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All Journal TELKOMNIKA (Telecommunication Computing Electronics and Control) Bulletin of Electrical Engineering and Informatics
Obinna M. Ezeja
University of Nigeria
Computer Science & IT Electrical & Electronics Engineering

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Modeling cache performance for embedded systems Ogechukwu Kingsley Ugwueze; Chijindu C. V.; Udeze C. C.; Ahaneku A. M.; Eneh N. J.; Obinna M. Ezeja; Edward C. Anoliefo
Bulletin of Electrical Engineering and Informatics Vol 10, No 5: October 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v10i5.2459

Abstract

This paper presents a cache performance model for embedded systems. The need for efficient cache design in embedded systems has led to the exploration of various methods of design for optimal cache configurations for embedded processor. Better users’ experiences are realized by improving performance parameters of embedded systems. This work presents a cache hit rate estimation model for embedded systems that can be used to explore optimal cache configurations using Bourneli’s binomial cumulative probability based on application of reuse distance profiles. The model presented was evaluated using three mibench benchmarks which are bitcount, basicmath and FFT for 4kb, 8kb, 16kb, 32kb and 64kb sizes of cache under 2-way, 4-ways, 8-ways and 16-ways set associative configurations, all using least recently-used (LRU) replacement policy. The results were compared with the results obtained using sim-cheetah from simplescalar simulators suite. The mean errors for bitcount, basicmath, and FFT benchmarks are 0.0263%, 2.4476%, and 1.9000% respectively. Therefore, the mean error for the three benchmarks is equal to 1.4579%. The margin of errors in the results was below 5% and within the acceptable limits showing that the model can be used to estimate hit rates of cache and to explore cache design options.
Stochastic resonance-aided energy detection for RF-powered cognitive radio networks Henry Onyemauche Osuagwu; Mamilus A. Ahaneku; Vincent C. Chijindu; Obinna M. Ezeja
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 24, No 3: June 2026
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v24i3.27596

Abstract

Conventional stochastic resonance (SR) techniques often face challenges with higher-frequency signals and parameter optimization for real-time applications, as observed in practical orthogonal frequency-division multiplexing (OFDM) systems that are vulnerable to noise uncertainty (NU). In this study, we present a novel SR-aided energy detection (ED) method that incorporates multi-taper spectrum estimation technique to improve spectrum estimation precision and Gauss-Seidel-like iteration method to accurately adjust the SR parameters for real-time adaptation. This combined strategy enhances weak signal detection, prevents signal distortion, and increases robustness against fluctuating noise conditions. Results from 5,000 Monte Carlo simulations showed that, at 0 dB NU, SR-aided ED attained 90% detection probability at -11 dB, outperforming conventional ED with an SNR gain of 12.5 dB. At 3 dB NU, the conventional ED accuracy degraded by 5.5 dB, resulting in a false alarm probability of 77%, while SR-aided ED demonstrated robustness to NU. At 10 dB NU, ED failed to distinguish the differences between noise and signal power, giving rise to 99% false alarm probability. In contrast, despite a 6 dB degradation, the developed SR-aided ED approach still guarantees a 1% false alarm probability. In clipping-prone systems, conventional ED is vulnerable to signal clipping. Conversely, SR-aided ED remains unaffected.
Co-Authors Ahaneku A. M. Chijindu C. V. Edward C. Anoliefo Eneh N. J. Henry Onyemauche Osuagwu Mamilus A. Ahaneku Ogechukwu Kingsley Ugwueze Udeze C. C. Vincent C. Chijindu