Cooperative Spectrum Sensing with Coded and Uncoded Decision Fusion under Correlated Shadowed Fading Report Channels

Area of Science:

• Wireless Communications
• Signal Processing
• Information Theory

Background:

• Cooperative spectrum sensing enables efficient detection of idle Orthogonal Frequency Division Multiplexing (OFDMA) subchannels.
• Report channels in centralized decision fusion are vulnerable to complex fading environments.

Purpose of the Study:

• To evaluate the effectiveness of forward error correction (FEC) codes in enhancing the reliability of report channel transmissions for cooperative spectrum sensing.
• To analyze the impact of spatially correlated shadowing and multipath fading on system performance.

Main Methods:

• Utilized a centralized decision fusion cooperative spectrum sensing scheme with OFDMA signals.
• Modeled report channels using a shadowed fading model with three-dimensional spatially correlated shadowing and Rayleigh fading.
• Applied Binary BCH and Repetition codes for error detection and correction.
• Employed the maximum eigenvalue detection test statistic for sensing.

Main Results:

• Spatially correlated shadowing significantly degrades overall spectrum sensing performance.
• FEC may be ineffective in protecting report channels, especially in low signal-to-noise ratio (SNR) regimes.
• Repetition codes demonstrated superior performance over BCH codes in specific scenarios, highlighting the importance of diversity gain.

Conclusions:

• Error correction coding's ability to mitigate performance degradation in cooperative spectrum sensing under correlated shadowing is limited.
• Diversity gain from coding schemes can be more beneficial than coding gain in heavily shadowed environments.