We present the third generation of Argos platforms, ArgosV3, intended for real-world applications and research. Developed from scratch specifically for many-antenna MU-MIMO, ArgosV3 is highly efficient in space, power, computation, and cost. While this new platform is highly configurable, featuring FPGA SoCs and frequency agile transceivers capable of operation from 50 MHz to 3.8 GHz, it is also highly compact and power efficient, enabling a complete 160 radio base station in less than 2 cubic feet. ArgosV3 is currently being deployed in a campus-wide multi-cell many-antenna network. For our demonstration we will show a single ArgosV3 base station serving multiple clients using a realtime LTE stack.

In this paper, we present and study a digital-controlled 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.

Many-antenna MU-MIMO faces a critical, previously unaddressed challenge: it lacks a practical control channel. At the heart of this challenge is that the potential range of MU-MIMO beamforming systems scales with up to the square of the number of base-station antennas once they have channel state information (CSI), whereas the range of traditional control channel operations remains constant since they take place before or during CSI acquisition. This range gap between no-CSI and CSI modes presents a critical challenge to the efficiency and feasibility of many-antenna base stations, as their operational range is limited to the no-CSI mode. We present a novel control channel design for many-antenna MU-MIMO, Faros, that allows the number of base-station antennas to scale up to 100s in practice. Faros leverages a combination of open-loop beamforming and coding gains to bridge the range gap between the CSI and no-CSI modes. Not only does Faros provide an elegant and efficient control channel for many-antenna MU-MIMO, but on a more fundamental level it exposes flexible, fine-grained, control over space, time, and code resources, which enables previously impossible optimizations. We implement our design on the Argos many-antenna base station and evaluate its performance in bridging the range gap, synchronization, and paging. With 108 antennas, Faros can provide over 40 dB of gain, which enables it to function reliably at over 250 meters outdoors with less than 100 μW of transmit power per antenna, 10 mW total, at 2.4 GHz.

Context information brings new opportunities for efficient and effective applications and services on mobile devices. A wide range of research has exploited context dependency, i.e. the relations between context(s) and the outcome, to achieve significant, quantified, performance gains for a variety of applications and services. These works typically have to deal with the challenges of multiple context sources leading to a sparse training dataset, and the challenges of energy hungry context sensors. Often, they address these challenges in an application specific and ad-hoc manner. We liberate mobile application designers and researchers from these burdens by providing a methodical approach to these challenges. In particular, we 1) define and measure the context-dependency of three principal types of mobile usage (visited websites, phone calls, and app usage) in an application agnostic yet practical manner, providing insight into the performance of potential application. 2) Address the challenge of data sparseness when dealing with multiple context sources in a systematic manner. 3) Present SmartContext to address the energy challenge by automatically selecting among context sources while ensuring a minimum accuracy for each estimation. Our analysis and findings are based on one year of usage and context traces collected in real-life settings from 24 iPhone users. We present findings regarding the context dependency of three types of mobile usage from 24 users, yet our methodology and the lessons we learn can be readily extended to other types of usage as well as system resources. Our findings guide the development of context aware systems, and highlight the challenges and expectations regarding the context dependency of mobile usage.

Is it possible to migrate TCP/IP flows between different networks on modern mobile devices without infrastructure support or protocol changes? To answer this question, we make three research contributions: 1) We report a comprehensive characterization of IP traffic on 27 iPhone 3GS users for three months. 2) Driven by these findings, we devise two simple, effective, and easily deployable system mechanisms to support seamless flow migration without network support, and extensively evaluate their effectiveness using our field collected traces of real-life usage. Wait-n-Migrate leverages the fact that most flows are short lived. It establishes new flows on newly available networks but allows preexisting flows on the old network to terminate naturally. Resumption Agent takes advantage of the resumption functionality of modern protocols to securely resume flows without application intervention. Combined, they provide an unprecedented opportunity to immediately deploy policies that leverage multiple networks to improve the performance, efficiency, and connectivity of mobile devices. 3) We report an iPhone-based implementation of these system mechanisms and demonstrate their overhead to be negligible. Furthermore, we employ a sample switching policy, AutoSwitch, to demonstrate their performance. Through traces and field measurements, we show that AutoSwitch reduces user disruptions by an order of magnitude.

Many-antenna base stations are a rapidly growing field in wireless research. A plethora of new theoretical techniques have been recently proposed for many-antenna base stations and networks. However, without experimental validation, it is difficult or impossible to predict the practicality and performance of these techniques in real hardware, under complex, rapidly varying, real-world conditions. Indeed, there is a significant demand for a flexible many-antenna research platform which supports rapid prototyping and validation of new massive-MIMO techniques. Leveraging our experience building Argos, a 64-antenna base station prototype, we have designed and built ArgosV2, a compact, powerful, and scalable many-antenna research platform based on WARP. In addition to the physical hardware and mechanical design, we are developing a software framework, ArgosLab, which will provide synchronization and channel estimation, greatly reducing the development effort for a wide range of massive-MIMO techniques. ArgosV2 is intended to provide ultimate scalability and programmability for experimental massive-MIMO research. The modular architecture and real-time capability of ArgosV2 can support up to 100s of base station antennas and 10s of users with streaming applications. For our demonstration, we will unveil a 96-antenna base station which supports real-time streaming applications to 32 users simultaneously.

