Sequans Communications (France)

Low-cost, resource-constrained, mainte-nance-free, and energy-harvesting (EH) Internet of Things (IoT) devices, referred to as zero-energy devices (ZEDs), are rapidly attracting attention from industry and academia due to their myriad of applications. To date, such devices remain primar-ily unsupported by modern IoT connectivity solutions due to their intrinsic fabrication, hardware, deployment, and operation limitations, while lacking clarity on their key technical enablers and prospects. Herein, we address this by discussing the main characteristics and enabling technologies of ZEDs within the next generation of mobile networks, specifically focusing on unconventional EH sources, multi-source EH, power management, energy storage solutions, manufacturing material and practices, backscattering, and low-complexity receivers. Moreover, we highlight the need for lightweight and energy-aware computing, communication, and scheduling protocols, while discussing potential approaches related to tiny machine learning (TinyML), duty cycling, and infrastructure enablers like radio frequency wire-less power transfer and wake-up protocols. Chal-lenging aspects and open research directions are identified and discussed in all the cases. Finally, we showcase an experimental ZED proof-of-con-cept related to ambient cellular backscattering.

The fifth generation of cellular communication systems is foreseen to enable a multitude of new applications and use cases with very different requirements. A new 5G multi-service air interface needs to enhance broadband performance as well as provide new levels of reliability, latency, and supported number of users. In this paper, we focus on the massive Machine Type Communications (mMTC) service within a multi-service air interface. Specifically, we present an overview of different physical and medium access techniques to address the problem of a massive number of access attempts in mMTC and discuss the protocol performance of these solutions in a common evaluation framework.

We present a precoding approach for spatial modulation (SM) to provide robustness against both the Rician fading effects and also spatial correlations among transmit antennas. This approach, based on phase-rotation and/or amplitude scaling of the transmitted symbols according to the active transmit antenna, can be implemented while keeping the average power budget and without any explicit knowledge of the channel state information at the transmitter. The optimum values of the precoding coefficients are determined so as to minimize the asymptotic average bit-error rate (ABER). Both theoretical analysis and simulation results indicate significant performance improvements even in the case of heavily correlated transmit antennas.

In this paper, we introduce a new spatial modulation (SM) technique using one or two active antennas and multiple signal constellations. The proposed technique, which we refer to as Enhanced SM or ESM, conveys information bits not only by the index(es) of the active antenna(s), but also by the constellations transmitted from each of them. The main feature of ESM is that it uses a primary signal constellation during the single active antenna periods and some other secondary constellations during the periods with two active transmit antennas. The secondary signal constellations are derived from the primary constellation by means of geometric interpolation in the signal space. We give design examples using two and four transmit antennas and QPSK, 16QAM, and 64QAM as primary modulations. The proposed technique is compared to conventional SM as well as to spatial multiplexing (SMX), and the results indicate that in most cases, ESM provides a substantial performance gain over conventional SM and SMX while reducing the maximum-likelihood (ML) decoder complexity.

Co-channel interference suppression is a key design concern for next-generation communication systems. It is particularly challenging in the presence of frequency-selective fading as the covariance matrices of the interference plus noise vary across subcarriers. The moving average technique is an effective scheme for estimating the frequency- selective covariance matrices. But the problem of choosing the optimal window size is far from trivial. In this work, we propose a window selection scheme based on the mean square error (MSE) of the covariance estimate. It only requires information of the signalto-noise ratio (SNR) and signal-to-interference ratio (SIR) and is robust against variations of the interfering channel's power delay profile. Moreover, the results can be applied to time-varying channels by simply replacing the frequency correlation function by the time correlation function.

A robust receiver for multiple-input multiple-output orthogonal frequency-division multiplexing (MIMO-OFDM) systems is proposed. We are interested in the scenario when only a limited number of observations in both time and frequency domains are available. For this scenario, perfect channel state information is impossible to obtain and the receiver suffers from statistical information mismatch. To overcome this limitation, we first propose the optimum receiver by performing jointly channel and data estimation. For statistical information mismatch, we construct a finite set of covariance matrices and derive a model-selection scheme based on Bayesian Model Selection. Finally, the sliding-window scheme is used in order to enhance the model selection accuracy. Simulation results are presented, showing that the proposed scheme outperforms the conventional scheme under imperfect channel knowledge.

LTE and LTE-Advanced have introduced complex system features to improve system capacity. Although exhaustively simulated, it often happens that the simulated capacity figures differ from the actual performance seen in the field. This paper explores the combination of real measurements from LTE devices and realistic propagation models to generate coverage maps that are truly representative of radio performance. The paper illustrates the proposed methodology by forecasting the gain of inter-cell interference mitigation implemented in a UE device.

Crisis management requires an efficient collaboration between heterogeneous actors in two places: the crisis scene (involving the operational actors) and the crisis cell (gathering the representatives for each participating group). This chapter presents how to define a situational model and use the embedded knowledge to deduce a collaborative business process dedicated to support the collaborative situation. The deduced collaborative process model has to be implemented as a collective computerizable workflow. Due to the obvious instability of a crisis situation, agility, as the ability to adapt to change, is a crucial requirement for a crisis cell, and for its mediation information system (MIS). The main factor of MIS agility is based on the MIS engineering approach and especially the MIS reengineering approach. Indeed, this design method has been implemented into an Enterprise Service Bus (ESB) where each tool of each step that has been plugged has a service. Controlled Vocabulary Terms business communication; information systems

In this paper, the truncated singular value decomposition expectation-maximization (TSVD-EM) based channel estimation on single transmit antenna transmission is extended to transmit diversity transmission. Particular attention is given to Long Term Evolution (LTE) systems. In order to obtain the received symbols for each transmit antenna, an approximation is proposed by using the soft symbols and channel estimates from the previous iteration. We prove that the mean square error (MSE) of TSVD-EM on transmit diversity transmission has almost the same constant value at high signal-to-noise ratio (SNR) as on single transmitter antenna case. Simulation results show that the proposed TSVD-EM channel estimation improves system performances remarkably and approaches the performance with perfect channel state information. Even without pilot boosting used in LTE systems, the TSVD-EM achieves the same performances as with pilot boosting.

A relatively recent idea of extending the benefits of MIMO systems to multiuser scenarios seems promising in the context of achieving high data rates envisioned for future cellular standards after 3G (3rd Generation). Although substantial research has been done on the theoretical front, recent focus is on making Multiuser Multiple-Input Multiple-Output (MUMIMO) practically realizable. This paper presents an overview of the different MU-MIMO schemes included/being studied in 3GPP standardization from LTE (long-term evolution) to LTE Advanced. MU-MIMO system concepts and implementation aspects have been studied here. Various low-complexity receiver architectures are investigated, and their performance assessed through link-level simulations. Appealing performance offered by low-complexity interference aware (IA) receivers is notably emphasized. Furthermore, system level simulations for LTE Release 8 are provided. Interestingly, it is shown that MU-MIMO only offers marginal performance gains with respect to single-user MIMO. This arises from the limited MU-MIMO features included in Release 8 and calls for improved schemes for the upcoming releases.