Perumal Kalpana Devi

Fault injection (FI) is a well-known method to attack embedded systems, particularly advanced FPGAs and microcontrollers physically. The FPGA-based embedded system constitutes SRAM for configuration data storage. Multiple-bit upset is a main threat for FPGAs due to technology scaling and complex application bit files. Space environments additionally incur radiation threats to these devices. This paper proposes burst error modeling and a burst fault injection tool (BUFIT) to address these issues. BUFIT has been proposed with fine-grained and coarse-grained circuits. Built-in instrumented FPGA-based FI is proposed for effectively injecting MBUs in configuration memory with space adaptive rate for accurately estimating soft errors. Evaluation of proposed BUFIT on Kintex-7 target FPGA to various OR 1200-based workloads is given to analyze the speed up of the proposed technique. Results on the OR 1200 processor show that BUFIT is three and two orders of magnitude faster than existing DPR and SCFIT techniques. It uses only 0.4 % CLB overhead and has negligible impact on FFs of target SFPGAs.

Spectrum sensing allows cognitive radio systems to detect relevant signals even in the presence of interference for reliable communication. Most of the existing spectrum sensing techniques use a particular signal‐to‐noise ratio model with assumptions and provide certain detection performance. Dynamic spectrum management techniques enabled the efficient allocation of channels to increasing number of users. In cognitive radio system, the dynamic spectrum management is efficient for sensing the channel occupancy and mobilizing the secondary user towards the unused primary user channel. For spectrum sensing, wavelet‐based spectrum sensing method is analyzed and effectively made spectrum decision. The performance analysis is made for various SNR values with enhanced false alarm and throughput in spectrum management cognitive radio system in 2.2 GHZ band communication.