Student project proposals

LEO satellites have only a short pass window, often just a few minutes, to get stored data down to a ground station. Payload data waiting for downlink is commonly held in a cyclic buffer, and frame losses during a pass, from fading, obstruction, or the link dropping below the MODCOD's demodulation threshold, put that short window at risk of an incomplete transfer. DVB-S2 already adapts its MODCOD using SNR feedback from the ground station, but this says nothing about whether the data itself was actually delivered. A key motivation for this project is to test whether an application layer code, layered above DVB-S2, can offer a more direct guarantee that stored data reaches the ground intact, and whether it can do so more efficiently than simply streaming the buffer as is.

RaptorQ generates a stream of encoded symbols from a source object such that a receiver can reconstruct the object from any sufficiently large subset of symbols, regardless of which specific frames were lost. Applying this above DVB-S2 raises a design question: since a DVB-S2 frame's usable payload changes with the code rate part of the current MODCOD, how much RaptorQ overhead is needed, and how should it be configured, to make efficient use of the link's time varying capacity over a pass.

This project addresses the following core research question: can RaptorQ, layered above DVB-S2 and configured to make efficient use of MODCOD dependent link capacity, deliver stored payload data from a LEO satellite more reliably and efficiently than a system that streams directly from the buffer without it?

The project proceeds in three phases. In the first phase, a DVB-S2 simulation is implemented with RaptorQ as an application layer FEC scheme, building on existing open-source RaptorQ implementations, and a representative LEO pass is modeled with elevation dependent SNR variation. In the second phase, RaptorQ's delivery performance is evaluated against the simulated pass, quantifying the symbol overhead needed to reliably reconstruct a source object, benchmarked against a baseline system that streams directly from the buffer without RaptorQ, and against a scheme where RaptorQ's own delivery outcomes are used as an additional feedback signal alongside SNR based MODCOD adaptation. In the third phase, and as an optional extension, the scheme is implemented and tested on the department's DVB-S2 lab setup to quantify its real-world performance.

Direction finding of RF-emitting targets is a core capability in radar, electronic warfare, spectrum monitoring, and wireless localisation systems. Mechanically steered antennas are slow and bulky; a phased array instead lets the angle of arrival be estimated purely from the phase differences measured across multiple fixed receive elements. A key motivation for this project is to demonstrate, at low cost and on standard fabrication processes, the full chain from antenna simulation to a working AoA estimate — giving hands-on experience with a capability that underpins much more complex operational direction-finding systems.

A linear array of receive elements sees a plane wave arrive with a small, predictable phase offset between adjacent elements that depends on the angle of arrival, the element spacing, and the wavelength. Recovering that angle accurately depends on three things being solved together: the array and its feed network must be designed so element spacing and pattern are well characterised at the operating frequency; the multi-channel receiver must sample all elements with a shared clock so the measured phase differences reflect only the incoming wave, not receiver timing error; and the estimation algorithm must convert the measured phases into a bearing with known, quantified resolution and error.

This project addresses the following core research question: can a 4-element linear phased array, built on standard PCB fabrication and read out by a phase-coherent multi-channel receiver, estimate the bearing of an S-band emitter to an accuracy consistent with array theory, when validated against a source at known bearings?

The project proceeds in three phases. In the first phase, the antenna array is simulated in ANSYS HFSS and fabricated as a 4-element linear patch array with λ/2 element spacing. In the second phase, the array is interfaced to a phase-coherent multi-channel receiver and a phase-comparison AoA estimation algorithm is implemented on the captured data. In the third phase, the system is validated with over-the-air measurements in an anechoic chamber against a reference transmitter placed at known bearings on a common plane with the array, and the achievable angular resolution is characterised against the theoretical estimate for a 4-element linear array.

IoT promises a world where physical objects are continuously reachable and addressable over the Internet. In supply chain management, RFID technology has become a cornerstone for tracking goods as they move between locations. However, a fundamental gap exists between the physical movement of tagged objects and their persistent network presence. When a passive RFID tag moves between readers, any associated network state is lost, making it impossible to maintain a continuous, addressable identity for the object.

This project proposes that a VM acting as the network counterpart of a physical object should migrate along with the object as it moves through the supply chain. A key motivation is that latency-critical local decisions can be made by the VM at the point of reader encounter, without incurring the round-trip delay of consulting a central server. Crucially, when the VM computes a decision or issues a compliance certificate at a checkpoint, it can instruct the local reader to write that result back onto the physical tag. The tag thereby becomes a physically embodied audit trail, carrying verified state from each checkpoint independently of network infrastructure. The VM and the tag act as complementary state carriers: the VM provides rich networked computation, while the tag provides a physically resilient record that survives even if network continuity is interrupted.

Passive RFID tags cannot host a network stack. However, as established in prior work, a reader can assign an IPv6 address to a VM acting as the tag's network counterpart, constructing the address from the tag's EPC using CGAs. The challenge arises when the object moves to a new reader: the network prefix changes, the old address becomes unreachable, and network continuity is lost.

This project addresses the following core research question: Can a live VM migration, triggered by and synchronised with the physical movement of an RFID-tagged object between readers, maintain continuous network reachability and preserve computational state across subnet boundaries, while using write-to-tag operations to maintain a physically embodied audit trail on the tag itself?

Three interrelated problems must be solved. How can the VM's network identity be cryptographically bound to the tag's EPC such that the identity remains stable as the VM migrates? How can reader events trigger VM migration in a timely manner, given that a passive tag can only report data at the moment of a reader encounter? And how can the underlying network, using SDN techniques such as OpenFlow, ensure that the VM's IP address remains routable after migration to a host on a different subnet?

The project will proceed in three phases, building on preliminary work already undertaken in constructing IPv6 addresses from EPC identifiers using CGA techniques.

• In the first phase, a testbed will be designed consisting of at least two RFID readers connected to separate network subnets, each associated with a hypervisor host running Xen. An SDN layer using Open vSwitch and an OpenFlow controller will provide a virtual L2 overlay across the subnets, ensuring the VM's IP address remains routable regardless of which host it resides on. The VM's IPv6 address will be constructed using the CGA scheme derived from the object's EPC, cryptographically binding the network identity to the physical tag. Tags with write capability, such as EPC Class 1 Generation 2 tags, will be used to support write-back operations.
• In the second phase, a triggering and orchestration mechanism will be implemented. When the tagged object enters the field of a new reader, a reader event will signal the orchestration layer to initiate a live Xen migration of the VM to the host associated with the new reader. Upon successful migration, the VM will perform any pending local computation and write a signed checkpoint record back onto the tag, updating the physically embodied audit trail.
• In the third phase, the end-to-end system will be evaluated. Success will be measured by the ability to continuously ping the object's IPv6 address throughout its physical journey, with computational state and audit trail integrity preserved across reader handovers. Metrics of interest will include migration latency, decision response time compared to a centralised server baseline, and the completeness and integrity of the audit trail written to the tag. Results will be discussed in the context of Mobile IPv6 and HIP based alternatives as identified in the related literature.