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: A Survey on Deep Learning Techniques in Wireless Signal Recognition 
Chapter Title:  Burst Signal Recognition. 
1. Abstract of Cited Paper (BIB001):  Recently, radar frequency bands have been drawing much attention as possible candidates for cognitive radio, since their utilization was revealed to be relatively low. One important functionality of a cognitive radio system is the spectrum sensing, which detects the presence of a primary user (PU) signal. The pulse radar signal, which is the PU signal in radar bands, is characterized by its sparsity in the time domain. Exploiting this sparsity, we present a spectrum sensing technique that combines the intermediate detections from multiple small sliding sensing windows of the received radar signal into a final decision. We also show by computer simulation that it can achieve improvement of the sensing performance in comparison with the conventional single-window-based spectrum sensing approach.

Literature Review:
Burst signal has been widely used in military field and there will be broad prospects for dynamic spectrum access in the future. The burst signal has the characteristics of short duration and uncertainty of starting and ending time, which poses great challenges to Wireless Communications and Mobile Computing 9 signal recognition  BIB001 BIB002 . Generally, the processing flow of signal recognition includes data acquisition, preprocessing, classification, and decision. The high quality labels have a crucial role for a satisfactory recognition accuracy but are relatively time-consuming in burst communication systems. Therefore, there are still research prospects on the identifying burst signals.