Exjobbspresentation: Hardware-Efficient Root Value Estimation for Zadoff-Chu Sequences of Known Length

In wireless communications protocols, Zadoff-Chu (ZC) sequences are often used for synchronisation between transmitter and receiver due to their advantageous mathematical properties. They are employed widely in LTE and 5G systems and UAV communications, among others. Blindly detecting ZC sequences has important applications for security and privacy. However, blind ZC sequence detection is computationally expensive, especially for longer sequences, restricting deployment to centralised processing platforms such as high-end desktop PCs or dedicated servers. This thesis investigates hardware-efficient detection algorithms and modifications, contributing to enabling detection in resource-constrained edge devices, such as Application Specific Integrated Circuits (ASICs) and Field-Programmable Gate Arrays (FPGAs). By simulating and evaluating a time-based cross correlation, a fast cross correlation, and a phase difference estimation algorithm, it was found that the time-based cross correlation had identical performance to the fast cross correlation with acceptable detection performance down to a Signal-to-Noise Ratio (SNR) of -14 dB. However, it consumed 10 times the energy, rendering it impractical. In contrast, the phase difference estimation algorithm consumed 10 times less energy than the fast cross-correlation algorithm, but the acceptable performance was limited to above an SNR of -6 dB. These algorithms were also modified to further reduce energy costs. Testing revealed that the fixed-point arithmetic scaling factor could be as low as 16 without noticeable performance degradation. Additionally, sequence stacking and downsampling yielded significantly lower energy costs proportional to the modification parameter. However, it was also found that the performance loss scaled with the modification parameter. Consequently, these trade-offs demonstrate that the optimal algorithm and modification configuration depend on the intended SNR environment, providing a dynamic low-power solution. 

Handledare: Johan Thunberg (EIT, LTH), Anders Lloyd (Axis Communications), Andreas Karlsson (Axis Communications), Per Andersson (EIT, LTH). 

Examinator: Pietro Andreani (EIT, LTH)