Showing papers by "Qualcomm published in 2015"

Downlink Cellular Network Analysis With Multi-Slope Path Loss Models

Abstract: Existing cellular network analyses, and even simulations, typically use the standard path loss model where received power decays like $\Vert x\Vert^{-\alpha}$ over a distance $\Vert x\Vert$ . This standard path loss model is quite idealized, and in most scenarios the path loss exponent $\alpha$ is itself a function of $\Vert x\Vert$ , typically an increasing one. Enforcing a single path loss exponent can lead to orders of magnitude differences in average received and interference powers versus the true values. In this paper, we study multi-slope path loss models, where different distance ranges are subject to different path loss exponents. We focus on the dual-slope path loss function, which is a piece-wise power law and continuous and accurately approximates many practical scenarios. We derive the distributions of SIR, SNR, and finally SINR before finding the potential throughput scaling, which provides insight on the observed cell-splitting rate gain. The exact mathematical results show that the SIR monotonically decreases with network density, while the converse is true for SNR, and thus the network coverage probability in terms of SINR is maximized at some finite density. With ultra-densification (network density goes to infinity), there exists a phase transition in the near-field path loss exponent $\alpha_{0}$ : if $\alpha_{0} >1$ unbounded potential throughput can be achieved asymptotically; if $\alpha_{0} , ultra-densification leads in the extreme case to zero throughput.

Joint Rate and SINR Coverage Analysis for Decoupled Uplink-Downlink Biased Cell Associations in HetNets

Abstract: Load balancing by proactively offloading users onto small and otherwise lightly-loaded cells is critical for tapping the potential of dense heterogeneous cellular networks (HCNs). Offloading has mostly been studied for the downlink, where it is generally assumed that a user offloaded to a small cell will communicate with it on the uplink as well. The impact of coupled downlink-uplink offloading is not well understood. Uplink power control and spatial interference correlation further complicate the mathematical analysis as compared to the downlink. We propose an accurate and tractable model to characterize the uplink $\textnormal{\texttt{SINR}}$ and rate distribution in a multi-tier HCN as a function of the association rules and power control parameters. Joint uplink-downlink rate coverage is also characterized. Using the developed analysis, it is shown that the optimal degree of channel inversion (for uplink power control) increases with load imbalance in the network. In sharp contrast to the downlink, minimum path loss association is shown to be optimal for uplink rate. Moreover, with minimum path loss association and full channel inversion, uplink $\textnormal{\texttt{SIR}}$ is shown to be invariant of infrastructure density. It is further shown that a decoupled association —employing differing association strategies for uplink and downlink—leads to significant improvement in joint uplink-downlink rate coverage over the standard coupled association in HCNs.

A Comparative Study of Modern Inference Techniques for Structured Discrete Energy Minimization Problems

Abstract: Szeliski et al. published an influential study in 2006 on energy minimization methods for Markov random fields. This study provided valuable insights in choosing the best optimization technique for certain classes of problems. While these insights remain generally useful today, the phenomenal success of random field models means that the kinds of inference problems that have to be solved changed significantly. Specifically, the models today often include higher order interactions, flexible connectivity structures, large label-spaces of different cardinalities, or learned energy tables. To reflect these changes, we provide a modernized and enlarged study. We present an empirical comparison of more than 27 state-of-the-art optimization techniques on a corpus of 2453 energy minimization instances from diverse applications in computer vision. To ensure reproducibility, we evaluate all methods in the OpenGM 2 framework and report extensive results regarding runtime and solution quality. Key insights from our study agree with the results of Szeliski et al. for the types of models they studied. However, on new and challenging types of models our findings disagree and suggest that polyhedral methods and integer programming solvers are competitive in terms of runtime and solution quality over a large range of model types.

