Document Type

Theses, Masters

Master Thesis

Master thesis


Available under a Creative Commons Attribution Non-Commercial Share Alike 4.0 International Licence



Publication Details

Thesis presented for the degree of Master of Philosophy, School of Electrical and Electronic Engineering, Technological University Dublin, November 2021.


The transmission of large amounts of data over resource-constrained radio frequency (RF) networks is impacted by regulatory constraints and can affect reliability due to channel congestion. These barriers limit the use case to specific applications. This research extends the use case scenario to include the transmission of digital images over such networks which to date has not been widely documented. To achieve this, the overall data volume needs to be reduced to manageable limits. Drawing on previous theoretical work this research explored, developed and implemented novel image compression techniques suitable for use in resource-constrained RF networks.

A compression technique was developed which allows variable compression ratios to be selected dependent on the specific use case. This was implemented in an end-to-end low-power radio network operating in license-free spectrum using a customised radio frequency testbed. The robust compression scheme which was developed here enabled out-of-sequence packet reception, further increasing the reliability of the transmission.

To allow detailed viewing of a region of interest (ROI) within a large format image (quarter video graphics array) to be transmitted, a novel algorithm was designed and implemented. This enabled the transmission of a region of interest (ROI) in an uncompressed format as a stand-alone image portion, or in combination with a fully compressed image. Significantly, this yielded flexibility in the quantity of data to be transmitted which could increase the lifespan of battery powered devices. A further development allowed direct manipulation of individual image pixels. This permitted additional data, such as battery voltage level to be directly embedded in the transmitted image data. An advantage of this innovative method was that it did not incur any extra overhead in data volume requirements.

The embodied system developed is an agnostic image compression algorithm and is suitable for use with resource-constrained devices and networks. Results showed that high compression ratios (70%) with good peak signal-to-noise ratio (PSNR) of approximately 36dB was achievable for a complete end-to-end transmission system.




Document Type

Master thesis