw useful conclusions.

Must Have

• Basic knowledge of graph theory, communication networks and optical networks
• Independent worker
• Working knowledge of Python
• Willingness to learn

Good to Have

• Knowledge of Java
• Familiarity with NetConf/YANG

To apply, please send your CV and grade transcripts to kireet.patri@tum.de

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The architecture of 5G radio access networks features the division of the base station (gNodeB) into a centralized unit (CU) and a distributed unit (DU). This division enables cost reduction and better user experience via enhanced interference mitigation. Recent research proposes the posibility to modify this functional split dynamically, that is, to lively change the functions that run on the CU and DU. This has interesting implications at the network operation.

In this topic, the student will employ a dedicated simulator developed by LKN to characterize the duration and transition rates of each functional split under multiple variables: population density, mitigation capabilities, mobility, etc. This characterization may be used then on traffic models to predict the network behavior.

MATLAB, some experience with mobile networks and simulators

Internetkommunikation offers the opportunity to develop interesting software solutions for technical questions about internet protocols and mechanisms. For the next semester, a position is available to assist the teaching assistants for the tutorials and class project.

• Knowledge in computer networking

• Good programming skills in Python

The Wireless Sensor Networks lab offers the opportunity to develop software solutions for the wireless sensor networking system, targeting innovative applications. For the next semester, a position is available to assist the participants in learning the programming environment and during the project development phase. The lab is planned to be held on-site every Tuesday and Thursday from 15:00 to 18:00.

Solid knowledge in Wireless Communication: PHY, MAC, and network layers. Solid programming skills: C/C++. Linux knowledge. Experience with embedded systems and microcontroller programming knowledge is preferable.

Future IoT will need wireless links with high data rates, low latency and reliable connectivity despite the limited radio spectrum. Connected lighting is an interesting infrastructure for IoT services because it enables visible light communication (VLC), i.e. a wireless communication using unlicensed light spectrum. This work will aim at developing a tool to perform an economic evaluation of the proposed solution in the particular case of a smart office.

For that purpose, the following tasks will have to be performed:

• Definition of a high-level framework specifying the different modules that will be implemented as well as the required inputs and the expected outputs of the tool.
• Development of a cost evaluation Excel-VBA tool. This tool will allow to evaluate different variations of the selected case study and if possible, to compare different alternative models (e.g., dimensioning) or scenarios (e.g., building types).

- Excel and VBA

Networked Control Systems, i. e. the interconnection of a control system over a communication network, are a fundamental building block of future industrial automation systems. To study NCS, the NCSbench platform [1,2] was developed allowing performance measurements of a real NCS. The platform is built using Lego, is developed in python, communicates over standard IP network interfaces and is fully open-source.

In order to further develop the platform, a working position is available.

[1] https://github.com/tum-lkn/NCSbench/wiki

[2] S. Zoppi, O. Ayan, F. Molinari; Z. Music, S. Gallenmüller, G. Carle, W. Kellerer, NCSbench: Reproducible Benchmarking Platform for Networked Control Systems. IEEE Consumer Communications & Networking Conference, 2020

This work will consist of a significant amount of programming and also of processing the measurement data.

Requirements:

• Good knowledge of wireless systems and protocols (WLAN, WSN).
• Basic knowledge of LTI control systems.
• Strong C and Python programming skills.
• Experience with Linux systems is recommended.
• Experience with python data processing tools is beneficial.

Network Function Virtualization (NFV) is becoming a promissing technology in modern networks. A challenging problem is determining the placement of Virtual Network Functions (VNFs). In this work, we plan to implement existing algorithms for embedding VNFs chains in NFV-enabled networks. 

Experience in Python or Java, object oriented programming

amir.varasteh@tum.de

The lecture Broadband Communication Networks (Prof. Wolfgang Kellerer) teaches network-related methods of mobile communication: WIFI, 2G to 5G cellular networks, etc. In order to bridge the gap between the methods and real life, innovative teaching concepts shall be developed in form of short podcasts where the students learn in short episodes about wireless communication and networking in day to day scenarios. In the podcasts the student should also be introduced to short exercises they can perform on their own.

In order to support designing these podcasts Pro. Kellerer is looking for a student experienced in programming and maybe in podcasts to help him.

Very good programming skills; experience with podcasts; experience with app programming (on android/ios)

The yle="color: #333333; font-family: Arial, sans-serif; font-size: 14px;">Software-Defined Networking (SDN) lab offers the opportunity to work with real hardware on interesting and entertaining projects related to the SDN network paradigm. For the next semester, a position is available to assist the teaching assistants for the lab (definition and preparation of the assignments, preparation of the hardware, etc.).

yle="list-style-type: square; margin-left: 0px; padding-left: 20px; color: #333333; font-family: Arial, sans-serif; font-size: 14px;">
• yle="padding-left: 0.3em;">Solid knowledge in computer networking (TCP/IP, SDN)
• yle="padding-left: 0.3em;">Solid knowledge of networking tools and Linux (iperf, ssh, etc)
• yle="padding-left: 0.3em;">Good programming skills: C/C++, Python