Karthik Sundaresan

A practical traffic management system for integrated LTE-WiFi networks

Mobile operators are leveraging WiFi to relieve the pressure posed on their networks by the surging bandwidth demand of applications. However, operators often lack intelligent mechanisms to control the way users access their WiFi networks. This lack of sophisticated control creates poor network utilization, which in turn degrades the quality of experience (QoE). To meet user traffic demands, it is evident that operators need solutions that optimally balance user traffic across cellular and WiFi networks. Motivated by the lack of practical solutions in this space, we design and implement ATOM - an end-to-end system for adaptive traffic offloading for WiFi-LTE deployments. ATOM has two novel components: (i) A network interface selection algorithm that maps user traffic across WiFi and LTE to optimize user QoE and (ii) an interface switching service that seamlessly re-directs ongoing user sessions in a cost-effective and standards-compatible manner. Our evaluations on a real LTE-WiFi testbed using YouTube traffic reveals that ATOM reduces video stalls by 3-4 times compared to naive solutions.

Scaling the LTE control-plane for future mobile access

In addition to growth of data traffic, mobile networks are bracing for a significant rise in the control-plane signaling. While a complete re-design of the network to overcome inefficiencies may help alleviate the effects of signaling, our goal is to improve the design of the current platform to better manage the signaling. To meet our goal, we combine two key trends. Firstly, mobile operators are keen to transform their networks with the adoption of Network Function Virtualization (NFV) to ensure economies of scales. Secondly, growing popularity of cloud computing has led to advances in distributed systems. In bringing these trends together, we solve several challenges specific to the context of telecom networks. We present SCALE - A framework for effectively virtualizing the MME (Mobility Management Entity), a key control-plane element in LTE. SCALE is fully compatible with the 3GPP protocols, ensuring that it can be readily deployed in todays networks. SCALE enables (i) computational scaling with load and number of devices, and (ii) computational multiplexing across data centers, thereby reducing both, the latencies for control-plane processing, and the VM provisioning costs. Using an LTE prototype implementation and large-scale simulations, we show the efficacy of SCALE.

ADAM: an adaptive beamforming system for multicasting in wireless LANs

We present the design and implementation of ADAM, the first adaptive beamforming-based multicast system and experimental framework for indoor wireless environments. ADAM addresses the joint problem of adaptive beamformer design at the PHY layer and client scheduling at the MAC layer by proposing efficient algorithms that are amenable to practical implementation. ADAM is implemented on a field programmable gate array (FPGA) platform, and its performance is compared against that of omnidirectional and switched beamforming based multicast. Our experimental results reveal that: 1) switched multicast beamforming has limited gains in indoor multipath environments, whose deficiencies can be effectively overcome by ADAM to yield an average gain of threefold; 2) the higher the dynamic range of the discrete transmission rates employed by the MAC hardware, the higher the gains in ADAMs performance, yielding up to ninefold improvement over omni with the 802.11 rate table; and 3) finally, ADAMs performance is susceptible to channel variations due to user mobility and infrequent channel information feedback. However, we show that training ADAMs signal-to-noise ratio (SNR)-rate mapping to incorporate feedback rate and coherence time significantly increases its robustness to channel dynamics.

LTE in unlicensed spectrum: are we there yet?

In this work, we explore the potential and impact of unlicensed LTE on WiFi in unlicensed spectrum. Our experiments demonstrate that the large asymmetry in the channel access methodologies employed by WiFi and LTE (carrier sensing/notification in WiFi, energy sensing alone in LTE-U), can result LTE-U completely blocking WiFi transmissions, and causing significant degradation to either technologies from collisions. We address this critical sensing asymmetry with Ultron, a LTE-WiFi co-existence solution that integrates WiFis carrier sensing and notification mechanisms into LTE, without any modifications to the LTE PHY standard. Ultron operates at the LTE base station and consists of two key components: (a) WiFi embedding that embeds appropriate data into the LTE-subframes through an intelligent reverse-engineering of the LTE PHY, so as to realize a WiFi PLCP preamble-header transmission over the air directly using the LTE PHY; and (b) scalable WiFi sensing that employs a single WiFi interface and maximizes its carrier sensing benefits to all the unlicensed channels operating at the LTE node. Our evaluations demonstrate that Ultron can increase the WiFi and LTE throughput by 5x and 6x respectively, resulting from a sharp reduction in LTE-WiFi interference.

Wireless multicast scheduling with switched beamforming antennas

Using beamforming antennas to improve wireless multicast transmissions has received considerable attention recently. A recent work proposes to partition all single-lobe beams into groups and to form composite multilobe beam patterns to transmit multicast traffic. Depending on how the power is split among the individual beams constituting a composite beam pattern, two power models are considered: 1) equal power split (EQP), and 2) asymmetric power split (ASP). This paper revisits the key challenge-beam partitioning in the beamforming-multicast problem-and makes significant progress in both algorithmic and analytic aspects of the problem. Under EQP, we propose a low-complexity optimal algorithm based on dynamic programming. Under ASP, we prove that it is NP-hard to have (3/2-ϵ)-approximation algorithm for any ϵ >; 0. For discrete rate functions under ASP, we develop an Asymptotic Polynomial-Time Approximation Scheme (APTAS), an asymptotic (3/2+ β)-approximation solution (where β ≥ 0 depends on the wireless technology), and an asymptotic 2-approximation solution to the problem by relating the problem to a generalized version of the bin-packing problem. In retrospect, we also obtain an asymptotic 2-approximation solution for the generalized bin-packing problem, which is of independent interest. For continuous rate functions under ASP, we develop sufficient conditions under which the optimal number of composite beams is 1, K, and arbitrary, respectively, where K is the total number of single-lobe beams. Both experimental results and simulations based on real-world channel measurements corroborate our analytical results by showing significant improvement compared to state-of-the-art algorithms.

Konark: A RFID based System for Enhancing In-store Shopping Experience

In this paper, we introduce a Radio Frequency IDentification (RFID) based smart shopping system, KONARK, which helps users to checkout items faster and to track purchases in real-time. In parallel, our solution also provides the shopping mall owner with information about user interest on particular items. The central component of KONARK system is a customized shopping cart having a RFID reader which reads RFID tagged items. To provide check-out facility, our system detects in-cart items with almost 100% accuracy within 60s delay by exploiting the fact that the physical level information (RSSI, phase, doppler, read rate etc.) of in-cart RFID tags are different than outside tags. KONARK also detects user interest with 100% accuracy by exploiting the change in physical level parameters of RFID tag on the object user interacted with. In general, KONARK has been shown to perform with reasonably high accuracy in different mobility speeds in a mock-up of a shopping mall isle.

Orchestrating the Data-Plane of Virtual LTE Core Networks

Growing demand for data and increasing number of devices are drastically changing the scale of operation in mobile networks. Future services and business models require efficient provisioning with enhanced traffic management. It is hard to meet these requirements on todays mobile networks that are deployed over specialized hardware. While operators are keen to adopt NFV (Network Function Virtualization) to virtualize their networks, virtualized mobile network deployments face a few technical barriers. To address these challenges, we design SCOPE that effectively applies concepts from SDN and distributed systems to realize NFV-based LTE core networks. Using centralized allocation, SCOPE effectively manages the resources across multiple telecom data-centers in a way to meet the traffic requirements. To enforce the computed al- locations, SCOPE includes flexible and efficient mechanisms to configure the data-plane. With full compliance to 3GPP- based protocols, SCOPE ensures faster and cost-effective deployments. The efficacy of SCOPE is shown using a prototype implementation and large-scale simulations.