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Abstract-In this paper, we present and study a digitalcontrolled method, called SoftNull, to enable full-duplex in many-antenna systems. Unlike most designs that rely on analog cancelers to suppress self-interference, SoftNull relies on digital transmit beamforming to reduce self-interference. SoftNull does not attempt to perfectly null self-interference, but instead seeks to reduce self-interference sufficiently to prevent swamping the receiver's dynamic range. Residual self-interference is then cancelled digitally by the receiver. We evaluate the performance of SoftNull using measurements from a 72-element antenna array in both indoor and outdoor environments. We find that SoftNull can significantly outperform half-duplex for small cells operating in the many-antenna regime, where the number of antennas is many more than the number of users served simultaneously.

Smartphone technology is penetrating world markets and becoming ubiquitous in most college settings. This study takes a naturalistic approach to explore the use of these devices to support student learning. Students that had never used a smartphone were recruited to participate and reported on their expectations of the value of smartphones to achieve their educational goals. Instrumented iPhones that logged device usage were then distributed to these students to use freely over the course of 1 year. After the study, students again reported on the actual value of their smartphones to support their educational goals. We found that students' reports changed substantially before and after the study; specifically, the utility of the smartphone to help with education was perceived as favorable prior to use, and then, by the end of the study, they viewed their phones as detrimental to their educational goals. Although students used their mobile device for informal learning and access to school resources according to the logged data, they perceived their iPhones as a distraction and a competitor to requisite learning for classroom performance.

Abstract-This study examined smartphone user behaviors and their relation to self-reported smartphone addiction. Thirty-four users who did not own smartphones were given instrumented iPhones that logged all phone use over the course of the year-long study. At the conclusion of the study, users were asked to rate their level of addiction to the device. Sixty-two percent agreed or strongly agreed that they were addicted to their iPhones. These users showed differentiated smartphone use as compared to those users who did not indicate an addiction. Addicted users spent twice as much time on their phone and launched applications much more frequently (nearly twice as often) as compared to the non-addicted user. Mail, Messaging, Facebook and the Web drove this use. Surprisingly, Games did not show any difference between addicted and nonaddicted users. Addicted users showed significantly lower time-per-interaction than did non-addicted users for Mail, Facebook and Messaging applications. One addicted user reported that his addiction was problematic, and his use data was beyond three standard deviations from the upper hinge. The implications of the relationship between the logged and self-report data are discussed.

The current paper establishes empirical patterns associated with mobile internet use on smartphones and explores user differences in these behaviors. We apply a naturalistic and longitudinal logs-based approach to collect real usage data from 24 iPhone users in the wild. These data are used to describe smartphone usage and analyze revisitation patterns of web browsers, native applications, and physical locations where phones are used. Among our findings are that web page revisitation through browsers occurred very infrequently (approximately 25% of URLs are revisited by each user), bookmarks were used sparingly, physical traversing patterns mirrored virtual (internet) traversing patterns and users systematically differed in their web use. We characterize these differences and suggest ways to support users with enhanced design of smartphone technologies and content.