Current commodity RFID systems incur high communication overhead due to severe tag-to-tag collisions. Although some recent works have been proposed to support parallel decoding for concurrent tag transmissions, they require accurate channel measurements, tight tag synchronization, or modifications to standard RFID tag operations. In this paper, we present BiGroup, a novel RFID communication paradigm that allows the reader to decode the collision from multiple commodity-off-the-shelf (COTS) RFID tags in one communication round. In BiGroup, COTS tags can directly join ongoing communication sessions and get decoded in parallel. The collision resolution intelligence is solely put at the reader side. To this end, BiGroup examines the tag collisions at RFID physical layer from constellation domain as well as time domain, exploits the under-utilized channel capacity due to low tag transmission rate, and leverages tag diversities. We implement BiGroup with USRP N210 software radio that is able to read and decode multiple concurrent transmissions from COTS passive tags. Our experimental study gives encouraging results that BiGroup greatly improves RFID communication efficiency, i.e., 11 times performance improvement compared with the alternative decoding scheme for COTS tags.

Estimating the number of RFID tags is a fundamental operation in RFID systems and has recently attracted wide attentions. Despite the subtleties in their designs, previous methods estimate the tag cardinality from the slot measurements, which distinguish idle and busy slots and based on that derive the cardinality following some probability models. In order to fundamentally improve the counting efficiency, in this paper we introduce PLACE, a physical layer based cardinality estimator. We show that it is possible to extract more information and infer integer states from the same slots in RFID communications. We propose a joint estimator that optimally combines multiple sub-estimators, each of which independently counts the number of tags with different inferred PHY states. Extensive experiments based on the GNURadio/USRP platform and the large-scale simulations demonstrate that PLACE achieves approximately 3 ~ 4× performance improvement over state-of-the-art cardinality estimation approaches.

Estimating the number of RFID tags is a fundamental operation in RFID systems and has recently attracted wide attentions. Despite the subtleties in their designs, previous methods estimate the tag cardinality from the slot measurements, which distinguish idle and busy slots and based on that derive the cardinality following some probability models. In order to fundamentally improve the counting efficiency, in this paper we introduce PLACE, a physical layer based cardinality estimator. We show that it is possible to extract more information and infer integer states from the same slots in RFID communications. We propose a joint estimator that optimally combines multiple sub-estimators, each of which independently counts the number of tags with different inferred PHY states. Extensive experiments based on the GNURadio/USRP platform and the large-scale simulations demonstrate that PLACE achieves approximately 3~4× performance improvement over state-of-the-art cardinality estimation approaches.

Current commodity RFID systems incur high communication overhead due to severe tag-to-tag collisions. Although some recent works have been proposed to support parallel decoding for concurrent tag transmissions, they require accurate channel measurements, tight tag synchronization, or modifications to standard RFID tag operations. In this paper, we present BiGroup, a novel RFID communication paradigm that allows the reader to decode the collision from multiple COTS (commodity-off-the-shelf) RFID tags in one communication round. In BiGroup, COTS tags can directly join ongoing communication sessions and get decoded in parallel. The collision resolution intelligence is solely put at the reader side. To this end, BiGroup examines the tag collisions at RFID physical layer from constellation domain as well as time domain, exploits the under-utilized channel capacity due to low tag transmission rate, and leverages tag diversities. We implement BiGroup with USRP N210 software radio that is able to read and decode multiple concurrent transmissions from COTS passive tags. Our experimental study gives encouraging results that BiGroup greatly improves RFID communication efficiency, i.e., 11× performance improvement compared to the alternative decoding scheme for COTS tags and 6× gain in time efficiency when applied to EPC C1G2 tag identification.

802.11 WLANs suffer from high packet losses due to interference and noise. Packet retransmission is a fundamental way to recover a lost packet. To extract useful information from incorrect symbols and improve retransmission efficiency, we present MISC, a packet retransmission scheme that merges incorrect symbols from multiple transmissions to produce correct ones. MISC proactively creates constellation diversity by rearranging the constellation maps in retransmissions. MISC addresses practical implementation issues and makes minimum amendments to integrate into current 802.11 WLAN framework. We implement MISC in an 802.11-based GNURadio/USRP platform and conduct extensive experiments to evaluate its efficacy. Experiment results demonstrate that MISC can substantially improve the throughput.

The phone attitude is an essential input to many smartphone applications. Based on in-depth understanding of the nature of the MEMS gyroscope and other IMU sensors, we propose A3 - an accurate and automatic attitude detector for commodity smartphones. In the demo, we show the performance of our attitude tracking algorithm and its usability in attitude-based mobile applications.