International audience

The rise of IoT in the past few years has led to the massive deployment of connected devices making IoT networks denser. To optimize transmission arising from congestion in dense networks, adaptive data-rate algorithms have been implemented such as the one used in the LoRaWAN protocol. Utilization of algorithms based on reinforcement learning, especially multi-armed bandit, have been investigated, but the duty-cycle limitation decreases the performance of these algorithms in dense networks up to 15 %. This paper aims at giving a solution to resolve the issue caused by duty-cycle limitation, using the LoRa technology as a study case. An effort was done on energy consumption and the reward is modified in order to save energy according to the quality of service. Performances are evaluated thanks to our new simulator J-LoRaNeS based on the Julia language.

Non-Intrusive Load Monitoring (NILM) attempts to break down the aggregated electrical consumption signal into the power consumption of each individual appliance, which can provide helpful understanding on energy consumption patterns and helps reduce overall energy usage and costs. This paper proposes an occupancy-aided energy disaggregation approach to address the NILM problem. Our methodology encompasses three key steps: firstly, features extraction from environmental sensors through the training of a DAE model; secondly, inference of occupancy information using the K-means algorithm; and finally, the disaggregation process using a Recurrent Neural Network (RNN) model, incorporating the detected occupancy status alongside power data. Experiments conducted on our real-world dataset demonstrate that our method significantly outperforms the state-of-the-art models while having good generalization capacity, achieving roughly 40% Mean Absolute Error (MAE) gain and 30% Root Mean Squared Error (RMSE) gain on a specific appliances disaggregation compared to the conventional NILM approach where only the power data is used.

In the last decade Internet of Things (IoT) grew up in an exponential behavior with applications requiring long range and low power wireless transmissions. Factory of the Future (FoF), also called Industry 4.0, aims to use IoT technologies to enhance productivity, therefore adding high reliability constraints. Several IoT standards were proposed and LoRa has emerged as a high potential candidate for a variety of applications. LoRa modulation is based on a chirp spread-spectrum technique and offers efficient transmission up to 50 kbps over several kilometers. The performance of LoRa in terms of symbol or bit error probability has been theoretically analyzed in few recent papers for a Gaussian channel. However, the industrial environment is often corrupted with impulsive non Gaussian noise generated by high-power equipment. In this paper, the impact of impulsive noise, modeled by the Middleton Class-A noise, is introduced and the robustness of a LoRa communication is studied. Compared to the Gaussian case, simulations show that impulsive noise may severely degrade system performance. This Signal-to-Noise Ratio loss can reach up to 10 dB, but increasing the spreading factor can reduce the noise impact.

In the last years, Internet of Things (IoT) grew up in an exponential behavior and required long range and low power wireless transmissions. Several standards were proposed and LoRa has emerged as a high potential candidate for many IoT solutions. LoRa modulation is based on a chirp spread-spectrum technique and offers efficient transmission up to 50 kbps over several kilometers. Although the principle is known and studied for decades now, the performance in terms of symbol or bit error probability has been theoretically analyzed in few papers only. Closed-form approximations for additive white Gaussian noise and Rayleigh fading were recently proposed. In this paper, we propose a new approach based on Marcum function. Simulations and comparisons with the state of the art show that the proposed approximation of the Binary Error Probability is up to ten times more accurate for a full SNR range.

In this paper, imperfect feedback-based linear precoding schemes are proposed for multiple-input-multipleoutput (MIMO) wireless communication systems, where input symbol streams are encoded by using generalized-orthogonal space-time block codes. The imperfect feedback information drastically degrades the system performance. Therefore, to overcome the effect of erroneous feedback information, error-tolerant weighting (ETW) schemes are implemented by employing diagonal precoder. The communication links are assumed to be Nakagami-m distributed for accurately characterizing practical wireless channels under different fading scenarios. Exact and asymptotic symbol-error-rate (SER) expressions of the considered MIMO system are derived under imperfect feedback with the help of order statistics. The most appropriate values of the transmit weights of the precoder matrix are obtained by minimizing the derived average SER over fixed and adaptive signal-to-noise ratio. Further, we study the trade-off between the proposed optimal and suboptimal feedback-based precoding schemes. Moreover, the ergodic-rate of the ETW schemes is also derived with imperfect feedback for arbitrary MIMO system by using the moment generating function approach. The simulated and analytical results show that a significant performance gain is achieved by the ETW schemes as compared to the uniform power allocation and existing precoding techniques under erroneous feedback information.