Feasible Point Pursuit and Successive Approximation of Non-Convex QCQPs

Abstract: Quadratically constrained quadratic programs (QCQPs) have a wide range of applications in signal processing and wireless communications. Non-convex QCQPs are NP-hard in general. Existing approaches relax the non-convexity using semi-definite relaxation (SDR) or linearize the non-convex part and solve the resulting convex problem. However, these techniques are seldom successful in even obtaining a feasible solution when the QCQP matrices are indefinite. In this letter, a new feasible point pursuit successive convex approximation (FPP-SCA) algorithm is proposed for non-convex QCQPs. FPP-SCA linearizes the non-convex parts of the problem as conventional SCA does, but adds slack variables to sustain feasibility, and a penalty to ensure slacks are sparingly used. When FPP-SCA is successful in identifying a feasible point of the non-convex QCQP, convergence to a Karush-Kuhn-Tucker (KKT) point is thereafter ensured. Simulations show the effectiveness of our proposed algorithm in obtaining feasible and near-optimal solutions, significantly outperforming existing approaches.

Cache-aided interference channels

Abstract: Over the past decade, the bulk of wireless traffic has shifted from speech to content. This shift creates the opportunity to cache part of the content in memories closer to the end users, for example in base stations. Most of the prior literature focuses on the reduction of load in the backhaul and core networks due to caching, i.e., on the benefits caching offers for the wireline communication link between the origin server and the caches. In this paper, we are instead interested in the benefits caching can offer for the wireless communication link between the caches and the end users. To quantify the gains of caching for this wireless link, we consider an interference channel in which each transmitter is equipped with an isolated cache memory. Communication takes place in two phases, a content placement phase followed by a content delivery phase. The objective is to design both the placement and the delivery phases to maximize the rate in the delivery phase in response to any possible user demands. Focusing on the three-user case, we show that through careful joint design of these phases, we can reap three distinct benefits from caching: a load balancing gain, an interference cancellation gain, and an interference alignment gain. In our proposed scheme, load balancing is achieved through a specific file splitting and placement, creating a particular pattern of content overlap at the caches. This overlap allows to implement interference cancellation. Further, it allows us to construct several virtual transmitters, each responsible for a part of the requested content, which increases interference alignment possibilities.

Fixed Point Quantization of Deep Convolutional Networks

Abstract: In recent years increasingly complex architectures for deep convolution networks (DCNs) have been proposed to boost the performance on image recognition tasks. However, the gains in performance have come at a cost of substantial increase in computation and model storage resources. Fixed point implementation of DCNs has the potential to alleviate some of these complexities and facilitate potential deployment on embedded hardware. In this paper, we propose a quantizer design for fixed point implementation of DCNs. We formulate and solve an optimization problem to identify optimal fixed point bit-width allocation across DCN layers. Our experiments show that in comparison to equal bit-width settings, the fixed point DCNs with optimized bit width allocation offer >20% reduction in the model size without any loss in accuracy on CIFAR-10 benchmark. We also demonstrate that fine-tuning can further enhance the accuracy of fixed point DCNs beyond that of the original floating point model. In doing so, we report a new state-of-the-art fixed point performance of 6.78% error-rate on CIFAR-10 benchmark.

Cache-Aided Interference Channels

Abstract: Over the past decade, the bulk of wireless traffic has shifted from speech to content. This shift creates the opportunity to cache part of the content in memories closer to the end users, for example in base stations. Most of the prior literature focuses on the reduction of load in the backhaul and core networks due to caching, i.e., on the benefits caching offers for the wireline communication link between the origin server and the caches. In this paper, we are instead interested in the benefits caching can offer for the wireless communication link between the caches and the end users. To quantify the gains of caching for this wireless link, we consider an interference channel in which each transmitter is equipped with an isolated cache memory. Communication takes place in two phases, a content placement phase followed by a content delivery phase. The objective is to design both the placement and the delivery phases to maximize the rate in the delivery phase in response to any possible user demands. Focusing on the three-user case, we show that through careful joint design of these phases, we can reap three distinct benefits from caching: a load balancing gain, an interference cancellation gain, and an interference alignment gain. In our proposed scheme, load balancing is achieved through a specific file splitting and placement, producing a particular pattern of content overlap at the caches. This overlap allows to implement interference cancellation. Further, it allows us to create several virtual transmitters, each transmitting a part of the requested content, which increases interference-alignment possibilities.

