You are presented with multiple paper abstracts, alongside the associated literature review and chapter titles. Given the provided information, you are going to do a literature review. Please generate a coherent literature review that synthesizes the content, draws connections between different works, highlights major findings, and identifies any gaps in the existing research.

Literature Review Title: Survey of RF Communications and Sensing Convergence Research 
Chapter Title:  C. CONSTRAINED CHANNEL ESTIMATION AND COMMUNICATIONS 
1. Abstract of Cited Paper (BIB001):  Abstract Due to the explosive growth of wireless devices and wireless traffic, the spectrum scarcity problem is becoming more urgent in numerous Radio Frequency (RF) systems. At the same time, many studies have shown that spectrum resources allocated to various existing RF systems are largely underutilized. As a potential solution to this spectrum scarcity problem, spectrum sharing among multiple, potentially dissimilar RF systems has been proposed. However, such spectrum sharing solutions are challenging to develop due to the lack of efficient coordination schemes and potentially different PHY/MAC properties. In this paper, we investigate existing spectrum sharing methods facilitating coexistence of various RF systems. The cognitive radio technique, which has been the subject of various surveys, constitutes a subset of our wider scope. We study more general coexistence scenarios and methods such as coexistence of communication systems with similar priorities, utilizing similar or different protocols or standards, as well as the coexistence of communication and non-communication systems using the same spectral resources. Finally, we explore open research issues on the spectrum sharing methods as well as potential approaches to resolving these issues.

Literature Review:
In Reference BIB001 , information theoretic bounds on a joint capacity-distortion function are developed. In this work, the balance between sending arbitrary data and distortion in estimating the communications channel is explored. Sending less information and more known signals, the channel can be better estimated. A better channel estimate ultimately supports an increased channel capacity. However, the average rate is reduced in sending known symbols to estimate the channel. It was shown in this work that, for a channel with uniform estimation costs, a system trying to transmit information and simultaneously perform channel state estimation can achieve the following rate-distortion tradeoff: where B is the bandwidth of the system, γ is a system parameter swept from 0 to 1, P c is the received communications power, σ 2 targ is the radar residual variance after radar cancelation, and P n is the thermal noise power. The distortion function given by Equation (10) can be viewed as the variance of estimation (channel state estimation or a more general parameter estimation) and can be applied to the estimation rate given by Equation BIB002 , to obtain a 'estimation cost' rate. The communications rate versus the estimation cost rate curve is shown in Figure 21 . FIGURE 21. Multiple-access bound for joint communications and channel estimation. The communications channel consists of a known direct path channel and an additive radar bounce channel interference term. The monostatic radar signal sends a known waveform, and knows the target channel from the tracking estimation. The communications transmitter sends its own signal direct to the receiver, which has a perfect direct path, but also receives an interfering bounce path radar return from the target. The curve in light blue represents trading radar channel estimation for data rate. This example assumes a monostatic radar with an independently transmitted communications signal also broadcast to a destination node, or a modification to the monostatic broadcast channel covered earlier. Due to the monostatic return of the target, the radar knows the radar signal bounce path channel to the destination node, which is modeled as an additional additive Gaussian term after successive interference cancellation (SIC) processing. The joint curve shown represents the tradeoff the communications user has at estimating the bounce channel (performing radar state estimation) and communicating arbitrary data. VOLUME 5, 2017 VII. SUMMARY We see this work as a point of departure. We defined the problem of spectral congestion, and the more broad concern of allocation of wireless resources to remote sensing and communications systems. Applications for joint sensingcommunications were discussed, both past and present. The primitive heterogeneous two-user system topologies that support RF convergence were enumerated and explored. The various level of system design, from complete isolation to ground-up co-design of a joint radar-communications system were discussed in detail. The conflicting waveform requirements for radar and communications were illustrated with a comparison between linear FM chirps and modern orthogonal frequency-division multiplexing (OFDM) communications waveforms. An overview was provided of the state of the art of joint radar-communications encompassing systems that coexist, cooperate, and are co-designed. A discussion of future information-based systems was presented to highlight the utility and need for joint spectral efficiency measures and bounds. This area of research is highly active and accelerating in response to the problems faced by wireless systems. We see tremendous opportunity in RF convergence as researchers, governments, and commercial industries continue to develop more sophisticated systems with dwindling available wireless resources.