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.

The WiFi radio in smartphones consumes a significant portion of energy when active. To reduce the energy consumption, the Power Saving Mode was standardized in IEEE 802.11 and two major implementations, Static PSM and Dynamic PSM, have been widely used in mobile devices. Unfortunately, both PSMs have inherent drawbacks: Static PSM is energy efficient but imposes considerable extra delays on data transfers; Dynamic PSM incurs little extra delay but misses energy saving opportunities. In this paper, we first analyze a one-week trace from 10 users and show that more than 80% of all traffic are Web 2.0 flows, which are of very small sizes and short durations. Targeting these short but dominant flows, we propose a system called Percy, to achieve the best of both worlds (Static and Dynamic PSM), i.e., to maximize the energy saving while minimizing the delay of flow completion time. Percy works by deploying a web proxy at the AP and suitably configuring the PSM parameters, and is designed to work with unchanged clients running Dynamic PSM, and unchanged APs and Internet servers. We evaluate our system via trace-driven testbed experiments. Our results show that Percy saves 40-70% energy compared to Dynamic PSM configurations of Nokia, iPhone and Android, while imposing low extra delay that can hardly be perceived by users.

Previous studies have found that smartphone users differ by orders of magnitude. We explore this variability to understand how users install and use native applications in ecologically-valid environments. A quasi-experimental approach is applied to compare how users in different socio-economic status (SES) groups adopt new smartphone technology along with how applications are installed and used. We present a longitudinal study of 34 iPhone 3GS users. 24 of these participants were chosen from two carefully selected SES groups who were otherwise similar and balanced. Usage data collected through an in-device programmable logger, as well as several structured interviews, identify similarities, differences, and trends, and highlight systematic differences in smartphone usage. A group of 10 lower SES participants were later recruited and confirm the influence of SES diversity on device usage. Among our findings are that a large number of applications were uninstalled, lower SES groups spent more money on applications and installed more applications overall, and the lowest SES group perceived the usability of their iPhones poorly in comparison to the other groups. We further discuss the primary reasons behind this low score, and suggest design implications to better support users across SES brackets.

Multi-user multiple-input multiple-output theory predicts manyfold capacity gains by leveraging many antennas on wireless base stations to serve multiple clients simultaneously through multi-user beamforming (MUBF). However, realizing a base station with a large number antennas is non-trivial, and has yet to be achieved in the real-world. We present the design, realization, and evaluation of Argos, the first reported base station architecture that is capable of serving many terminals simultaneously through MUBF with a large number of antennas (M >> 10). Designed for extreme flexibility and scalability, Argos exploits hierarchical and modular design principles, properly partitions baseband processing, and holistically considers real-time requirements of MUBF. Argos employs a novel, completely distributed, beamforming technique, as well as an internal calibration procedure to enable implicit beamforming with channel estimation cost independent of the number of base station antennas. We report an Argos prototype with 64 antennas and capable of serving 15 clients simultaneously. We experimentally demonstrate that by scaling from 1 to 64 antennas the prototype can achieve up to 6.7 fold capacity gains while using a mere 1/64th of the transmission power.

The present report is an empirical analysis of smartphone personalisation. We collected data from two groups of users to measure how they adapt the content, interface and physical appearance of their devices. This user-driven personalisation is measured with a simple heuristic approach to quantify the behaviour. Using these scores, we explore how users differ from each other in how they personalise their smartphones with a focus on gender differences, usability and device usage in the wild. Among our findings are that not all users personalise their smartphones, females and males personalise their iPhones differently, and those who personalised their phones more tended to rate it as more usable. The users who personalised more also used their device for greater periods of time on a broader range of applications. For instance, individuals who adapted their iPhones to a greater degree also accessed the Web more often and spent more time browsing once it was accessed. We conclude with a discussion of possible factors underlying the large user diversity of smartphone personalisation found in this research.

Consumer electronics and mobile devices intended for pervasive applications are often subject to shaking that makes their screen difficult to read. To address this usability challenge, we present NoShake, a system for screen content stabilization. NoShake utilizes a single accelerometer, now present in numerous consumer electronics and mobile devices. The core of NoShake is a physics inspired model that dynamically compensates for the device shaking by shifting the screen content opposite the direction of the shake. The model is efficient, parametric, and can be fine tuned based on shaking pattern detection. We implement a prototype of NoShake on an Apple iPhone and conduct user studies in a number of scenarios, which highlight the strengths as well as limitations of NoShake in coping with shaking devices.