The Ambient Internet of Things (AIoT), recently standardized by the 3rd Generation Partnership Project (3GPP), demands a low-power wide-area communication solution. Ambient Backscatter Communication (AmBC) is a promising approach that enables Backscatter Devices (BDs) to communicate by reusing existing signals without additional spectrum or energy cost. This paper investigates the feasibility of AmBC in the uplink of Long Term Evolution (LTE) cellular systems. We model the received BD signal, derive the optimal Maximum A Posteriori (MAP) detector, and propose simplified receiver architectures that achieve near-optimal performance with reduced complexity. A theoretical Bit Error Rate (BER) analysis is developed, including a Gaussian approximation, and the achievable coverage is evaluated. The results show that AmBC can sustain a BER on the order of 10−2at a reading distance of 1.5 m. Over-the-air experiments using commercial LTE uplink Sounding Reference Signals (SRS) further confirm the theoretical and simulation results. Overall, this work demonstrates that LTE cellular systems can natively support AmBC in the uplink, reinforcing its potential as a symbiotic radio paradigm for future low-power, spectrum-efficient AIoT connectivity.

The Long Term Evolution (LTE) is a promising can-didate to be used as a signal source in the Ambient Backscatter Communications (AmBC). LTE provides ubiquitous coverage, and LTE User Equipment (UE), such as mobile phone, can be used as the reader of a Backscatter Device (BD) signal with small firmware modifications. In this paper we measure a BD signal indoor coverage with commercial LTE base station as the illuminating ambient signal. The reader is synchronized to the LTE BS and estimates the BD signal from the LTE signal pilots. The BD is fully passive powered by a solar panel. The BD locations are distributed spatially along the corridor and for each BD location we measure the AmBC reader signal Bit Error Ratio (BER). The signal is uncoded. For each BD location the BER is measured from different directions with respect to the BD position. The measurement results show that along the corridor in most location, the observed BER is in order one percent. The results shed light on the feasibility of applications where the UE is in close proximity to the BD.

Ambient backscatter communication (AmBC) technology and zero-energy device (ZED) have been introduced as promising enablers for Internet-of- Things (IoT) applications in next-generation networks. AmBC is an eco-friendly technology that allows devices to communicate by backscattering ambient radio frequency (RF) waves, rather than generating signals by themselves. When introducing AmBC to cellular networks, ZEDs are proposed as self-powered backscatter devices connected to the 6G network. A ZED harvests energy solely from ambient and solar sources. Owing to its low power consumption and simple hardware design, ZED is poised to play a significant role in large-scale IoT applications, such as logistics and automated warehousing. In this paper, we develop an OpenAirInterface(OAI)-based AmBC platform and implement AmBC in a bistatic way, utilizing an OAI long-term evolution (LTE) base station(BS), an OAI LTE user equipment (UE) and a ZED. The ZED backscatters ambient RF waves from the BS and the UE decodes the backscattered data using pilots. This demonstrates the feasibility for a standard-compliant UE to function as an AmBC reader when the BS serves as an ambient source. Additionally, we propose a multi-frequency detector to enhance the detection performance of ZEDs. Finally, our work reveals the potential for new IoT use cases within existing architectures and for future technologies.

As upcoming, beyond-5G (B5G) wireless network generations are expected to deliver much better performance than existing solutions, Reconfigurable intelligent surfaces (RISs) are gaining relevance as one of the new key technologies able to facilitate such improvement. Interestingly, they can redesign how the propagation environment is conceived by giving an opportunity to programmatically alter it: they can be configured to behave as orientable mirrors, scatterers, or lenses. This flexibility allows for the successful exploitation of bands which provide superior performance in wireless links but present poor propagation properties. However, this fascinating technology comes at not negligible costs: RISs require ad-hoc design, deployment and management operations to be fully exploited. In this paper, we tackle one of the open problems in the RISs literature: the optimal placement. We propose a model-based and a model-free approach, respectively RISA and AI-RISA, showcasing their large-scale solutions on synthetic topologies to improve communication performance while solving the “dead-zone” coverage problem. Additionally, our frameworks are empirically validated within a realistic indoor scenario, the Rennes railway station, showing how a complex indoor propagation environment can be fully disciplined by an advanced RISs installation.

