An efficient waveform diversity based on variational mode decomposition of coded beat‐frequency shifted signals algorithm for multiple‐input multiple‐output millimetre‐wave imaging

Abstract

Waveforms used in multiple-input multiple-output (MIMO) systems must be considered in such a way that individual transceiver (T-R) pairs can be separated from the composite received signal. An algorithm called variational mode decomposition of coded beatfrequency shifted signals (VMD-CBFSS) is presented for waveform diversity. First, transmitters are divided into several groups. A small shift is applied to the carrier frequency of the transmitters of different groups. Also, signals within each group are encoded by assigning a binary phase in a time block. On the receiver side, by using a multiresolution analysis technique, the combined signal is decomposed into its main frequency components and then the composite signals of each group are decoded to retrieve each T-R pair. VMD-CBFSS provides an efficient solution in terms of overall transmitting time and sampling rate in addition to robustness against channel noise. Moreover, the algorithm is employed in a near-field MIMO millimetre-wave imaging system, and results are presented in the form of numerical simulations.This is an open access article under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made.

A multi-resolution analysis-based approach to accelerate data acquisition for near-field MIMO millimeter-wave imaging

“…According to the designs done in [4], on the Tx-side, first, T N Tx antennas are divided into G non-overlapping groups so that ). The carrier frequency of each group has a small offset f ∆ compared to the previous group, so that 0 f f ∆ ≪ .…”

“…The carrier frequency of each group has a small offset f ∆ compared to the previous group, so that 0 f f ∆ ≪ . Finally, before transmitting, the signals within the th g group are encoded by assigning a binary phase in a time block of length g P P T [4]. Figure 3…”

“…However, MIMO systems usually require higher levels of design and signal processing in the Tx and Rx sections. An important challenge in using MIMO systems is the need to generate optimal signals that are orthogonal to each other (so-called waveform diversity) [4]; in other words, the transmitted waveforms must be designed and optimized in such a way that all pairs of individual Tx-Rx signals can be separated from the composite received signal at the Rx. Also, accurate retrieval of each pair of signals requires some efficient processing on the Rx.…”

“…Recently in [4], an efficient mechanism for waveform diversity in a MIMO structure is proposed. The Txs are first classified into several groups, and the same carrier frequency is assigned to the corresponding signals of the Txs in each group.…”

Efficient 3D Image Reconstruction for Near-Field Microwave Imaging Using Dynamic Metasurface Antenna

“…In recent decades, the widespread applications of microwave imaging in areas such as security screening, medical imaging, nondestructive testing and evaluation, structural health monitoring, and through-wall imaging have led to significant advances in various layers of imaging radars, from the physical layer to the system and signal processing layers [1], [2]. In imaging systems, gathering the scene data is usually done either by mechanical scanning or by electronic scanning (large phased arrays with independent antennas) [3], [4]. Although the electronic scanning mechanism may be a suitable solution to improve the data acquisition rate, phased array antennas may be expensive and bulky.…”