In this paper, we propose a smartphone-based hearing assistive system (termed SmartHear) to facilitate speech recognition for various target users who could benefit from enhanced listening clarity in the classroom. The SmartHear system consists of transmitter and receiver devices (e.g., smartphone and Bluetooth headset) for voice transmission, and an Android mobile application that controls and connects the different devices via Bluetooth or WiFi technology. The wireless transmission of voice signals between devices overcomes the reverberation and ambient noise effects in the classroom. The main functionalities of SmartHear include: 1) configurable transmitter/receiver assignment, to allow flexible designation of transmitter/receiver roles; 2) advanced noise-reduction techniques; 3) audio recording; and 4) voice-to-text conversion, to give students visual text aid. All the functions are implemented as a mobile application with an easy-to-navigate user interface. Experiments show the effectiveness of the noise-reduction schemes at low signal-to-noise ratios (SNR) in terms of standard speech perception and quality indices, and show the effectiveness of SmartHear in maintaining voice-to-text conversion accuracy regardless of the distance between the speaker and listener. Future applications of SmartHear are also discussed.
OLED power management on mobile devices is very challenging due to the dynamic nature of human-screen interaction. This paper presents the design, algorithms, and implementation of a lightweight mobile app called ShiftMask, which allows the user to dynamically shift OLED power to the portion of interest, while dimming the remainder of the screen based on visual acuity. To adapt to the user’s focus of attention, we propose efficient algorithms that consider visual fixation in static scenes, as well as changes in focus and screen scrolling. The results of experiments conducted on a commercial smartphone with popular interactive apps demonstrate that ShiftMask can achieve substantial energy savings, while preserving acceptable readability.
This paper considers a device-to-device (D2D) communications underlaid multiple-input multiple-output (MIMO) cellular network and studies D2D mode selection from a previously unexamined perspective. Since D2D mode selection affects the network interference profile and vice versa, a joint D2D mode selection and interference management is desired but challenging. In this work, we propose a holistic approach to this problem with interference-free considerations. We adopt the degrees-of-freedom (DoF) as the mode-selection criterion and exploit the linear interference alignment (IA) technique for interference management. We analyze the achievable sum DoF of the potential D2D users according to their mode selections, and derive the probabilistic sum-rate relations between the proposed DoF-based mode selection scheme and the common received-signal-strength-index (RSSI)-based mode selection scheme in Poisson point process (PPP) networks. Simulation illustrates the theoretical insights and shows the advantages of the proposed DoF-based mode selection scheme over conventional mode selection schemes from various perspectives. The proposed scheme presents a promising proposal for D2D mode selection in 5G communications.
Improving PCMendurance is a fundamental issue when it is considered as an alternative to replace DRAM as main memory. Memory-based wear leveling (WL) is an effective way to improve PCM endurance, but its major challenge is how to efficiently determine the appropriate memory pages for allocation or swapping. In this article, we present a constant-cost WL design that is compatible with existing memory management. Two implementations, namely bucket-based and array-based WL, with constant-time (or nearly zero) search cost are proposed to be integrated into the OS layer and the hardware layer, respectively, as well as to trade between time and space complexity. The results of experiments conducted based on an implementation in Android, as well as simulations with popular benchmarks, to evaluate the effectiveness of the proposed design are very encouraging.
In simultaneous wireless information and power transfer (SWIPT), practical receiver architectures consisting of an information receiver and an energy harvester have been proposed in place of an ideal receiver capable of performing two tasks simultaneously using the same circuits. In this paper, we present a novel receiver architecture design incorporating an interplay between the information receiver and the energy harvester to enhance the performance of the practical SWIPT receiver. In particular, the energy level of the received signal monitored at the energy harvester is fed back to the information receiver to assist information decoding at the information receiver. The symbol-error-rate (SER) and diversity analyses show that the proposed receiver architecture could yield a higher diversity order for unconventional constellations where any two distinct symbols have distinct energy levels, and the same diversity order for conventional modulations. Simulation of PAM and QAM modulations verifies the analysis, shows the improved SER performance of the proposed receiver architecture, and illustrates the energy-dimension-augmented decision regions. Some insights into designing enhanced practical SWIPT receivers are provided as a result.
Application paradigms will increasingly exceed a mobile device's physical boundaries. This paper presents a system solution for a mobile device to mount remote sensors on other devices. Our design is generic to mobile senor stacks, thus supporting unmodified apps and commodity sensors. Furthermore, it uses an asynchronous access model to facilitate semantics passing and data reporting in between. Such semantic information allows the development of an energy-efficient reporting policy for remote sensing applications. The results of experiments conducted on commercial Android smartphones with popular apps demonstrate that our design is very efficient in terms of energy consumption and completion time.
Resident applications, which autonomously awaken mobile devices, can gradually and imperceptibly drain device batteries. This paper introduces the concept of alarm similarity into wakeup management for mobile systems in connected standby. First, we define hardware similarity to reflect the degree of energy savings and time similarity to reflect the impact on user experience. We then propose a policy that aligns alarms based on their similarity to save standby energy while maintaining the quality of the user experience. Finally, we integrate our design into Android and conduct extensive experiments on a commercial smartphone running popular mobile apps. The results demonstrate that our design can further extend the standby time achieved with Android's native policy by up to one-third.
This paper considers a two-cell uplink cochannel multiple-input multiple-output (MIMO) network with users sequentially arriving to the network. We study the problem of sequential base station (BS) selection for the users, with the selection criterion based on the degrees of freedom (DoF) available for the new arriving user. We find that different sequential BS selections affect individual and network performance in terms of the individual and network sum DoF as well as the number of admissible users in the network. We propose a method to build the tree structure for sequential BS selection, which carries trellis information for individual and system-wide selections. The properties of the tree are analytically studied. It turns out that by adopting an interference coordination strategy based on the concept of interference alignment, a better individual and network performance can be achieved. Simulation compares the proposed DoF-based BS selection and traditional BS selection schemes and highlights the advantages of the proposed scheme.
Mobile applications will become progressively more complicated and diverse. Heterogeneous computing architectures like big.LITTLE are a hardware solution that allows mobile devices to combine computing performance and energy efficiency. However, software solutions that conform to the paradigm of conventional fair scheduling and governing are not applicable to mobile systems, thereby degrading user experience or reducing energy efficiency. In this article, we exploit the concept of application sensitivity, which reflects the user’s attention on each application, and devise a user-centric scheduler and governor that allocate computing resources to applications according to their sensitivity. Furthermore, we integrate our design into the Android operating system. The results of experiments conducted on a commercial big.LITTLE smartphone with real-world mobile apps demonstrate that the proposed design can achieve significant gains in energy efficiency while improving the quality of user experience.
An increasing number of mobile devices are being equipped with 802.11n interfaces to support bandwidth-intensive applications; however, the improved bandwidth increases power consumption. To address the issue, researchers are focusing on antenna management. In this paper, we present a dynamic antenna management (DAM) scheme to improve the uplink energy efficiency on mobile devices whose packet workloads may vary significantly and frequently. First, we model antenna management as an optimization problem, with the objective of minimizing the energy required to transmit a sequence of variable-length packets with random arrival times. Then, we propose an optimal offline algorithm to solve the problem, as well as a competitive online algorithm that has a provable performance guarantee and allows compatible implementations on 802.11n mobile devices. To evaluate our scheme, we conducted extensive simulations based on real mobile user traces and application transmission patterns. Nearly all commercial 802.11n mobile devices support the power save mode (PSM). Our results demonstrate that DAM can improve the energy efficiency of PSM significantly at a cost of slight throughput degradation.