Ambient power enabled Internet of Things a.k.a. Ambient IoT is a novel concept connecting battery-free energy autonomous devices to the Internet. In this paper, we demonstrate the feasibility of using the channel estimator at the user equipment (UE) as a receiver for backscatter signals in LTE downlink. Our real-time demonstrator system consists of signal generator that mimics the operation of a base station (BS), a backscatter device (BD) modulating the incidence signal, and a software defined radio receiver that plays the role of the user equipment. The UE channel estimator and BD demodulation software is implemented with C++ and Python, respectively and made open source. Our results indicate that UE can demodulate the BD signal with bit error less than 10-3 when the downlink signal-to-noise ratio is larger than 10 dB when the pathloss between the BD and UE is less than 13 dB.

Reconfigurable Intelligent Surfaces (RISs) are one of the key emerging 6th Generation (6G) technologies that are expected to improve the link budgets between transmitters and receivers by adding artificial propagation paths. In such re-configured propagation environment, Downlink (DL) Multi-User Multi-Input Multi-Output (MU-MIMO) brings capacity improvement to cellular networks. It benefits from the spatial dimension offered by MIMO systems to enable simultaneous transmission of independent data streams to multiple users on the same radio resources by applying appropriate Beamforming (BF) schemes. However, in some cases, serving the same subset of users for a long period of time may cause some undesired regions where the average Electromagnetic Field Exposure (EMFE) exceeds the regulatory limits. To address this challenge, we propose in this paper a novel Electromagnetic Field (EMF) aware MU-MIMO BF scheme that aims to optimize the overall capacity under EMF constraints in RIS-aided cellular networks.

Future generations of wireless networks will offer unrivalled performance via unprecedented solutions: meta-surfaces will drive such revolution by enabling control over the surrounding propagation environment, always portrayed as a tamper-proof black box. The reconfigurable intelligent surface (RIS) technology, envisioned as the discrete version of a metasurface, can dynamically alter the propagation of the impinging signals by, e.g., steering the corresponding beams towards controllable directions. This will unlock new application opportunities and deliver advanced end-user services.However, this fascinating solution comes at non-negligible costs: RISs require ad-hoc design, deployment and management operations to be fully exploited. In this paper, we tackle the RISs placement problem from a theoretical viewpoint, showcasing a large-scale solution on synthetic topologies to improve communication performance while solving the dead-zone problem. Additionally, our mathematical framework is empirically validated in a realistic indoor scenario, the Rennes railway station, showing how a complex indoor propagation environment can be fully disciplined by an advanced RIS installation.

Reconfigurable Intelligent Surface (RIS) is one of the key technologies for the upcoming 6th Generation (6G) communications, which can improve the signal strength at the receivers by adding artificial propagation paths. In the context of Downlink (DL) Multi-User Multiple-Input Multiple-Output (MU-MIMO) communications, designing an appropriate Beamforming (BF) scheme to take full advantage of this reconfigured propagation environment and improve the network capacity is a major challenge. Due to the spatial dimension provided by MIMO systems, independent data streams can be transmitted to multiple users simultaneously on the same radio resources. It is important to note that serving the same subset of users over a period of time may lead to undesired areas where the average Electromagnetic Field Exposure (EMFE) exceeds regulatory limits. To address this challenge, in this paper, we propose a Dual Gradient Descent (Dual-GD)-based Electromagnetic Field (EMF)-aware MU-MIMO BF scheme that aims to optimize the overall capacity under EMFE constraints in RIS-aided 6G cellular networks.

