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. 2021 Oct 17;21(20):6881.
doi: 10.3390/s21206881.

Algorithm for Evaluating Energy Detection Spectrum Sensing Performance of Cognitive Radio MIMO-OFDM Systems

Josip Lorincz  1 , Ivana Ramljak  2 , Dinko Begusic  1
Affiliations

Algorithm for Evaluating Energy Detection Spectrum Sensing Performance of Cognitive Radio MIMO-OFDM Systems

Josip Lorincz et al. Sensors (Basel). .

Abstract

Cognitive radio technology enables spectrum sensing (SS), which allows the secondary user (SU) to access vacant frequency bands in the periods when the primary user (PU) is not active. Due to its minute implementation complexity, the SS approach based on energy detection (ED) of the PU signal has been analyzed in this paper. Analyses were performed for detecting PU signals by the SU in communication systems exploiting multiple-input multiple-output orthogonal frequency division multiplexing (MIMO-OFDM) transmission technology. To perform the analyses, a new algorithm for simulating the ED process based on a square-law combining (SLC) technique was developed. The main contribution of the proposed algorithm is enabling comprehensive simulation analyses of ED performance based on the SLC method for versatile combinations of operating parameter characteristics for different working environments of MIMO-OFDM systems. The influence of a false alarm on the detection probability of PU signals impacted by operating parameters such as the signal-to-noise ratios, the number of samples, the PU transmit powers, the modulation types and the number of the PU transmit and SU receive branches of the MIMO-OFDM systems have been analyzed in the paper. Simulation analyses are performed by running the proposed algorithm, which enables precise selection of and variation in the operating parameters, the level of noise uncertainty and the detection threshold in different simulation scenarios. The presented analysis of the obtained simulation results indicates how the considered operating parameters impact the ED efficiency of symmetric and asymmetric MIMO-OFDM systems.

Keywords: MIMO; OFDM; false alarm probability; probability of detection; simulations; square-law combining.

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Conflict of interest statement

The authors declare no conflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript; or in the decision to publish the results.

Figures

Figure 1
Figure 1
Block diagram of the ED process based on SLC in a MIMO-OFDM system with M Tx and R Rx branches.
Figure 2
Figure 2
The ROC curves presenting the ED performance for different SNR values equal to: (a) −20 dB, (b) −15 dB and (c) −10 dB.
Figure 2
Figure 2
The ROC curves presenting the ED performance for different SNR values equal to: (a) −20 dB, (b) −15 dB and (c) −10 dB.
Figure 3
Figure 3
The ROC curves presenting the ED performance for the different PU Tx powers and an SNR of −15 dB in (a) SISO and (b) 2 × 2 MIMO communication systems.
Figure 4
Figure 4
The ROC curves presenting the ED performance for the different PU Tx powers and the SNR of −20 dB in (a) SISO, (b) 2 × 2, (c) 2 × 4 and (d) 2 × 6 MIMO communication systems.
Figure 4
Figure 4
The ROC curves presenting the ED performance for the different PU Tx powers and the SNR of −20 dB in (a) SISO, (b) 2 × 2, (c) 2 × 4 and (d) 2 × 6 MIMO communication systems.
Figure 5
Figure 5
The ROC curves presenting the ED performance for the different number of samples in (a) the SISO system with a PU Tx power of 100 mW, (b) the SISO system with a PU Tx power of 1 W, (c) the MIMO 2 × 2 system with a PU Tx power of 100 mW and (d) the MIMO 2 × 2 system with a PU Tx power of 1 W.
Figure 5
Figure 5
The ROC curves presenting the ED performance for the different number of samples in (a) the SISO system with a PU Tx power of 100 mW, (b) the SISO system with a PU Tx power of 1 W, (c) the MIMO 2 × 2 system with a PU Tx power of 100 mW and (d) the MIMO 2 × 2 system with a PU Tx power of 1 W.
Figure 6
Figure 6
The ROC curves presenting the ED performance for signal transmission with different modulation schemas in (a) SISO, (b) symmetric MIMO (2 × 2) and (c) asymmetric MIMO (2 × 3) systems.
Figure 7
Figure 7
The ROC curves presenting ED performance for MIMO system impacted with different PU Tx powers and modulation schemes.
Figure 8
Figure 8
The ROC curves presenting the ED performance for the asymmetric 2 × 3, 2 × 4, 4 × 2 and 3 × 2 MIMO-OFDM communication systems.
Figure 9
Figure 9
The ROC curves presenting the ED performance for the symmetric 2 × 2, 3 × 3, 4 × 4 and 5 × 5 MIMO-OFDM communication systems.
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