Optimized Waveforms for 5G–6G Communication With Sensing: Theory, Simulations and Experiments

Joint communication and sensing (JCAS) is an emerging technology for managing efficiently the scarce radio frequency (RF) spectrum, and is expected to be a key ingredient in beyond fifth-generation (5G) networks. We consider a JCAS system, where the full-duplex radar transceiver and the communication transmitter are the same device, and pursue orthogonal frequency-division multiplexing (OFDM) waveform optimization by jointly minimizing the lower bounds of delay and Doppler estimation. This is attained by filling the empty subcarriers within the OFDM frame with optimized samples while reallocating a proportion of the communication subcarriers’ power, which essentially controls the fairness between the two functionalities. Both communication and filled radar subcarriers are used for radar processing. The optimized sample values are found analytically, and a computationally feasible algorithm is presented for this task. We also address how the peak-to-average power ratio of the waveform can be controlled and minimized along the optimization process. The results are then numerically evaluated in 5G New Radio (NR) network context, which indicate a trade-off between the minimization of the lower bounds. The main-lobe width and the peak side-lobe level (PSL) of the range and velocity profiles of the radar image are also analyzed. An inverse relation between the lower bounds and the PSLs is observed, while the main-lobe width can be minimized simultaneously. The trade-off between communication and sensing is investigated, which indicates that the lower bounds can be improved at the cost of the communication capacity. Moreover, over-the-air RF measurements are carried out with unoptimized and optimized 5G NR waveforms at the 28 GHz mm-wave band, to validate the range profile’s PSL improvement in an outdoor mapping scenario, depicting considerable performance gain.