Ambient backscatter communications have been identified for ultra-low energy wireless communications. Indeed, a tag can send a message to a reader without emitting any wave and without battery, simply by backscattering the waves generated by a source. In the simplest implementation of such a system, the tag sends a binary message by oscillating between two states and the reader detects the bits by comparing the two distinct received powers. In this paper, for the first time, we propose to study an ambient backscatter communication system, in the presence of a diffusing surface, a simple flat panel that diffuses in all directions. We establish the analytical closed form expression of the power contrast in the presence of the surface. We show that the diffusing surface improves the power contrast. Moreover our approach allows us to express the contrast to noise ratio, and therefore to establish the BER performance. Furthermore, we derive the optimum source transmit power for a given target power contrast. This makes it possible to quantify the amount of energy that can be saved at the source side, thanks to the diffusing surface.

Ambient backscatter communications have been introduced as low-power communications for green networking. This technology is very promising as it recycles ambient radio frequency waves, however such systems have limitations and suffer from poor performance due to their low-power. In this paper, we present and evaluate the performance of an ambient backscatter system equipped with a massive multiple input multiple output (MIMO) antenna at the reader side. A mobile device transmits a signal that is backscattered by a tag and received by the reader. Thanks to the spatial diversity of the massive MIMO antenna, the reader is able to identify, for each received signal, the state of the tag (backscattering or transparent) that corresponds to a bit of the tag message. First, we experimentally determine the channel between the device and the reader for two states of the tag. Then using a minimum mean square error algorithm we evaluate the performance of the ambient backscatter communication. We demonstrate that the performance of the ambient backscatter system is significantly improved by the massive MIMO reader.

Ambient backscatter communication system is an emerging and promising low-energy technology for Internet of Things. In such system, a device named tag, sends a binary message to a reader by backscattering a radio frequency signal generated by an ambient source. Such tag can operate without battery and without generating additional wave. However, the tag-to-reader link suffers from the source-to-reader direct interference. In this paper, for the first time, we propose to exploit a "polarization reconfigurable" antenna to improve robustness of the tag-to-reader link against the source-to-reader direct interference. Our proposed new tag sends its message by backscattering as an usual tag. However, it repeats its message several times, with a different radiation pattern and polarization, each time. We expect one polarization pattern to be better detected by the reader. We show by simulations and experiments, in line-of-sight and in richly scattering environment, that a polarization reconfigurable tag limited to 4 polarization directions outperforms a non-reconfigurable tag and nearly equals an ideally reconfigurable tag in performance.

In this paper, we present an ambient backscatters-friendly 5G network that creates locations with large power (hot spots) for tags and good reception locations (quiet spots or coherent spots) for readers. Tags are devices that communicate information to readers by backscattering ambient radiofrequency signals. The massive multiple input multiple output (M-MIMO) antenna and beamforming capability of the 5G network is used as follows. In a first step, a training device (separate from tags and readers) is used to send pilots and train the 5G network to perform focusing and/or nulling onto marked locations. In a second step, tags and readers are positioned onto the marked locations. The robustness of M-MIMO beamforming to slight changes in the environment is exploited. Our initial simulation results, in a multipath propagation channel environment, show that creating a hot spot on a tag improves the tag-reader range however with a low probability of detection. Creating a hot spot on a tag and a good reception spot on a reader at the same time, improves the tag-reader range with 99% probability of detection. The study also shows that beamforming does not degrade the performance of a legacy 5G communication.

For future large-scale multi-antenna systems, channel orthogonal downlink pilots are not feasible due to extensive overhead requirements. Instead, channel reciprocity can be utilized in time division duplex (TDD) systems so that the downlink channel estimates can be based on pilots transmitted during the uplink. User mobility affects the reciprocity and makes the channel state information outdated for high velocities and/or long downlink subframe durations. Channel extrapolation, e.g. through Kalman prediction, can reduce the problem but is also limited by high velocities and long downlink subframes. An alternative solution has been proposed where channel predictions are made with the help of an extra antenna, e.g. on the roof of a car, so called predictor antenna, with the primary objective to measure the channel at a position that is later encountered by the rearward antenna(s). The predictor antenna is not directly limited by high velocities and allows the channel in the downlinks to be interpolated rather than extrapolated. One remaining challenge here is to obtain a good interpolation of the uplink channel estimate, since a sequence of uplink reference signals (pilots) will be interrupted by downlink subframes. We here evaluate a Kalman smoothing estimate of the downlink channels and compare it to a cubic spline interpolation. These results are also compared to results where uplink channels are estimated through Kalman filters and predictors. Results are based on measured channels and show that with Kalman smoothing, predictor antennas can enable accurate channel estimates for a longer downlink period at vehicular velocities. The gaps in the uplink pilot stream, due to downlink subframes, can have durations that correspond to a vehicle movement of up to 0.75 carrier wavelengths in space, for Rayleigh-like non-line-of-sight fading.

