Robust OFDM integrated radar and communications waveform design based on information theory

Abstract

An integrated radar and communications system (IRCS) where a monostatic radar transceiver is employed for target classification while simultaneously used as a communications transmitter is considered. The radar combined propagation-target response (joint response of the radar propagation channel and target) and communications channel response are generally frequency selective but the corresponding frequency response functions are not exactly known. In particular, these frequency response functions are only known to lie in an uncertainty class. To ensure the IRCS simultaneously provides acceptable target classification performance and communications rate, a robust orthogonal frequency division multiplexing (OFDM) integrated radar and communications waveform (IRCW) design method is proposed. The approach finds a waveform that simultaneously provides a sufficiently large weighted sum of the communications data information rate (DIR) and the conditional mutual information (MI) between the observed signal and the radar target over the entire uncertainty class. First, the conditional MI and DIR based on the integrated OFDM radar and communications waveform are derived. Then, a robust OFDM IRCW optimization problem based on the minimax design philosophy is developed such that closed-form solution is derived. Finally, several numerical results are presented to demonstrate the effectiveness of the proposed method.Index Terms-Robust waveform design, integrated radar and communications, orthogonal frequency division multiplexing, conditional mutual information, data information rate I INTRODUCTIONWith the increased acceptance of communications and radar systems for both commercial and defense applications, the study of integrated systems has attracted significant attention in the signal processing community [1]-[3]. These systems have advantages in reducing the hardware cost and improving the spectrum usage. For example, [4] describes how radar, communications, and electronic 

A Multicarrier Phase‐Coded Waveform Design Scheme for Joint Radar and Communication System

“…In this subsection, we propose an integrated waveform design method by simultaneously maximizing SCNR and Shannon capacity, subject to both ISLR constraint and energy constraint. The method is formulated as 18) where γ represents the relative weight of SCNR with respect to Shannon capacity, and 0 ≤ γ ≤ 1. Notice that δ 0 is a predefined value representing the worst acceptable ISLR.…”

“…In practice, the phase code c p,m,n can be generated by several methods such as P4, Huffman and Costas coding [33] , etc. Nevertheless, for JRC system, c p,m,n is usually modulated by Phase shift keying (PSK) or Quadrature amplitude modulation (QAM) for communication purpose and generated randomly with uniform distribution [18] , thus…”

“…For the sake of communication data transmission in the frequency selective fading channel [25] , Shannon capacity for MCPC signal is chosen as the metric for communication performance, expressed as [18] C…”

“…For radar performance, the metrics for waveform design contain: ambiguity function [16,17] , mutual information [18,19] , probability of detection [20] , Signal-toclutter-to-noise ratio (SCNR) [21] , mean-square error [22,23] and Cramér-Rao Bound [24] , etc. For communication performance, Shannon capacity enables us to compute the highest rate at which reliable communication over the channel is possible [25] .…”

“…For communication performance, Shannon capacity enables us to compute the highest rate at which reliable communication over the channel is possible [25] . Under a fixed energy constraint, the shape of spectrum could be adaptively modified to match the subchannels and accordingly obtain the maximum information rate [18] . In addition, the Integrated sidelobe level ratio (ISLR) [26] is also an unavoidable metric.…”