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Full-Text Articles in Physical Sciences and Mathematics
The Final Case Of The Decoding Delay Problem For Maximum Rate Complex Orthogonal Designs, Sarah Adams, Nathaniel Karst, Mathav Murugan
The Final Case Of The Decoding Delay Problem For Maximum Rate Complex Orthogonal Designs, Sarah Adams, Nathaniel Karst, Mathav Murugan
Sarah Spence Adams
Complex orthogonal space-time block codes (COSTBCs) based on generalized complex orthogonal designs (CODs) have been successfully implemented in wireless systems with multiple transmit antennas and single or multiple receive antennas. It has been shown that for a maximum rate COD with 2m-1 or 2m columns, a lower bound on decoding delay is (m-1 2m) and this delay is achievable when the number of columns is congruent to 0, 1 , or 3 modulo 4. In this paper, the final case is addressed, and it is shown that when the number of columns is congruent to 2 modulo 4, the lower …
Synthesis Of Static And Dynamic Multiple-Input Translinear Element Networks, Bradley Minch
Synthesis Of Static And Dynamic Multiple-Input Translinear Element Networks, Bradley Minch
Bradley Minch
In this paper, we discuss the process of synthesizing static and dynamic multiple-input translinear element (MITE) networks systematically from high-level descriptions given in the time domain, in terms of static polynomial constraints and algebraic differential equations. We provide several examples, illustrating the process for both static and dynamic system constraints. Although our examples will all involve MITE networks, the early steps of the synthesis process are equally applicable to the synthesis of static and dynamic translinear-loop circuits.
Interactionless Calendar-Based Training For 802.11 Localization, Mark Chang, Andrew J. Barry, Noah L. Tye
Interactionless Calendar-Based Training For 802.11 Localization, Mark Chang, Andrew J. Barry, Noah L. Tye
Mark L. Chang
This paper presents our work in solving one of the weakest links in 802.11-based indoor-localization: the training of ground-truth received signal strength data. While crowdsourcing this information has been demonstrated to be a viable alternative to the time consuming and accuracy-limited process of manual training, one of the chief drawbacks is the rate at which a system can be trained. We demonstrate an approach that utilizes users' calendar and appointment information to perform interactionless training of an 802.11-based indoor localization system. Our system automatically determines if a user attended a calendar event, resulting in accuracy comparable to our previously published …