Real-life ants use pheromone trails to guide themselves back and forth from food, without the help of a map. In this paper, we introduce a new protocol for wireless networks, called Time Reversal for Ant Trails (TRAT) which mimics ants by using electromagnetic virtual beacons generated by Time Reversal focusing instead of pheromones. Simulations show that for a given trajectory, the performance of the proposed scheme increases with the number of transmit antennas at the network side, with the precision of the scanning, and decreases with inter-beacon spacing and the carrier frequency.

By using large point-to-point multiple input multiple output (MIMO), spatial multiplexing of a large number of data streams in wireless communications using millimeter-waves (mm-waves) can be achieved. However, according to the antenna spacing and transmitter-receiver distance, the MIMO channel is likely to be ill-conditioned. In such conditions, highly complex schemes such as the singular value decomposition (SVD) are necessary. In this paper, we propose a new low complexity system called discrete Fourier transform based spatial multiplexing (DFT-SM) with maximum ratio transmission (DFT-SM-MRT). When the DFT-SM scheme alone is used, the data streams are either mapped onto different angles of departures in the case of aligned linear arrays, or mapped onto different orbital angular momentums in the case of aligned circular arrays. Maximum ratio transmission pre-equalizes the channel and compensates for arrays misalignments. Simulation results show that, although the DFT-SM-MRT scheme has a much lower complexity than the SVD scheme, it still achieves large spectral efficiencies and is robust to misalignment and reflection.

Low complexity Multiple Input Multiple Output (MIMO) precoders for Orthogonal Frequency Division Multiplex (OFDM), such as Maximum Ratio Transmission (MRT) and Minimum Mean Square Error (MMSE) precoders enable to multiplex data streams in the spatial domain, without breaking OFDM orthogonality in the frequency domain, and therefore achieve a high spectral efficiency. OFDM using Offset Quadrature Amplitude Modulation (OFDM/OQAM) is an alternate modulation which is more spectrally efficient than OFDM. Unfortunately, when applied to OFDM/OQAM, traditional low complexity precoders introduce an inter-carrier interference (ICI) which is complex to cancel at the receiver side. This paper proposes a new family of low complexity precoders, called “Make-It-Real” (MIR) precoders. These precoders are designed so that the equivalent channel including precoding and propagation is “made real” and does not break the orthogonality of OFDM/OQAM in the frequency domain. At the receiver side, a simple extraction of the real part of the demodulated signal is necessary. Simulations show that OFDM/OQAM with MIR MMSE precoder outperforms all studied MIMO OFDM solutions, without requiring a complex ICI cancellation at the receiver.

Time Reversal (TR) is a multiple-input single-output (MISO) pre-filtering technique that allows a signal to be sent towards a target antenna by focusing the wave at the receiver both in the time and in the space domains. Recently, TR has been advertised for both green communications and confidential communications. This paper proposes an experimental characterization of the confidentiality of an indoor MISO-TR communication. The transmit system is made of 16 transmit antennas distributed within a room and the data stream is transmitted with a 256-Quadratic Amplitude Modulation (256QAM). The received signal is demodulated by the target user but also by a spy or eavesdropper antenna, both using a Single Tap Receiver. The Bit Error Rate (BER) achieved by the spy is then evaluated for variable positions of the spy nearby the target. The “spy BER” is plotted as a function of the spy-to-target distance. This experimental measurement clearly shows the presence of a spy BER “sink” centered on the target.

