Multi-band Signaling Research Articles

Deep-Learning-Based Multiband Signal Fusion for 3-D SAR Superresolution

Three-dimensional (3-D) synthetic aperture radar (SAR) is widely used in many security and industrial applications requiring high-resolution imaging of concealed or occluded objects. The ability to resolve intricate 3-D targets is essential to the performance of such applications and depends directly on system bandwidth. However, because high-bandwidth systems face several prohibitive hurdles, an alternative solution is to operate multiple radars at distinct frequency bands and fuse the multiband signals. Current multiband signal fusion methods assume a simple target model and a small number of point reflectors, which is invalid for realistic security screening and industrial imaging scenarios wherein the target model effectively consists of a large number of reflectors. To the best of our knowledge, this study presents the first use of deep learning for multiband signal fusion. The proposed network, called <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$kR$</tex-math></inline-formula> -Net, employs a hybrid, dual-domain complex-valued convolutional neural network (CV-CNN) to fuse multiband signals and impute the missing samples in the frequency gaps between subbands. By exploiting the relationships in both the wavenumber domain and wavenumber spectral domain, the proposed framework overcomes the drawbacks of existing multiband imaging techniques for realistic scenarios at a fraction of the computation time of existing multiband fusion algorithms. Our method achieves high-resolution imaging of intricate targets previously impossible using conventional techniques and enables finer resolution capacity for concealed weapon detection and occluded object classification using multiband signaling without requiring more advanced hardware. Furthermore, a fully integrated multiband imaging system is developed using commercially available millimeter-wave (mmWave) radars for efficient multiband imaging. Using two mmWave radars, each with a bandwidth of 4 GHz operating at 60 GHz and 77 GHz, the proposed <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$kR$</tex-math></inline-formula> -Net is employed to achieve an effective bandwidth of 21 GHz by robustly estimating the full-band signal. Additionally, the generalizability of the proposed technique is demonstrated across multiband sensing scenarios in the mmWave and terahertz (THz) frequencies. Extensive numerical simulations and empirical experiments are conducted to illustrate the superiority of our approach over existing methods for a diverse set of realistic 3-D SAR imaging scenarios.

A 16-Gb/s 14.7-mW Tri-Band Cognitive Serial Link Transmitter With Forwarded Clock to Enable PAM-16/256-QAM and Channel Response Detection

A cognitive tri-band transmitter (TX) with a forwarded clock using multiband signaling and high-order digital signal modulations is presented for serial link applications. The TX features learning an arbitrary channel response by sending a sweep of continuous wave, detecting power level at the receiver side, and then adapting modulation scheme, data bandwidth, and carrier frequencies accordingly based on detected channel information. The supported modulation scheme ranges from nonreturn to zero/Quadrature phase shift keying (QPSK) to Pulse-amplitude modulation (PAM) 16/256-Quadrature amplitude modulation(QAM). The proposed highly reconfigurable TX is capable of dealing with low-cost serial channels, such as low-cost connectors, cables, or multidrop buses with deep and narrow notches in the frequency domain (e.g., a 40-dB loss at notches). The adaptive multiband scheme mitigates equalization requirements and enhances the energy efficiency by avoiding frequency notches and utilizing the maximum available signal-to-noise ratio and channel bandwidth. The implemented TX prototype consumes a 14.7-mW power and occupies 0.016 mm2 in a 28-nm CMOS. It achieves a maximum data rate of 16 Gb/s with forwarded clock through one differential pair and the most energy efficient figure of merit of 20.4 $\mu \text{W}$ /Gb/s/dB, which is calculated based on power consumption of transmitting per gigabits per second data and simultaneously overcoming per decibel worst case channel loss within the Nyquist frequency.

A Pulsed UWB Transceiver in 65 nm CMOS With Four-Element Beamforming for 1 Gbps Meter-Range WPAN Applications

A pulsed ultrawideband (UWB) transceiver with four-element receiver beamforming is described. Multiband signaling with frequency hopping is employed to efficiently utilize spectrum from 6 to 8.5 GHz to achieve a high data rate of 1 Gbps. A pulse-based signaling approach with low implementation complexity is utilized. Frequency-hopping reduces the overhead for multiband implementation by sharing multiple circuit blocks in the transmitter and receiver paths. The sinusoids for pulse-shaping and single-sideband mixing are synthesized using multiphase LOs to avoid high-speed DACs. The receiver channelizes the spectrum with cascaded mixers for which the LO signals are derived from a single PLL. A single-input multi-output (SIMO) beamforming architecture is employed to increase the sensitivity of the receiver. Beamforming is performed at baseband to avoid the requirement for a wideband delay circuit. The prototype is implemented in 65 nm CMOS and meets the ECC mask. The measured power dissipation of the transmitter is 221 mW, while that of the receiver is 211 mW. A receiver sensitivity of -69 dBm is achieved and Gbps communication over 2 m is demonstrated.

On adaptive multiband signal detection with the SMI algorithm

In a nonstationary and/or nonhomogeneous interference environment, an adaptive system for target detection may suffer a severe performance degradation due to the lack of a sufficient amount of data from which the system can learn (estimate) the statistics of the environment. The detection performance of an adaptive system, which employs a frequency diversity (multiband) signaling waveform and a multiband sample matrix inversion algorithm (SMI), is analyzed. By comparison with the corresponding single-band system under the chosen system constraint, it is shown that the multiband system can significantly outperform the single band when the amount of data available from a single frequency band is severely limited by the environment. >