The small carrier wavelength at millimeter-wave (mm-Wave) frequencies allows the possibility of implementing a large number of antennas on a single chip. This work uses the potential of large antenna arrays at these frequencies to develop a low-complexity directional modulation technique: Antenna Subset Modulation (ASM) for point-to-point secure wireless communication. The main idea in ASM is to communicate information by modulating the far-field radiation pattern of the array at the symbol rate. By driving only a subset of antennas and changing the subset used for each symbol transmission the far-field pattern is modulated. Two techniques for implementing antenna subset selection are proposed. The first technique is simple where the antenna subset to be used is selected at random for every symbol transmission. While randomly switching antenna subsets does not affect the symbol modulation for a desired receiver along the main lobe direction, it effectively randomizes the amplitude and phase of the received symbol for an eavesdropper along a sidelobe. Using a simplified statistical model for random antenna subset selection, an expression for the average symbol error rate (SER) is derived as a function of observation angle for linear arrays. To overcome the problem of large peak sidelobe level in random antenna subset switching, an optimized antenna subset selection procedure based on simulated annealing is then discussed. Finally, numerical results comparing the average SER performance of the proposed techniques against conventional array transmission are presented. While both methods produce a narrower information beam-width in the desired direction, the optimized antenna subset selection technique is shown to offer better security and array performance. / text

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The proliferation of connected embedded devices has driven wireless communications into commercial, military, industrial, and personal systems. It is unreasonable to expect privacy and security to be inherent in these networks given the spatial density of these devices, limited spectral resources, and the broadcast nature of wireless communications systems. Communications for these systems must have sufficient information capacity and secrecy capacity while typically maintaining small size, light weight, and minimized power consumption. With increasing crowding of the electromagnetic spectrum, interference must be leveraged as an available resource. This work develops a new beamforming method for direction-dependent modulation that provides wireless communications devices with enhanced physical layer security and the ability to simultaneously communicate and harvest energy by exploiting co-channel interference. We propose a method that optimizes a set of time-varying array steering vectors to enable direction-dependent modulation, thus exploiting a new degree of freedom in the space-time-frequency paradigm. We formulate steering vector selection as a convex optimization problem for rapid computation given arbitrarily positioned array antenna elements. We show that this method allows us to spectrally separate co-channel interference from an information-bearing signal in the analog domain, enabling the energy from the interference to be diverted for harvesting during the digitization and decoding of the information-bearing signal. We also show that this method provides wireless communications devices with not only enhanced information capacity, but also enhanced secrecy capacity in a broadcast channel. By using the proposed method, we can increase the overall channel capacity in a broadcast system beyond the current state-of-the-art for wireless broadcast channels, which is based on static coding techniques. Further, we also increase the overall secrecy capacity of the system by enabling secrecy for each user in the system. In practical terms, this results in higher-rate, confidential messages delivered to multiple devices in a broadcast channel for a given power constraint. Finally, we corroborate these claims with simulation and experimental results for the proposed method. / PHD