Scene classification with semantic Fisher vectors

Abstract: With the help of a convolutional neural network (CNN) trained to recognize objects, a scene image is represented as a bag of semantics (BoS). This involves classifying image patches using the network and considering the class posterior probability vectors as locally extracted semantic descriptors. The image BoS is summarized using a Fisher vector (FV) embedding that exploits the properties of the space of these descriptors. The resulting representation is referred to as a semantic Fisher vector. Two implementations of a semantic FV are investigated. First involves modeling the BoS with a Dirichlet Mixture and computing the Fisher gradients for this model. Due to the difficulty of mixture modeling on a non-Euclidean probability simplex, this approach is shown to be unsuccessful. A second implementation is derived using the interpretation of semantic descriptors as parameters of a multinomial distribution. Like the parameters of any exponential family, these can be projected into their natural parameter space. For a CNN, this is shown equivalent to using inputs of its soft-max layer as patch descriptors. A semantic FV is then computed as a Gaussian Mixture FV in the space of these natural parameters. This representation is shown to outperform other alternatives such as FVs of features from the intermediate CNN layers or a classifier obtained by adapting (fine-tuning) the CNN. The proposed FV represents an embedding for object classification probabilities. As an image representation, therefore, it is complementary to the features obtained from a scene classification CNN. A combination of the two representations is shown to achieve state-of-the-art results on MIT Indoor scenes and SUN datasets.

Systems and methods for restricting drone airspace access

Abstract: Methods, systems, and devices are disclosed for providing conditional access for a drone for accessing a restricted area. Conditional access information associated with conditional access restrictions for the restricted area may be received by the drone. The drone may compare the received conditional access information to one or more access parameters for the drone. The drone may access the restricted area based on the comparison of the received conditional access information and the access parameter. A drone may take corrective action when the received conditional access information does not permit access to the restricted area based on the access parameter for the drone.

Generalized Spatial Modulation in Large-Scale Multiuser MIMO Systems

Abstract: Generalized spatial modulation (GSM) uses $n_{t} $ transmit antenna elements but fewer transmit radio frequency (RF) chains, $n_{rf} $ . Spatial modulation (SM) and spatial multiplexing are special cases of GSM with $n_{rf}=1$ and $n_{rf}=n_{t} $ , respectively. In GSM, in addition to conveying information bits through $n_{rf} $ conventional modulation symbols (for example, QAM), the indices of the $n_{rf} $ active transmit antennas also convey information bits. In this paper, we investigate GSM for large-scale multiuser MIMO communications on the uplink. Our contributions in this paper include: 1) an average bit error probability (ABEP) analysis for maximum-likelihood detection in multiuser GSM-MIMO on the uplink, where we derive an upper bound on the ABEP, and 2) low-complexity algorithms for GSM-MIMO signal detection and channel estimation at the base station receiver based on message passing. The analytical upper bounds on the ABEP are found to be tight at moderate to high signal-to-noise ratios (SNR) . The proposed receiver algorithms are found to scale very well in complexity while achieving near-optimal performance in large dimensions. Simulation results show that, for the same spectral efficiency, multiuser GSM-MIMO can outperform multiuser SM-MIMO as well as conventional multiuser MIMO, by about 2 to 9 dB at a bit error rate of $10^{-3} $ . Such SNR gains in GSM-MIMO compared to SM-MIMO and conventional MIMO can be attributed to the fact that, because of a larger number of spatial index bits, GSM-MIMO can use a lower-order QAM alphabet which is more power efficient.

Multiple Hypotheses Image Segmentation and Classification With Application to Dietary Assessment

Abstract: We propose a method for dietary assessment to automatically identify and locate food in a variety of images captured during controlled and natural eating events. Two concepts are combined to achieve this: a set of segmented objects can be partitioned into perceptually similar object classes based on global and local features; and perceptually similar object classes can be used to assess the accuracy of image segmentation. These ideas are implemented by generating multiple segmentations of an image to select stable segmentations based on the classifier’s confidence score assigned to each segmented image region. Automatic segmented regions are classified using a multichannel feature classification system. For each segmented region, multiple feature spaces are formed. Feature vectors in each of the feature spaces are individually classified. The final decision is obtained by combining class decisions from individual feature spaces using decision rules. We show improved accuracy of segmenting food images with classifier feedback.

