One of the main challenges in cognitive radio networks is the ability of secondary users to detect the primary user presence with high probability of detection. In previous research, optimizing cooperative sensing in cognitive radio networks is performed for either a targeted probability of detection or a false alarm. After setting one of the probabilities as an optimization constraint, the other is optimized. In this paper, a guaranteed constant throughput at the secondary users is introduced as a target while optimizing probability of detection for cooperative sensing. Both sensing time values and number of cooperated cognitive radio secondary users are investigated to maximize the probability of detection of primary user. AND and OR hard decision schemes are considered and compared with soft decision scheme which is weighted modified deflection coefficient scheme (W-MDC). It is illustrated that cooperation of all users and utilizing full frames for sensing time will not provide maximum probability of detection. A tradeoff between performances of cognitive radio networks with and without optimization is presented. The effects of varying network sizes, normalized target throughput, maximum frame duration times, and received signal-to-noise ratio at the fusion center are investigated for different fusion rules.
In this paper, the joint effect of quantization and clipping done by the Analog-to-Digital Converter (ADC) in the receiver of a Wireless Sensor and Actuator Network (WSAN) is investigated. As an Ultra Reliable Low-Latency Communication (URLLC) system, a combination of Code Division Multiple Access (CDMA) and Orthogonal Frequency Division Multiplexing (OFDM) that uses Offset Quadrature Amplitude Modulation (OQAM) is applied. It is shown that under an industrial Non-Line-Of-Sight (NLOS) channel, CDMA-OQAM-OFDM outperforms CDMA-OFDM when both transmissions are attacked by Random Frequency Hopping Jamming (RFHJ).
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