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Abstract
This paper presents an approach to exploit the superimposed training (ST)-based primary users’ (PUs) transmissions in the context of spectrum sensing for cognitive radio. In the low signal-to-noise ratio (SNR), the proposed scheme splits the spectrum sensing phase into two sample processing periods, allowing a secondary user (SU) to carry out a training sequence synchronization (with a small probability of error) before the implementation of a robust spectrum sensing algorithm that enhances the detection, based on the deterministic signal components embedded in the ST PU’s signals along with the unknown data signal. The overall sensing performance is improved using a reasonable number of samples to achieve a high probability of detection, resulting in a reduced spectrum sensing duration. Furthermore, a low computational complexity version of the proposed ST combined approach for a reduced phase (SCAR-Phase) of spectrum sensing is presented, which attains the same detection performance with a smaller number of real operations in the low SNR. In the practical consideration of imperfect training sequence synchronizations, the results show the advantages of exploiting the ST sequence to perform spectrum sensing, thus quantifying the significant improvement in detection performance and the maximum SU’s achievable throughput.
Highlights
Cognitive radio (CR) is envisioned as one of the technologies that will alleviate the demand for more radio frequency (RF) spectrum required by future wireless communications systems and networks
The proposed SCAR-Phase sensing took advantage of the superimposed training (ST) information to carry out the synchronization of an secondary user (SU) with the ST primary users’ (PUs)’s sequence and to enhance its detection performance
In the second one, an enhanced ST-based detector (i.e., ST-Det) was designed to perform the spectrum sensing with a small number of samples and a high probability of detection
Summary
Cognitive radio (CR) is envisioned as one of the technologies that will alleviate the demand for more radio frequency (RF) spectrum required by future wireless communications systems and networks. Signals with embedded pilots (e.g., digital TV signals) is proposed for spectrum sensing over a lossless channel This detector takes advantage of both the known pilot symbols and the energy of the received signal to improve the detection performance of SUs. In [9] a semi-blind spectrum sensing algorithm is designed by exploiting the knowledge of a training sequence that is time-multiplexed with binary phase shift keying (BPSK) modulated PU’s signals. A detector for ST PUs’ signals (called ST-Det) is designed and used in the second sample processing period of the proposed superimposed training combined approach for a reduced phase (SCAR-Phase) of spectrum sensing to implement an enhanced detection, considering the synchronized training and the data sequences.
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