An ambient RF energy harvesting and backscatter modulating tag system enabling zero-power wireless data communication

Kim, Young-Han; Ahn, Hyun-Seok; Yoon, Changseok; Lim, Yongseok; Lim, Seung-Ok

doi:10.1145/3131542.3140260

Cited by 2 publications

(5 citation statements)

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“…Applications for the AmBC would be smart home or IoT environments where massive numbers of RF devices are seamlessly integrated into existing wireless infrastructure. For AmBC, AP transmits IEEE 802.11g Wi-Fi OFDM signals [2] while tags harvest these ambient RF signals [46] and upload data streams by switching load impedances [9]. Then, RF tag in SC-AmBC modulates M load impedances with nonorthogonal sparse codeword, while that in TD-AmBC modulates M impedances with TDMA [2], [23].…”

Section: Simulation Resultsmentioning

confidence: 99%

“…Moreover, backscatter symbols from N ≥ K tags (i.e., NOMA) in active states can be interfered in time-domain causing MAI, further complicating reliable detection of AmBC. Since RF tags are powered by ambient energy harvesting, circuit-power constraint that harvested power with efficiency η [46] is greater than circuit power for entire K sampling period should be satisfied. If we assume a linear power consumption model with respect to energy per symbol σ 2 c and backscatter symbol rate R s [8], [9], the circuit-power constraint can be formulated as…”

Section: B System Modelmentioning

confidence: 99%

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Novel Sparse-Coded Ambient Backscatter Communication for Massive IoT Connectivity

Kim

2018

Energies

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Low-power ambient backscatter communication (AmBC) relying on radio-frequency (RF) energy harvesting is an energy-efficient solution for batteryless Internet of Things (IoT). However, ambient backscatter signals are severely faded by dyadic backscatter channel (DBC), limiting connectivity in conventional orthogonal time-division-based AmBC (TD-AmBC). In order to support massive connectivity in AmBC, we propose sparse-coded AmBC (SC-AmBC) based on non-orthogonal signaling. Sparse code utilizes inherent sparsity of AmBC where power supplies of RF tags rely on ambient RF energy harvesting. Consequently, sparse-coded backscatter modulation algorithm (SC-BMA) can enable non-orthogonal multiple access (NOMA) as well as M-ary modulation for concurrent backscatter transmissions, providing additional diversity gain. These sparse codewords from multiple tags can be efficiently detected at access point (AP) using iterative message passing algorithm (MPA). To overcome DBC along with intersymbol interference (ISI), we propose dyadic channel estimation algorithm (D-CEA) and dyadic MPA (D-MPA) exploiting weighted-sum of the ISI for information exchange in the factor graph. Simulation results validate the potential of the SC-AmBC in terms of connectivity, detection performance and sum throughput.

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Section: Simulation Resultsmentioning

confidence: 99%

Section: B System Modelmentioning

confidence: 99%

Novel Sparse-Coded Ambient Backscatter Communication for Massive IoT Connectivity

Kim

2018

Energies

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“…where σ 2 c is the energy per symbol (e.g., 0.58 pJ/symbol [18]), η the energy harvesting efficiency (e.g., 25% [41]), σ 2 b the average backscatter symbol power, and R s = 1 T s represents the backscatter symbol rate. It is noteworthy that since there are U multiple ambient sources with the OFDM modulation, tags can harvest sufficient energy from these sources nearby in dense network scenarios and be activated to upload data to the reader.…”

Section: Duty-cycling Operationmentioning

confidence: 99%

“…Also, the rest of the system parameters [3,18,25,41] can be found in Figure 9b. Although we selected Wi-Fi carriers for performance evaluations, the system can also be generalized to support the other OFDM networks such as LTE or DVB by simple modification of the system parameters (e.g., the pilot subcarrier set Φ PI , the CP size L CP , and the bandwidth W).…”

Section: Practical Implementation Of Ambcmentioning

confidence: 99%

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Multi-Dimensional Sparse-Coded Ambient Backscatter Communication for Massive IoT Networks

Kim

2018

Energies

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In this paper, we propose a multi-dimensional sparse-coded ambient backscatter communication (MSC-AmBC) system for long-range and high-rate massive Internet of things (IoT) networks. We utilize the characteristics of the ambient sources employing orthogonal frequency division multiplexing (OFDM) modulation to mitigate strong direct-link interference and improve signal detection of AmBC at the reader. Also, utilization of the sparsity originated from the duty-cycling operation of batteryless RF tags is proposed to increase the dimension of signal space of backscatter signals to achieve either diversity or multiplexing gains in AmBC. We propose optimal constellation mapping and reflection coefficient projection and expansion methods to effectively construct multi-dimensional constellation for high-order backscatter modulation while guaranteeing sufficient energy harvesting opportunities at these tags. Simulation results confirm the feasibility of the long-range and high-rate AmBC in massive IoT networks where a huge number of active ambient sources and passive RF tags coexist.

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An ambient RF energy harvesting and backscatter modulating tag system enabling zero-power wireless data communication

Cited by 2 publications

References 1 publication

Novel Sparse-Coded Ambient Backscatter Communication for Massive IoT Connectivity

Novel Sparse-Coded Ambient Backscatter Communication for Massive IoT Connectivity

Multi-Dimensional Sparse-Coded Ambient Backscatter Communication for Massive IoT Networks

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