Wireless communication systems based on Time Reversal (TR) and a Single Tap Receiver (STR) are optimum at low Signal-to-Noise Ratio (SNR), while keeping low complexity at the receiver. Thus, they are interesting for low order Phase and Amplitude Modulations, such as Binary Phase Shift Keying (BPSK) or Quadrature Phase Shift Keying (QPSK). However, at higher Signal to Noise Ratio, Inter-Symbol Interference prevents from using higher order modulations such as 16 Quadrature Amplitude Modulation (16QAM) or 64QAM. This paper presents a new spatial modulation technique called Received Antenna Shift Keying (RASK), enabling the use of higher order modulation with TR and STR. Information is not conveyed by Phase and Amplitude Modulation (PAM). Instead, at the transmitter side, Time Reversal pre-filtering technique is used to focus a signal with constant amplitude and phase onto a single receive antenna among several receive antennas. Every symbol duration, the transmitter updates the target receive antenna. The index of the antenna is simply equal to the integer value coded by the binary sequence of information that has to be transmitted during the considered symbol. At the receiver side, each antenna has a Single Tap Receiver. The output of the Single Tap Receivers are used by a simple detector to determine the target receive antenna among all antennas. The detected antenna index is then converted into a binary sequence. If N is the number of receive antennas, a N-RASK system transmits Log2(N) bits per symbol. The performance of 16RASK is compared to 16QAM, with Time Reversal, and 1 bit Time Reversal, using simulations modeling inter-symbol and un-perfect spatial focusing. The study shows that 16RASK outperforms 16QAM, under strong multipath or when the number of transmit antennas is high.

This paper proposes a new pre-coding technique called Frequency Division Duplex Time Reversal (FDD TR) for FDD Multiple Input Multiple Output (MIMO) wireless communications which relies on unquantized uncoded channel feedback. This technique is compared in terms of performance and overhead to Time Reversal (TR), 1bit Time Reversal (1bit TR). The performance assessment of a 16x2 MIMO system, is based on post receiver Signal To Noise Ratio (SINR) formulas and simulated indoor propagation channels. Results show that FDD TR outperforms 1bit TR in terms of overhead and throughput.

In this paper, two new coordination and resource allocation schemes based on zero-forcing and maximum ratio transmission pre-coding for densely deployed femtocells connected through a high data rate backhaul are proposed. These schemes aim at offering a uniform rate in a given building, i.e. equal rate simultaneously achieved by all users in that building. New link adaptation and power allocation mechanisms that maximize the uniform rate are proposed. The performance of the proposed schemes is assessed in terms of per user spectral efficiency and backhaul control overhead using system level simulations under realistic propagation models. The study shows that zero-forcing outperforms maximum ratio transmission in terms of spectrum efficiency while being penalizing in terms of backhaul control overhead.

In this paper, we study the performance of time reversal (TR) pre-equalization technique in terms of outage probability for downlink multi-cellular wideband indoor communication environments. We derive a closed form expression of the cumulative distribution function (CDF) of the output signal to interference ratio (SIR) or equivalently the outage probability. This expression allows for faster and simpler performance analysis of newly designed wireless communication systems.

This paper provides a link and system level study of the downlink in a B3G system using MIMO OFDMA techniques. A 3GPP/LTE-like scenario, in terms of frame structure and system main parameters, is considered in this study. At the link level, the double Alamouti MIMO scheme is studied and the performances of various modulation and coding schemes (MCS) are provided. The impact of real MIMO channel estimation (including RF impairments, CFO compensation and automatic gain control AGC) on the MCSs link performance is also presented. System level study is thus carried out to assess the performance of the downlink OFDMA in terms of coverage and cell throughput. Several scheduling disciplines and MIMO schemes are investigated and the impact of the spatial diversity on the cell throughput is provided. This study has been carried out in the scope of the French RNRT OPUS project.