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Intelligent reflecting surfaces (IRSs) are a promising low-cost solution for achieving high spectral and energy efficiency in future communication systems by enabling the customization of wireless propagation environments.Despite the plethora of research on resource allocation design for IRS-assisted multiuser wireless communication systems, the optimal design and the corresponding performance upper bound are still not fully understood. To bridge this gap in knowledge, in this paper, we investigate the optimal resource allocation design for IRS-assisted multiuser multiple-input single-output (MISO) systems employing practical discrete IRS phase shifters. In particular, we jointly optimize the beamforming vector at the base station (BS) and the discrete IRS phase shifts to minimize the total transmit power for the cases of perfect and imperfect channel state information (CSI) knowledge. To this end, two novel algorithms based on the generalized Bender's decomposition (GBD) method are developed to obtain the globally optimal solution for perfect and imperfect CSI, respectively. Moreover, to facilitate practical implementation, we propose two corresponding low-complexity suboptimal algorithms with guaranteed convergence by capitalizing on successive convex approximation (SCA). In particular, for imperfect CSI, we adopt a bounded error model to characterize the CSI uncertainty and propose a new transformation to convexify the robust quality-ofservice (QoS) constraints. Our numerical results confirm the optimality of the proposed GBD-based algorithms for the considered system for both perfect and imperfect CSI. Furthermore, we unveil that both proposed SCA-based algorithms can achieve a close-to-optimal performance within a few iterations. Moreover, compared with the stateof-the-art solution based on the alternating optimization (AO) method, the proposed SCA-based scheme achieves a significant performance gain with low complexity, especially for moderate-to-large numbers of IRS elements.

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The security of wireless sensor networks (WSN) has become a great challenge due to the transmission of sensor data through an open and wireless network with limited resources. In the paper, we discussed a lightweight security scheme to protect the confidentiality of data transmission between sensors and an ally fusion center (AFC) over insecure links. For the typical security problem of WSN’s binary hypothesis testing of a target’s state, sensors were divided into flipping and non-flipping groups according to the outputs of a pseudo-random function which was held by sensors and the AFC. Then in order to prevent an enemy fusion center (EFC) from eavesdropping, the binary outputs from the flipping group were intentionally flipped to hinder the EFC’s data fusion. Accordingly, the AFC performed inverse flipping to recover the flipped data before data fusion. We extended the scheme to a more common scenario with multiple scales of sensor quantification and candidate states. The underlying idea was that the sensor measurements were randomly mapped to other quantification scales using a mapping matrix, which ensured that as long as the EFC was not aware of the matrix, it could not distract any useful information from the captured data, while the AFC could appropriately perform data fusion based on the inverse mapping of the sensor outputs.

Eavesdroppers can easily intercept the data transmitted in a wireless sensor network (WSN) because of the network’s open properties and constrained resources. Therefore, it is important to ensure data confidentiality in WSN with highly efficient security mechanisms. We proposed a lightweight security transmission method based on information hiding and random data flipping to ensure that the ally fusion center (AFC) can achieve confidential data transmission over insecure open links. First, the sensors’ local measurements are coded into a customized binary string, and then before data transmission, some parts of the string are flipped by the sensors according to the outputs of a pre-deployed pseudo-random function. The AFC can recover the flipped binaries using the same function and extract the measurement hidden in the string, while the enemy fusion center (EFC) cannot distinguish flipped and non-flipped data at all, and they cannot restore the measurement correctly as long as one bit in the string is not correctly recovered. We proved the security and anti-interference of the scheme through both simulations and physical experiments. Furthermore, the proposed method is more efficient such that it consumes less power than traditional digital encryptions through real power consumption tests.