Deriving and Validating User Experience Model for DASH Video Streaming

Abstract: Ever since video compression and streaming techniques have been introduced, measurement of perceived video quality has been a non-trivial task. Dynamic adaptive streaming (DASH) over hypertext transfer protocol, is a new worldwide standard for adaptive streaming of video. DASH has introduced an additional level of complexity for measuring perceived video quality, as it varies the video bit rate and quality. In this paper, we study the perceived video quality using DASH. We investigate three factors which impact user perceived video quality: 1) initial delay; 2) stall (frame freezing); and 3) bit rate (frame quality) fluctuation. For each factor, we explore multiple dimensions that can have different effects on perceived quality. For example, in the case of the factor stall, while most previous research have studied how stall duration correlates with user experience, we also consider how the stalls are distributed together with the amount of motion in the video content, since we believe they may also impact user perceived quality. We conduct extensive subjective tests in which a group of subjects provide subjective evaluation while watching DASH videos with one or more artifacts occurring. Based on the subjective tests, we first derive impairment functions which can quantitatively measure the impairment of each factor, and then combine these impairment functions together to formulate an overall user experience model for any DASH video. We validate with high accuracy the user experience model, and demonstrate its applicability to long videos.

A SiGe Terahertz Heterodyne Imaging Transmitter With 3.3 mW Radiated Power and Fully-Integrated Phase-Locked Loop

Abstract: A high-power 320 GHz transmitter using 130 nm SiGe BiCMOS technology ( $f_{T}/f_{\max} =$ 220/280 GHz) is reported. This transmitter consists of a 4 × 4 array of radiators based on coupled harmonic oscillators. By incorporating a signal filter structure called return-path gap coupler into a differential self-feeding oscillator, the proposed 320 GHz radiator simultaneously maximizes the fundamental oscillation power, harmonic generation, as well as on-chip radiation. To facilitate the TX-RX synchronization of a future terahertz (THz) heterodyne imaging chipset, a fully-integrated phase-locked loop (PLL) is also implemented in the transmitter. Such on-chip phase-locking capability is the first demonstration for all THz radiators in silicon. In the far-field measurement, the total radiated power and EIRP of the chip is 3.3 mW and 22.5 dBm, respectively. The transmitter consumes 610 mW DC power, which leads to a DC-to-THz radiation efficiency of 0.54%. To the authors' best knowledge, this work presents the highest radiated power and DC-to-THz radiation efficiency in silicon-based THz radiating sources.

Piggybacking unmanned aerial vehicle

Abstract: Various embodiments include methods for piggybacking an unmanned aerial vehicle (UAV) on a vehicle (e.g., motor vehicles and trailers coupled to motor vehicles) to reach a destination. Various embodiments may include determining whether to dock on a vehicle. One or more candidate vehicles may be identified for docking. Travel profile characteristics of the one or more candidate vehicles may be identified. A first vehicle may be selected from the one or more candidate vehicles based on one or more travel profile characteristics that assist the UAV in reaching the UAV destination. The UAV may dock with the first vehicle. While docked to the first vehicle the UAV may charge an onboard battery via an electrical connection in a docking structure or by harvesting energy in the wind caused by movement of the vehicle by configuring the UAV rotors to charge the battery.

Three phase and polarity encoded serial interface

Abstract: A high speed serial interface is provided. In one aspect, the high speed serial interface uses three phase modulation for jointly encoding data and clock information. Accordingly, the need for de-skewing circuitry at the receiving end of the interface is eliminated, resulting in reduced link start-up time and improved link efficiency and power consumption. In one embodiment, the high speed serial interface uses fewer signal conductors than conventional systems having separate conductors for data and clock information. In another embodiment, the serial interface allows for data to be transmitted at any speed without the receiving end having prior knowledge of the transmission data rate. In another aspect, the high speed serial interface uses polarity encoded three phase modulation for jointly encoding data and clock information. This further increases the link capacity of the serial interface by allowing for more than one bit to be transmitted in any single baud interval.

