This work studies both limited sensitivity and nonlinearity of far field RF energy harvesting observed in reality and quantifies their effect, attempting to fill a major hole in the simultaneous wireless information and power transfer (SWIPT) literature. RF harvested power is modeled as an arbitrary nonlinear, continuous, and non-decreasing function of received power, taking into account limited sensitivity and saturation effects. RF harvester’s sensitivity may be several dBs worse than communications receiver’s sensitivity, potentially rendering RF information signals useless for energy harvesting purposes. Given finite number of datapoint pairs of harvested (output) power and corresponding input power, a piecewise linear approximation is applied and the statistics of the harvested power are offered, as a function of the wireless channel fading statistics. Limited number of datapoints are needed and accuracy analysis is also provided. Case studies include duty-cycled (non-continuous), as well as continuous SWIPT, comparing with industry-level, RF harvesting. The proposed approximation, even though simple, offers accurate performance for all studied metrics. On the other hand, linear models or nonlinear-unlimited sensitivity harvesting models deviate from reality, especially in the low-input-power regime. The proposed methodology can be utilized in current and future SWIPT research.

This work offers both analog and digital tag modulation schemes and respective receiver designs, for ultra-low power, high performance, ambient backscatter communications. All proposed techniques are based on simple, but careful, switching frequency control at the tag, allowing for easy frequency-domain multiple access. First, a digital modulation scheme is offered, namely pseudo-frequency shift keying (P-FSK), assuming illumination from constant envelope-modulated signals and a fully coherent detector is derived along with closed-form probability of error. A second digital modulation scheme is also offered, based on a frequency-shifted form of binary phase shift keying (S-BPSK), relaxing the constant-envelope requirement for the illuminator and an illumination-agnostic detector is derived. Based on S-BPSK, short packet error correction coding is utilized for ambient backscatter communication, for the first time in the literature. It is shown that the proposed coded scheme under modulated ambient signal illumination & wireless channel variation, offers tremendous performance gains, i.e., modulation of the ambient signal is helpful. Finally, a third, purely analog, modulation scheme is analyzed, based on FM remodulation principles. A low-cost tag is implemented, demonstrating tag-toreceiver ranges up to 26 meters outdoors, power consumption of 24 μWatts in continuous operation, able to be interrogated by any conventional frequency modulation (FM) receiver. The proposed techniques cover a large variety of omnipresent wireless industry systems, enabling universal ambient backscatter and relevant wireless information and power transfer (WIPT) applications.

Scatter radio, i.e., communication by means of reflection, has been recently proposed as a viable ultra-low power solution for wireless sensor networks (WSNs). This work offers a detailed comparison between monostatic and multistatic scatter radio architectures. In monostatic architecture, the reader consists of both the illuminating transmitter and the receiver of signals scattered back from the sensors. The multistatic architecture includes several ultra-low cost illuminating carrier emitters and a single reader. Maximum-likelihood coherent and noncoherent bit error rate (BER), diversity order, average information and energy outage probability comparison is performed, under dyadic Nakagami fading, filling a gap in the literature. It is found that: (i) diversity order, BER, and tag locationindependent performance bounds of multistatic architecture outperform monostatic, (ii) energy outage due to radio frequency (RF) harvesting for passive tags, is less frequent in multistatic than monostatic architecture, and (iii) multistatic coverage is higher than monostatic. Furthermore, a proof-of-concept digital multistatic, scatter radio WSN with a single receiver, four lowcost emitters and multiple ambiently-powered, low-bitrate tags, perhaps the first of its kind, is experimentally demonstrated (at 13 dBm transmission power), covering an area of 3500 m2. Research findings are applicable in the industries of WSNs, radio frequency identification (RFID), and emerging Internet-of-Things.

Time information is critical for a variety of applications in distributed environments that facilitate pervasive computing and communication. This work describes and evaluates a novel Kalman filtering algorithm for end-to-end time synchronization between a client computer and a server of "true" time [e.g., a Global Positioning System (GPS) source] using messages transmitted over packet-switched networks, such as the Internet. The messages exchanged have the network time protocol (NTP) format, and the algorithm evaluated, is performed only at the client side. The Kalman filtering algorithm is compared to two other techniques widely used, based on linear programming and statistical averaging, and the experiments involve independent consecutive measurements (Gaussian case) or measurements exhibiting long-range dependence (self-similar case). Performance is evaluated according to the estimation error of frequency offset and time offset between client and server clock, the standard deviation of the estimates and the number of packets used for a specific estimation. The algorithms could exploit existing NTP infrastructure, and a specific example is presented.

Backscatter (or simply scatter) radio is based on reflection principles, where each tag modulates information on top of an illuminating signal, by simply connecting its antenna to different loads; modulation of information is based on the modifications of the tag antenna-load reflection coefficient, requiring in principle only a switch and omitting powerconsuming signal conditioning units, such as mixers, amplifiers, oscillators, and filters. The ultralow-power nature of backscatter radio, in conjunction with the recent advances in multiple access and achieved communication ranges (on the order of hundreds of meters to kilometers), due to intelligent signal processing, elevate backscatter radio as the de facto communication principle e for nW (or less)-level consumption, last-mile connectivity, and Internet of Things (IoT) networking. This article is an update to the state-of-the-art advances in the emerging backscatter radio domain, focusing on the signal processing engine, including ambient illumination from existing signals, as well as unconventional backscatter radio-based IoT technologies that could revolutionize environmental sensing and agriculture. Finally, the offered research methodology and techniques in short-packet, channel-encoded (or not), coherent (or not) sequence detection will assist researchers in radio-frequency identification (RFID)/backscatter radio as well as other domains of the telecommunications industry.

Channel state information (CSI) at the base station (BS) is crucial to achieve beamforming and multiplexing gains in multiple-input multiple-output (MIMO) systems. State-of-the-art limited feedback schemes require feedback overhead that scales linearly with the number of BS antennas, which is prohibitive for 5G massive MIMO. This paper proposes novel limited feedback algorithms that lift this burden by exploiting the inherent sparsity in double-directional MIMO channel representation using overcomplete dictionaries. These dictionaries are associated with angle of arrival and angle of departure that specifically account for antenna directivity patterns at both ends of the link. The proposed algorithms achieve satisfactory channel estimation accuracy using a small number of feedback bits, even when the number of transmit antennas at the BS is large—making them ideal for 5G massive MIMO. Judicious simulations reveal that they outperform a number of popular feedback schemes and underscore the importance of using angle dictionaries matching the given antenna directivity patterns, as opposed to uniform dictionaries. The proposed algorithms are lightweight in terms of computation, especially on the user equipment side, making them ideal for actual deployment in 5G systems.