Bryan Paul

Inner Bounds on Performance of Radar and Communications Co-Existence

We investigate methods of co-existence between radar and communications systems. Each system typically considers the other system a source of interference. Consequently, the traditional solution is to isolate the two systems spectrally or spatially. By considering a cooperative radar and communications signaling scheme, we derive achievable bounds on performance for a receiver that observes communications and radar return in the same frequency allocation. We assume the radar and communications operations to be a single joint system. Bounds on performance of the joint system are measured in terms of data information rate for communications and a novel radar estimation information rate for the radar.

Joint communications and radar performance bounds under continuous waveform optimization: The waveform awakens

We develop a joint radar and communications performance bound by optimizing waveforms jointly for the simultaneous radar return and communications receiver. We develop radar waveforms that jointly maximize radar estimation rate and communications data rate for a shared spectrum. As an extension to our previous efforts, we consider a parametrically defined radar spectral weighting of the waveform, balancing the potential increase in entropy due to range sidelobes with the potential improvement in main lobe performance. Successive interference cancellation is used to mitigate an in-band communications user signal after the predicted radar return is removed. The emphasis on radar estimation rate and communications rate is varied, and results are obtained using numerical methods.

Extending joint radar-communications bounds for FMCW radar with Doppler estimation

We investigate cooperative in-band radar and communications signaling for frequency-modulated continuous-wave (FMCW) radar and Doppler estimation. While each system typically considers the other system a source of interference, by considering the radar and communications operations to be a single system, joint performance bounds can be formulated. We extend previous work where a novel estimation and information theoretic bound formulation was constructed for a receiver that observes communications and radar returns in the same frequency allocation. While the previous work derived a joint performance bound in terms of the communications rate and the target delay estimation rate of the system for pulsed waveforms, we derive a similar bound for FMCW radar and include Doppler estimation. This extension is important given the rise of popularity of FMCW radars, and since the continuous signaling brings them closer to how communications systems operate.

Constant information radar for dynamic shared spectrum access

We derive the constant information radar, or CIR. Previous works developed the notion of a radar estimation rate, a measure of information shared between the true target range and range-rate, and the actual noisy measurement over time. This measure provided a means to compare various cooperative schemes for shared spectrum access for radar and communications (SSPARC). Since it provides a measure of target uncertainty and thus information transfer for a given tracking loop period, it can be used to modulate radar emission rate to minimize shared spectrum impact to communications networks.

Survey of RF Communications and Sensing Convergence Research

Wireless mediums, such as RF, optical, or acoustical, provide finite resources for the purposes of remote sensing (such as radar) and data communications. Often, these two functions are at odds with one another and compete for these resources. Applications for wireless technology are growing rapidly, and RF convergence is already presenting itself as a requirement for both users as consumer and military system requirements evolve. The broad solution space to this complex problem encompasses cooperation or codesigning of systems with both sensing and communications functions. By jointly considering the systems during the design phase, rather than perpetuating a notion of mutual interference, both system’s performance can be improved. We provide a point of departure for future researchers that will be required to solve this problem by presenting the applications, topologies, levels of system integration, the current state of the art, and outlines of future information-centric systems.

Joint radar-communications information bounds with clutter: The phase noise menace

We model the effects of phase noise on clutter cancellation and study the overall impact it has on the radar estimation rate. Cooperative bounds involving radar cancellation for additional communications access are impacted by complicating the overall model. We assume the clutter is static with small intrinsic clutter motion (ICM). Treating the clutter cancellation residual due to intrinsic clutter motion and phase noise as an additional noise source, the radar estimation rate is negatively impacted. This clutter cancellation residual further degrades the communications channel, affecting the communications data rate as well. We also study the relationship between the clutter cancellation residual and the range of the scatterer.

The Constant Information Radar

The constant information radar, or CIR, is a tracking radar that modulates target revisit time by maintaining a fixed mutual information measure. For highly dynamic targets that deviate significantly from the path predicted by the tracking motion model, the CIR adjusts by illuminating the target more frequently than it would for well-modeled targets. If SNR is low, the radar delays revisit to the target until the state entropy overcomes noise uncertainty. As a result, we show that the information measure is highly dependent on target entropy and target measurement covariance. A constant information measure maintains a fixed spectral efficiency to support the RF convergence of radar and communications. The result is a radar implementing a novel target scheduling algorithm based on information instead of heuristic or ad hoc methods. The CIR mathematically ensures that spectral use is justified.

Radar-Communications Convergence: Coexistence, Cooperation, and Co-Design

In this paper, we introduce a radar information metric, the estimation rate, that allows the radar user to be considered in a multiple-access channel enabling performance bounds for joint radar-communications coexistence to be derived. Traditionally, the two systems were isolated in one or multiple dimensions. We categorize new attempts at spectrum-space-time convergence as either coexistence, cooperation, or co-design. The meaning and interpretation of the estimation rate and what it means to alter it are discussed. Additionally, we introduce and elaborate on the concept of “not all bits are equal,” which states that communications rate bits and estimation rate bits do not have equal value. Finally, results for joint radar-communications information bounds and their accompanying weighted spectral efficiency measures are presented.

Simultaneous radar detection and communications performance with clutter mitigation

We analyze the performance of a joint radar-communications receiver performing target detection while simultaneously decoding a message from an in-band communications user. We assume that there is clutter in the environment and that the joint receiver performs basic clutter mitigation. Inner bounds on the performance of the joint radar-communications receiver are then formulated. Bounds on performance of the joint system are measured in terms of data information rate for communications and area under the receiver operating characteristic (ROC) curve for radar.

Estimation information bounds using the I-MMSE formula and Gaussian mixture models

We derive a method to bound the mutual information between a noisy and noiseless measurement exploiting the I-MMSE estimation and information theory connection. Modeling the source distribution as a Gaussian mixture model, a closed form expression for upper and lower bounds of the minimum mean square error is found using recent results. Using the connection between rate of information relative to SNR and the minimum mean square error of the estimator, the mutual information can be bounded as well for arbitrary source distributions in Gaussian noise.