A correlated shadowing model for urban wireless networks

Abstract: This paper presents an analytically tractable stochastic geometry model for urban wireless networks, where the locations of the nodes and the shadowing are highly correlated and different path loss functions can be applied to line-of-sight (LOS) and non-line-of-sight (NLOS) links. Using a distance-based LOS path loss model and a blockage (shadowing)-based NLOS path loss model, we are able to derive the distribution of the interference observed at a typical location and the joint distribution at different locations. When applied to cellular networks, this model leads to tractable expressions for the coverage probability (SINR distribution). We show that this model captures important features of urban wireless networks, which cannot be analyzed using existing models. The numerical results also suggest that even in the presence of significant penetration loss, ignoring the NLOS interference can lead to erroneous estimations on coverage. They also suggest that allowing users to be associated with NLOS BSs may provide a non-trivial gain on coverage.

Continuous authentication with a mobile device

Abstract: A mobile device may perform continuous authentication with an authenticating entity. The mobile device may include a set of biometric and non-biometric sensors and a processor. The processor may be configured to receive sensor data from the set of sensors, form authentication information from the received sensor data, and continuously update the authentication information.

Systems and methods for context-aware application control

Abstract: A method performed by an electronic device is described. The method includes obtaining sensor information. The method also includes identifying a class of an object based on the sensor information. The method further includes determining one or more actions based on the sensor information, the class of the object and an action usage history. The method additionally includes performing at least one of the one or more actions based on at least one application.

On-demand system information

Abstract: A wireless network may provide system information by either a fixed periodic broadcast or broad-beam transmission or in response to a request by a user equipment (UE). The wireless network may broadcast (or broad-beam transmit) a signal that indicates to the UEs within a cell or zone coverage area that system information is to be transmitted on a fixed periodic schedule or in response to a request sent by one or more UEs.

Interactive touchscreen and sensor array

Abstract: An object detection system for capturing one or more sensor images of an object is provided that includes a touch system including a touch-sensitive screen and a display of a device. The object detection system also includes a sensor system including a sensor array and a processing component. The sensor array is coupled to the touch-sensitive screen, and the processing component is configured to capture one or more images of an object when the object is detected by the touch-sensitive screen. At least a portion of the sensor array overlaps with at least a portion of the touch-sensitive screen.

Beam Switching for Millimeter Wave Communication to Support High Speed Trains

Abstract: This paper considers a millimeter wave (mmWave) system that enables multi-Gbps wireless service for high speed trains. MmWave systems require proper beam alignment to achieve good performance making it difficult to apply to high speed trains due to the need for frequent realignment. In this paper, using the IEEE 802.11ad system parameters, we first show that the channel coherence time will not be enough for communication with wide beams, and thus conventional approaches based on beam sweeping become inefficient if not impossible. Then we consider a beam switching approach that leverages the position information from the train control system for efficient beam alignment. Using this network architecture, we investigate the optimal choice of beamwidth and show that a properly optimized system can achieve multi-Gbps throughput.

Overview of the EVS codec architecture

Abstract: The recently standardized 3GPP codec for Enhanced Voice Services (EVS) offers new features and improvements for low-delay real-time communication systems. Based on a novel, switched low-delay speech/audio codec, the EVS codec contains various tools for better compression efficiency and higher quality for clean/noisy speech, mixed content and music, including support for wideband, super-wideband and full-band content. The EVS codec operates in a broad range of bitrates, is highly robust against packet loss and provides an AMR-WB interoperable mode for compatibility with existing systems. This paper gives an overview of the underlying architecture as well as the novel technologies in the EVS codec and presents listening test results showing the performance of the new codec in terms of compression and speech/audio quality.

Method and apparatus for activating application by speech input

Abstract: A method, which is performed in an electronic device, for activating a target application is disclosed. The method may include receiving an input sound stream including an activation keyword for activating the target application and a speech command indicative of a function of the target application. The method may also detect the activation keyword from the input sound stream. If the activation keyword is detected, a portion of the input sound stream including at least a portion of the speech command may be buffered in a buffer memory. In addition, in response to detecting the activation keyword, the target application may be activated to perform the function of the target application.

