Abstract-This work investigates the lower bounds of wireless localization accuracy using signal strength on commodity hardware. Our work relies on trace-driven analysis using an extensive indoor experimental infrastructure. First, we report the best experimental accuracy, twice the best prior reported accuracy for any localization system. We experimentally show that adding more and more resources (e.g., training points or landmarks) beyond a certain limit, can degrade the localization performance for lateration-based algorithms, and that it could only be improved further by "cleaning" the data. However, matching algorithms are more robust to poor quality RSS measurements. We next compare with a theoretical lower bound using standard Cramér Rao Bound (CRB) analysis for unbiased estimators, which is frequently used to provide bounds on localization precision. Because many localization algorithms are based on different mathematical foundations, we apply a diverse set of existing algorithms to our packet traces and found that the variance of the localization errors from these algorithms are smaller than the variance bound established by the CRB. Finally, we found that there exists a wide discrepancy from what freespace models predict in the signal to distance function even in an environment with limited shadowing and multipath, thereby imposing a fundamental limit on the achievable localization accuracy indoors.

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Abstract-We present the DECODE technique to determine whether a set of transmitters are comoving, i.e., moving together in close proximity. Comovement information can find use in applications ranging from inventory tracking to social network sensing and to optimizing mobile device localization. The positioning errors from indoor RSS-based localization systems tend to be too large, making it difficult to detect whether two devices are moving together based on the interdevice distances. DECODE achieves accurate comovement detection by exploiting the correlations in positioning errors over time. DECODE can not only be implemented in the position space but also in the signal space where a correlation in shadow fading due to objects blocking the path between the transmitter and receiver exists. This technique requires no change in or cooperation from the tracked devices other than sporadic transmission of packets. Using experiments from an office environment, we show that DECODE can achieve near-perfect comovement detection at walking speed mobility using correlation coefficients computed over approximately 60-second time intervals. We further show that DECODE is generic and could accomplish detection for mixed mobile transmitters of different technologies (IEEE 802.11b/g and IEEE 802.15.4), and our results are not very sensitive to the frequency at which transmitters communicate.

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We present the DECODE technique to determine from a remote receiver whether a set oftransmitters are co-moving, i.e., moving

Abstract-This paper presents an experimental study on the spectrum coexistence 1 problems between multi-radio platforms in dense-radio physical world environments. Computing and communication devices such as laptops and cellular phones with multiple radios including WiFi, Bluetooth, UWB, WiMax and Zigbee in a small conference room face significant interference problems. A realistic small office/home office (SOHO) scenario with ~10-25 multi-radio platforms is mapped onto the ORBIT radio grid testbed, and system throughput results are obtained experimentally, demonstrating significant degradation due to inter-platform interference. The CSCC (Common Spectrum Coordination Channel) protocol proposed in earlier work is used as the basis for implementing a set of distributed spectrum coexistence algorithms intended to improve system performance. Detailed results from ORBIT testbed experiments are given for the proposed CSCC-based distributed spectrum coordination algorithms. The results show significant performance gains due to CSCC coordination, typically achieving ~2x improvement in system throughput for WiFi/Bluetooth dual radio scenarios.