SalsaNet: Fast Road and Vehicle Segmentation in LiDAR Point Clouds for Autonomous Driving

In this paper, we introduce a deep encoder-decoder network, named SalsaNet, for efficient semantic segmentation of 3D LiDAR point clouds. SalsaNet segments the road, i.e. drivable free-space, and vehicles in the scene by employing the Bird-Eye-View (BEV) image projection of the point cloud. To overcome the lack of annotated point cloud data, in particular for the road segments, we introduce an auto-labeling process which transfers automatically generated labels from the camera to LiDAR. We also explore the role of imagelike projection of LiDAR data in semantic segmentation by comparing BEV with spherical-front-view projection and show that SalsaNet is projection-agnostic. We perform quantitative and qualitative evaluations on the KITTI dataset, which demonstrate that the proposed SalsaNet outperforms other state-of-the-art semantic segmentation networks in terms of accuracy and computation time. Our code and data are publicly available at https://gitlab.com/aksoyeren/salsanet.git

Energy saving market for mobile operators

Ensuring seamless coverage accounts for the lion's share of the energy consumed in a mobile network. Overlapping coverage of three to five mobile network operators (MNOs) results in enormous amount of energy waste which is avoidable. The traffic demands of the mobile networks vary significantly throughout the day. As the offered load for all networks are not same at a given time and the differences in energy consumption at different loads are significant, multi-MNO capacity/coverage sharing can dramatically reduce energy consumption of mobile networks and provide the MNOs a cost effective means to cope with the exponential growth of traffic. In this paper, we propose an energy saving market for a multi-MNO network scenario. As the competing MNOs are not comfortable with information sharing, we propose a double auction clearinghouse market mechanism where MNOs sell and buy capacity in order to minimize energy consumption. In our setting, each MNO proposes its bids and asks simultaneously for buying and selling multi-unit capacities respectively to an independent auctioneer, i.e., clearinghouse and ends up either as a buyer or as a seller in each round. We show that the mechanism allows the MNOs to save significant percentage of energy cost throughout a wide range of network load. Different than other energy saving features such as cell sleep or antenna muting which can not be enabled at heavy traffic load, dynamic capacity sharing allows MNOs to handle traffic bursts with energy saving opportunity.Comment: 6 pages, 2 figures, to be published in ICC 2015 workshop on Next Generation Green IC

Gülen sect: Reached for the state, got capital instead

A religious sect now defies the strongest political party in Turkey. There must be a reason for this alarming self-confidence. Is it rooted in history; that is, does the sect have a long heritage? Not really -it is a movement that started to take shape in the 1970s. What about economic clout? Well, sort of; but in a country where each transaction must be approved by the state, economic force can translate into business investment only as far as the state allows it

Grant-free Radio Access IoT Networks: Scalability Analysis in Coexistence Scenarios

IoT networks with grant-free radio access, like SigFox and LoRa, offer low-cost durable communications over unlicensed band. These networks are becoming more and more popular due to the ever-increasing need for ultra durable, in terms of battery lifetime, IoT networks. Most studies evaluate the system performance assuming single radio access technology deployment. In this paper, we study the impact of coexisting competing radio access technologies on the system performance. Considering \mathpzc K technologies, defined by time and frequency activity factors, bandwidth, and power, which share a set of radio resources, we derive closed-form expressions for the successful transmission probability, expected battery lifetime, and experienced delay as a function of distance to the serving access point. Our analytical model, which is validated by simulation results, provides a tool to evaluate the coexistence scenarios and analyze how introduction of a new coexisting technology may degrade the system performance in terms of success probability and battery lifetime. We further investigate solutions in which this destructive effect could be compensated, e.g., by densifying the network to a certain extent and utilizing joint reception

Journal Staff

Elastic Optical Networks (EONs), evolved as a scalable infrastructure to provide optical connectivity for large variety of bandwidth requests ranging from 1Gbps to 1Tbps. Thanks to the enabling technologies such as bandwidth variable transponders and flexible switches, bandwidth adaptive spectrum allocation became possible. EONs can carry large optical channels with higher spectrum efficiency with the recent changes in the standard fixed division of optical spectrum. In this study we propose a distance adaptive, dynamic shared path protection scheme for EONs. In conventional WDM networks, sharability used to be one of the prime objectives to maximize the backup resource efficiency. In EONs, spectrum resources can be shared partially between connections and different parts of the allocated spectrum may be shared by different connections at the same time. Not only the routing but also spectrum allocation of backup resources has a big impact on the sharability in EONs. Taking this into account, we developed a novel RSA (Routing and Spectrum Allocation) algorithm applying different strategies for primary and backup resources called Primary First-Fit Modified Backup Last-Fit (PF-MBL) aiming to reduce the fragmentation and to increase the sharability. As a result overall bandwidth blocking probability is significantly reduced in the network. Results show that PF-MBL can improve the performance in terms of bandwidth blocking probability by 24% up to 59% compared to the current outperforming algorithm when the bandwidth acceptance ratio of the system varies from 90% to 99.9% in different loads.QC 20131024</p

Single Tree Vegetation Depth Estimation Tool for Satellite Services Link Design

Attenuation caused by tree shadowing is an important factor for describing the propagation channel of satellite services. Thus, vegetation effects should be determined by experimental studies or empirical formulations. In this study, tree types in the Black Sea Region of Turkey are classified based on their geometrical shapes into four groups such as conic, ellipsoid, spherical and hemispherical. The variations of the vegetation depth according to different tree shapes are calculated with ray tracing method. It is showed that different geometrical shapes have different vegetation depths even if they have same foliage volume for different elevation angles. The proposed method is validated with the related literature in terms of average single tree attenuation. On the other hand, due to decrease system requirements (speed, memory usage etc.) of ray tracing method, an artificial neural network is proposed as an alternative. A graphical user interface is created for the above processes in MATLAB environment named vegetation depth estimation tool (VdET)