Access control lists for private networks of system agnostic connected devices

Abstract: The disclosure relates to using a control service to control external access to APIs of IoT devices on a private network. An external application can request access to an API, and in response, the control service can monitor broadcasts from the IoT devices indicating what APIs they have available. If a match exists, the control service can request user authorization to allow the requested access. The user can grant or deny the requested access, and place limitations on the authorized access. The control service uses this information to open a connection between the requesting application and the IoT device having the requested API, and via this connection, the requesting application can access and control the device running the requested API.

Piezoelectric ultrasonic transducer and process

Abstract: A piezoelectric micromechanical ultrasonic transducer (PMUT) includes a multilayer stack disposed on a substrate. The multilayer stack may include an anchor structure disposed over the substrate, a piezoelectric layer stack disposed over the anchor structure, and a mechanical layer disposed proximate to the piezoelectric layer stack. The piezoelectric layer stack may be disposed over a cavity. The mechanical layer may seal the cavity and, together with the piezoelectric layer stack, is supported by the anchor structure and forms a membrane over the cavity, the membrane being configured to undergo one or both of flexural motion and vibration when the PMUT receives or transmits ultrasonic signals.

Generating a location profile of an internet of things device based on augmented location information associated with one or more nearby internet of things devices

Abstract: In an embodiment, an Internet of Things (IoT) device obtains augmented location information (ALI) that identifies (i) one or more device classifications (e.g., mobile, geo-static, etc.) for one or more IoT devices near the IoT device in the IoT environment and/or (ii) immediate surroundings (e.g., a picture, an audio recording, etc.) of the one or more IoT devices, and generates a location profile of the IoT device based on the obtained ALI. In another embodiment, a power-limited IoT device selects a proxy IoT device. The selected proxy IoT device performs an ALI reporting function on behalf of the power-limited IoT device, while the power-limited IoT device refrains from performing the ALI reporting function.

Adaptive selection of artificial neural networks

Abstract: A method of adaptively selecting a configuration for a machine learning process includes determining current system resources and performance specifications of a current system. A new configuration for the machine learning process is determined based at least in part on the current system resources and the performance specifications. The method also includes dynamically selecting between a current configuration and the new configuration based at least in part on the current system resources and the performance specifications.

Block adaptive color-space conversion coding

Abstract: A video coder decodes a coding unit (CU) of video data. In decoding the video data, the video coder determines that the CU was encoded using the color space conversion. The video coder determines the initial quantization parameter (QP), determines the final QP that is equal to a sum of the initial QP and a QP offset, and inverse quantizes, based on the final QP, a coefficient block, then reconstructs the CU based on the inverse quantized coefficient blocks.

Auto-focus in low-profile folded optics multi-camera system

Abstract: An image capturing system and a method of autofocusing are disclosed such that, for example, when a folded optics configuration is used, a field corrector lens can be placed on the image sensor of the system and a plurality of lenses can be placed perpendicular to the image sensor. The plurality of lenses can be movable relative to the image sensor such that acceptable MTF curve performances can be obtained when the image capturing system is focused at reference distances.

SINR and Throughput Scaling in Ultradense Urban Cellular Networks

Abstract: We consider a dense urban cellular network where the base stations (BSs) are stacked vertically as well as extending infinitely in the horizontal plane, resulting in a greater than two dimensional (2D) deployment. We use a dual-slope path loss model that is well supported empirically, wherein a “close-in” pathloss exponent $\alpha_0$ is used for distances less than a corner distance $R_c$ , and then changes to $\alpha_1 > \alpha_0$ outside $R_c$ . We extend recent 2D coverage probability and potential throughput results to $d$ dimensions, and prove that if the close-in path loss exponent $\alpha_0 , then the SINR eventually decays to zero. For example, $\alpha_0 \le 3$ results in an eventual SINR of 0 for all users in a 3D network, which is a troubling fact. We also show that the potential (i.e. best case) aggregate throughput decays to zero for $\alpha_0 . Both of these scaling results also hold for the more realistic case that we term 3D+, where there are no BSs below the user, as in a dense urban network with the user on or near the ground.