On the Energy Efficiency of LT Codes in Proactive Wireless Sensor Networks

This paper presents an in-depth analysis on the energy efficiency of Luby Transform (LT) codes with Frequency Shift Keying (FSK) modulation in a Wireless Sensor Network (WSN) over Rayleigh fading channels with pathloss. We describe a proactive system model according to a flexible duty-cycling mechanism utilized in practical sensor apparatus. The present analysis is based on realistic parameters including the effect of channel bandwidth used in the IEEE 802.15.4 standard, active mode duration and computation energy. A comprehensive analysis, supported by some simulation studies on the probability mass function of the LT code rate and coding gain, shows that among uncoded FSK and various classical channel coding schemes, the optimized LT coded FSK is the most energy-efficient scheme for distance d greater than the pre-determined threshold level d_T , where the optimization is performed over coding and modulation parameters. In addition, although the optimized uncoded FSK outperforms coded schemes for d < d_T , the energy gap between LT coded and uncoded FSK is negligible for d < d_T compared to the other coded schemes. These results come from the flexibility of the LT code to adjust its rate to suit instantaneous channel conditions, and suggest that LT codes are beneficial in practical low-power WSNs with dynamic position sensor nodes.Comment: accepted for publication in IEEE Transactions on Signal Processin

Symbol-Level Multiuser MISO Precoding for Multi-level Adaptive Modulation

Symbol-level precoding is a new paradigm for multiuser downlink systems which aims at creating constructive interference among the transmitted data streams. This can be enabled by designing the precoded signal of the multiantenna transmitter on a symbol level, taking into account both channel state information and data symbols. Previous literature has studied this paradigm for MPSK modulations by addressing various performance metrics, such as power minimization and maximization of the minimum rate. In this paper, we extend this to generic multi-level modulations i.e. MQAM and APSK by establishing connection to PHY layer multicasting with phase constraints. Furthermore, we address adaptive modulation schemes which are crucial in enabling the throughput scaling of symbol-level precoded systems. In this direction, we design signal processing algorithms for minimizing the required power under per-user SINR or goodput constraints. Extensive numerical results show that the proposed algorithm provides considerable power and energy efficiency gains, while adapting the employed modulation scheme to match the requested data rate

A two phase framework for visible light-based positioning in an indoor environment: performance, latency, and illumination

Recently with the advancement of solid state lighting and the application thereof to Visible Light Communications (VLC), the concept of Visible Light Positioning (VLP) has been targeted as a very attractive indoor positioning system (IPS) due to its ubiquity, directionality, spatial reuse, and relatively high modulation bandwidth. IPSs, in general, have 4 major components (1) a modulation, (2) a multiple access scheme, (3) a channel measurement, and (4) a positioning algorithm. A number of VLP approaches have been proposed in the literature and primarily focus on a fixed combination of these elements and moreover evaluate the quality of the contribution often by accuracy or precision alone. In this dissertation, we provide a novel two-phase indoor positioning algorithmic framework that is able to increase robustness when subject to insufficient anchor luminaries and also incorporate any combination of the four major IPS components. The first phase provides robust and timely albeit less accurate positioning proximity estimates without requiring more than a single luminary anchor using time division access to On Off Keying (OOK) modulated signals while the second phase provides a more accurate, conventional, positioning estimate approach using a novel geometric constrained triangulation algorithm based on angle of arrival (AoA) measurements. However, this approach is still an application of a specific combination of IPS components. To achieve a broader impact, the framework is employed on a collection of IPS component combinations ranging from (1) pulsed modulations to multicarrier modulations, (2) time, frequency, and code division multiple access, (3) received signal strength (RSS), time of flight (ToF), and AoA, as well as (4) trilateration and triangulation positioning algorithms. Results illustrate full room positioning coverage ranging with median accuracies ranging from 3.09 cm to 12.07 cm at 50% duty cycle illumination levels. The framework further allows for duty cycle variation to include dimming modulations and results range from 3.62 cm to 13.15 cm at 20% duty cycle while 2.06 cm to 8.44 cm at a 78% duty cycle. Testbed results reinforce this frameworks applicability. Lastly, a novel latency constrained optimization algorithm can be overlaid on the two phase framework to decide when to simply use the coarse estimate or when to expend more computational resources on a potentially more accurate fine estimate. The creation of the two phase framework enables robust, illumination, latency sensitive positioning with the ability to be applied within a vast array of system deployment constraints

LPDQ: a self-scheduled TDMA MAC protocol for one-hop dynamic lowpower wireless networks

Current Medium Access Control (MAC) protocols for data collection scenarios with a large number of nodes that generate bursty traffic are based on Low-Power Listening (LPL) for network synchronization and Frame Slotted ALOHA (FSA) as the channel access mechanism. However, FSA has an efficiency bounded to 36.8% due to contention effects, which reduces packet throughput and increases energy consumption. In this paper, we target such scenarios by presenting Low-Power Distributed Queuing (LPDQ), a highly efficient and low-power MAC protocol. LPDQ is able to self-schedule data transmissions, acting as a FSA MAC under light traffic and seamlessly converging to a Time Division Multiple Access (TDMA) MAC under congestion. The paper presents the design principles and the implementation details of LPDQ using low-power commercial radio transceivers. Experiments demonstrate an efficiency close to 99% that is independent of the number of nodes and is fair in terms of resource allocation.Peer ReviewedPostprint (author’s final draft