Fundamentals of Inter-cell Overhead Signaling in Heterogeneous Cellular Networks

Heterogeneous base stations (e.g. picocells, microcells, femtocells and distributed antennas) will become increasingly essential for cellular network capacity and coverage. Up until now, little basic research has been done on the fundamentals of managing so much infrastructure -- much of it unplanned -- together with the carefully planned macro-cellular network. Inter-cell coordination is in principle an effective way of ensuring different infrastructure components behave in a way that increases, rather than decreases, the key quality of service (QoS) metrics. The success of such coordination depends heavily on how the overhead is shared, and the rate and delay of the overhead sharing. We develop a novel framework to quantify overhead signaling for inter-cell coordination, which is usually ignored in traditional 1-tier networks, and assumes even more importance in multi-tier heterogeneous cellular networks (HCNs). We derive the overhead quality contour for general K-tier HCNs -- the achievable set of overhead packet rate, size, delay and outage probability -- in closed-form expressions or computable integrals under general assumptions on overhead arrivals and different overhead signaling methods (backhaul and/or wireless). The overhead quality contour is further simplified for two widely used models of overhead arrivals: Poisson and deterministic arrival process. This framework can be used in the design and evaluation of any inter-cell coordination scheme. It also provides design insights on backhaul and wireless overhead channels to handle specific overhead signaling requirements.Comment: 21 pages, 9 figure

Open, Closed, and Shared Access Femtocells in the Downlink

A fundamental choice in femtocell deployments is the set of users which are allowed to access each femtocell. Closed access restricts the set to specifically registered users, while open access allows any mobile subscriber to use any femtocell. Which one is preferable depends strongly on the distance between the macrocell base station (MBS) and femtocell. The main results of the paper are lemmas which provide expressions for the SINR distribution for various zones within a cell as a function of this MBS-femto distance. The average sum throughput (or any other SINR-based metric) of home users and cellular users under open and closed access can be readily determined from these expressions. We show that unlike in the uplink, the interests of home and cellular users are in conflict, with home users preferring closed access and cellular users preferring open access. The conflict is most pronounced for femtocells near the cell edge, when there are many cellular users and fewer femtocells. To mitigate this conflict, we propose a middle way which we term shared access in which femtocells allocate an adjustable number of time-slots between home and cellular users such that a specified minimum rate for each can be achieved. The optimal such sharing fraction is derived. Analysis shows that shared access achieves at least the overall throughput of open access while also satisfying rate requirements, while closed access fails for cellular users and open access fails for the home user.Comment: 26 pages, 8 figures, Submitted to IEEE Transactions on Wireless Communication

Self-optimized Coverage Coordination in Femtocell Networks

This paper proposes a self-optimized coverage coordination scheme for two-tier femtocell networks, in which a femtocell base station adjusts the transmit power based on the statistics of the signal and the interference power that is measured at a femtocell downlink. Furthermore, an analytic expression is derived for the coverage leakage probability that a femtocell coverage area leaks into an outdoor macrocell. The coverage analysis is verified by simulation, which shows that the proposed scheme provides sufficient indoor femtocell coverage and that the femtocell coverage does not leak into an outdoor macrocell.Comment: 16 pages, 5 figure

Workload-aware Automatic Parallelization for Multi-GPU DNN Training

Deep neural networks (DNNs) have emerged as successful solutions for variety of artificial intelligence applications, but their very large and deep models impose high computational requirements during training. Multi-GPU parallelization is a popular option to accelerate demanding computations in DNN training, but most state-of-the-art multi-GPU deep learning frameworks not only require users to have an in-depth understanding of the implementation of the frameworks themselves, but also apply parallelization in a straight-forward way without optimizing GPU utilization. In this work, we propose a workload-aware auto-parallelization framework (WAP) for DNN training, where the work is automatically distributed to multiple GPUs based on the workload characteristics. We evaluate WAP using TensorFlow with popular DNN benchmarks (AlexNet and VGG-16), and show competitive training throughput compared with the state-of-the-art frameworks, and also demonstrate that WAP automatically optimizes GPU assignment based on the workload's compute requirements, thereby improving energy efficiency.Comment: This paper is accepted in ICASSP201

Observation of Conduction Band Satellite of Ni Metal by 3p-3d Resonant Inverse Photoemission Study

Resonant inverse photoemission spectra of Ni metal have been obtained across the Ni 3$p$ absorption edge. The intensity of Ni 3$d$ band just above Fermi edge shows asymmetric Fano-like resonance. Satellite structures are found at about 2.5 and 4.2 eV above Fermi edge, which show resonant enhancement at the absorption edge. The satellite structures are due to a many-body configuration interaction and confirms the existence of 3$d^8$ configuration in the ground state of Ni metal.Comment: 4 pages, 3 figures, submitted to Physical Review Letter