# Fast and Reliable Burst Data Transmission for Backscatter Communications
## 1 Introduction  
Currently, miniature and ultra-low power sensors are widely used in urban and indoor areas. They are attached to common items and logistics to be used to track these objects [1]. Such devices utilize energy in the environment or RF to power and communicate with RFID readers by backscattering for data transmission. Computational radio frequency identification (CRFID) is a kind of passive sensing node that captures RF energy [2] and presents a new frontier for distributed sensing [3]. CRFIDs follow the RFID backscatter communication mode, which obtains energy from the RF signal emitted by the reader and modulates the encoded data back into the reader in the received signal. CRFID sensors are very different from existing battery sensor platforms and commercial RFID systems. They rely entirely on the energy of the capacitor for continuous sensing and efficient backscatter communication for data transmission. Compared to commercial RFID systems, they are able to sense, calculate, and store not just able to simply identify. In recent years, CRFID sensor systems have received increasing attention because of their potential for battery-free permanent sensing [4; 5; 6]. Typical CRFID systems include the WISP (Wireless Identification and Sensing Platform) [7], jointly developed by Intel and the University of Washington, and the UMass Moo [8], developed by the University of Michigan on the basis of WISP. In this paper, we focus on mobile CRFID [9] and consider CRFID to use the harvesting energy for burst data transmission. CRFIDs are very small and can be deployed in large numbers indoors on moving objects or on the human body. As they move near the reader, the buffered data are transmittedto the reader via backscatter communication, such as mobility health monitoring. With the widespread deployment of CRFIDs, sensing tasks are becoming more complex and the sensing data is increasing. In particular, when it needs to be transmitted quickly and efficiently for critical and emergency data [10], such as clinical monitoring and industrial gas leaks, current backscatter communication brings some challenges. First, commercial RFID systems follow the EPC C1G2 protocol [11], which is designed to read a small amount of data (identifier EPC) for a large number of tags but is less efficient in scenarios where a small number of CRFIDs need to transfer large amounts of buffered data. Second, the key parameter controlling the efficiency of the EPC C1G2 protocol is the size of the window Q value [12], which is set by the reader based on its estimated number of tags. Also, the QueryRep or QueryAdj command of the tag listening to the unresponsive slot generates a lot of overhead, resulting in wasted energy and time [13]. Third, mobility of CRFID sensors results in dynamic changes in both energy-harvesting and channel conditions [14]. When the energy-harvesting conditions are poor, CRFID needs a long sleep charging time to reach the working voltage; when the channel quality is poor, bit errors easily occur, resulting in data frames being discarded, and CRFID needs to be recharged again, which leads to low goodput. In response to the above difficulties, the following are the chief contributions of our work:  
* We propose a method for burst data transmission by fragmenting large data packets into blocks. Then, we dynamically adjust the frame length of every block through an online adjustment strategy at runtime by the feedback of the reader. * We introduce a burst transmission mechanism. The core idea is to let a tag occupy all time slots for burst transmission when there are critical and emergency data to be transmitted, which reduces the idle time slot. * We utilize erasure codes to reduce acknowledgement frame waiting delay and to avoid retransmission overhead, which improves system robustness and reliability. * Under specific energy-harvesting and channel conditions, our proposed scheme is much better than the EPC C1G2 protocol fixed frame length approach and DFCA scheme, and the performance can converge to near optimal.