Dawei Shen

Separation of multiple passive RFID signals using Software Defined Radio

We present a practical design of an RFID reader that is capable of reading multiple passive tags through joint decoding. The reader is implemented and analyzed using the GNU Software Defined Radio system. We use low frequency (LF) 125kHz commodity MIT ID cards in the experiment, and discuss extensions to decoding high frequency (HF) tags. This design reconsiders opportunities available in the lower layers of RFID design. Physical layer communication is analyzed rigorously and a complete system design is introduced as a result. We demonstrate this by exploring the differences in amplitudes and phase offsets among signal components, multiple tags can be separated and efficiently decoded using joint decoding. System performance is analyzed with both implementation and simulation. Based on these results, we summarize opportunities for improving industrial auto-collision algorithms with multiple-tag decoding capability.

Follow the Profit or the Herd? Exploring Social Effects in Peer-to-Peer Lending

This paper examines the impacts of social factors on lenders’ decision-making in online peer-to-peer (P2P) lending. Data collected from a major U.S. online loan marketplace, Prosper.com, have been analyzed. We propose a model based on preferential attachment and fragmentation to model the bidding behavior of lenders. Our data analysis presents strong empirical evidence that there were significant herding effects when lenders made their investment decisions on loan listings. The distribution of the number of bids put on loan listings exhibits a power law with an exponential cutoff, which matches what the model predicts. The paper concludes that lenders on Prosper did not make rational investment decisions based on risk and returns, but followed the herd.

Barter: mechanism design for a market incented wisdom exchange

Information markets benefit the communities they serve by facilitating electronic distributed exchange and enhancing knowledge sharing, innovation, and productivity. This research explores innovative market mechanisms to build incentives while encouraging pro-social behavior. A key advantage of this study is a direct appeal to theories of information economics and macro policies to market design. We built and deployed a web-based software platform called Barter at several universities. Preliminary analysis of user data helps test information market effectiveness and illustrate effects of various market interventions. We present our design framework, demonstrate why such an architecture provides sustainable incentives, and list key findings learned in the process of system deployment.

On Frame Synchronization for Multiple Access Channels

The problem of frame synchronization is formulated and investigated for multiple access channels (MAC). Several decision rules for locating the starting positions in continuously transmitted frames are proposed and compared, for both user- synchronous and user-asynchronous cases. It is shown that the common decision rule based on the correlation statistic is suboptimal, and that correction terms need be added in order to achieve an improved detection performance. For the user- asynchronous case, the optimal joint decision rule is derived in analytical form for two-user MAC and is highly complex, and is shown to suffer from a high computational complexity. To reduce the complexity, suboptimal separate decision algorithms with and without Gaussian approximation are derived, and it is il- lustrated using Monte Carlo simulation that those low-complexity algorithms only incur a slight degradation in optimality. by the specific problem of RFID signal separation (6). When multiple RFID tags are activated, symbol-synchronous signals from these tags are simultaneously transmitted in a continuous and repeated fashion, with fixed sync-words inserted into the data streams. Such a system model exactly fits into the research domain of frame synchronization. In this paper, we investigate both the user-synchronous and user-asynchronous cases. In the user-synchronous case, transmitters are scheduled such that their transmitted frames align synchronously. We derive the optimal maximum a pos- terior (MAP) decision rule in this case, which akin to single- user channels includes a correction term in addition to the correlation statistic. In the more general and complicated user- asynchronous case, multiple transmitters start transmitting frames at different time instants and thus there are multiple frame positions to locate. The computational complexity of the MAP joint decision rule grows exponentially with the number of transmitters thus rendering it infeasible for practical implementation. Consequently, an alternative approach which performs frame synchronization for each transmitter separately is proposed, with and without the further complexity reduction via Gaussian approximation of multiple access interference. The performance of the various approaches is evaluated through Monte Carlo simulation, in which different design parameters like the choice of sync words, the relative signal strength between transmitters, and the number of transmitters are examined.

Connected Consumption: The Hidden Networks of Consumption

In this paper, we present the Connected Consumption Network (CCN) that allows a community of consumers to collaboratively sense the market from a mobile device, enabling more informed financial decisions in geo-local context. The mobile application allows one to log ones wish list and itemized list of transactions to form a social network around the list of interests. Individuals can share this data to inform and guide others in a timely, personal and contextual manner when they are shopping for a product or seeking a service. It can also help people connect opportunistically in a local area to make group purchases, to pick up an item for a friend, and to perform reverse auctions. We present the design, architecture and concept prototype. We simulate a social network with three months of existing credit/debit card transaction data in various geographical areas to analyze the mutual information and recommendations that can be shared among networked consumers.

Open Transaction Network: Connecting Communities of Experience through Mobile Transactions

In order to understand the value of social information in the context of mobile commerce, we created the Open Transaction Network (OTN), a collaborative, social transaction system. OTN uses voluntarily contributed transactions to index personal and social experiences in the physical world and to form dynamic communities around purchases. We use mobile phones and Open Spaces as portals to facilitate sharing of transactions. Through real world deployment we investigate the design elements and analyze users’ tolerance to sharing such experiences. The sociability threshold, introduced as a measure of user’s willingness to share for different categories of products, is found to correlate with price. The system was deployed to over 20 users over a 5 month period to allow the participants to share their in-store purchases. The analysis of empirical data shows that second degree connections are valuable for obtaining recommendations.