Modulation-Aware Artificial Noise Design for Secrecy in MISO IoT Channels with Rayleigh Fading
摘要
This paper investigates artificial noise (AN)-aided physical-layer security (PLS) for narrowband multiple-input single-output (MISO) Internet-of-Things (IoT) wireless networks. We consider a transmitter equipped with multiple antennas (Alice) that sends confidential information to a single-antenna legitimate receiver (Bob) in the presence of a passive eavesdropper (Eve). The transmit signal is composed of two parts: a data-bearing component beamformed toward Bob and an AN component projected into Bob’s null space to degrade Eve’s reception. Bit error rate (BER) expressions in integral form are derived for both binary phase-shift keying (BPSK) and quadrature phase-shift keying (QPSK), which are efficiently evaluated using numerical integration. These expressions reveal the impact of the AN power ratio and modulation on secrecy performance. Extensive simulations are conducted to examine the trade-off between secrecy and reliability over a range of signal-to-noise ratio (SNR) values. The results reveal that allocating \(\approx 40\%\) of the total power to the AN maximizes the ergodic secrecy rate while maintaining Bob’s BER below \(10^{-3}\) at a 10 dB SNR and doubling the transmit-antenna count ( \(2\!\rightarrow \!4\) ) enlarges the Bob–Eve BER gap by two orders of magnitude, providing actionable guidance for low-power IoT design. These findings provide valuable insights into secure and energy-efficient PLS designs for practical IoT deployments.