Emerging Low Power Wide Area Networks (LPWAN) represent a real breakthrough for monitoring applications, since they give the possibility to generate and transmit data over dozens of kilometers while consuming few energy. To further increase the autonomy of such wireless systems, the present paper proposes an original methodology to correctly dimension the key elements of an energy autonomous node, namely, the supercapacitor and the battery that mainly give the form factor of the node. Among the LPWAN candidates, LoRa is chosen for real field experiments with a custom wireless platform that proves its energy neutrality over a finite horizon. Different LoRa configurations are explored, leading to adequate dimensioning. As an example, it is shown that, for the same quality of service, the size of the solar panel needed to keep a LoRa node autonomous in the South of France is less than half of the size required in North of France.

In this paper, we propose an imperfect quantized feedback-based diagonal precoding scheme for generalized orthogonal space-time block codes in an N × 1 multiple-input single-output (MISO) wireless communication system employing M-QAM constellation. It is well known that a feedback-based precoding scheme aids channel adaptive signaling in wireless communication system and capitulates large improvements in almost all performance metrics. However, a practical feedback link is susceptible to error due to wireless channel fading and leads to wrong precoder selection. Therefore, a signal-to-noise ratio (SNR) adaptive error-tolerant weighting scheme is introduced which provides significant gain in comparison with another proposed arbitrarily fixed SNR error-tolerant weighting scheme. At first, a tight approximate closed-form expression of average symbol-error-rate (SER) and an exact analytical expression of outage probability are derived under imperfect feedback information with the help of order statistics. By minimizing the derived average SER, optimized transmit weights for the diagonal precoding matrix (based on feedback bits) are obtained. Later, a closed-form expression of the ergodic capacity with erroneous feedback bits for arbitrary MISO system is also provided by using the moment generating function approach. Further, numerical results show that the considered error-tolerant schemes outperform the uniform power allocation scheme in term of all the investigated performance metrics.

The linear closed-loop MIMO precoding technique employs the channel state information (CSI) at both sides of the link to optimize various criteria such as the capacity, the mean square error, the signal to noise ratio (SNR), etc. Besides classical criteria such as capacity or bit error rate, the diversity-multiplexing trade-off (DMT) is now widely used to evaluate the performance of designed precoders. Indeed, it is known that a fundamental tradeoff between the spatial multiplexing and the diversity order exists. The first definition was given for asymptotic SNR, then was extended to finite values. The DMT was studied for open-loop scheme (Alamouti or V-BLAST) and we propose in this paper a method to obtain DMT of multi-form MIMO precoders. Although several multi-form solutions were found, to obtain their theoretical performance is still difficult. In order to tackle this challenge, we propose to investigate the minimal distance approach: starting from the probability density function of a square minimum distance, we obtain the outage probability and diversity-multiplexing trade-off (DMT) at operational SNR. We arbitrarily choose the max-dminprecoder based on the maximization of a minimal distance using the CSI at the transmitter (closed-loop). This expression is validated by simulations and comparisons between different MIMO precoding schemes are performed. The method can be applied to others precoders and fading channels.

In wireless networks, the cooperative diversity is an implicit form of space diversity commonly used when other conventional transmit diversity methods might not be practical. It was largely proved that cooperative transmission, where a source and a relay cooperate to communicate with a unique destination, is power‐efficient compared to the point‐to‐point transmission. However, the model considered when stating this conclusion is counting only the transmission power consumption. In this study, the authors study the effect of taking into account not only the transmission power at each transmission node but also the processing power consumed in each reception node on the overall end‐to‐end performance. They formulate the optimisation problem aiming to minimise the total power consumption in order to achieve a target performance constraint, where the total power consumption stands for the sum of the transmission power and the processing power consumed in the decoding (neglecting other forms of power consumption). The authors' analysis relies on the characterisation of an information‐theoretic bound on the decoding power of any modern code to achieve a specified bit error probability while operating at a certain gap from the capacity. As this bound is built on the sphere‐packing analysis, this study focuses on message‐passing decoders. Using this theoretical framework, the improvement of well‐known cooperative protocols over the original non‐cooperative point‐to‐point system system is reinvestigated in terms of total power consumption. Thanks to this theoretical framework, a new classification of the studied cooperative protocols is given revealing some surprising conclusions. In particular, the selective decode‐and‐forward protocol is no more constantly preferred to its simpler alternative, i.e. the decode‐and‐forward protocol.

The linear closed-loop MIMO precoding technique employs the channel state information at both sides of the link to optimize various criteria such as the capacity, the mean square error, the mutual information. However, the cost is generally an increased complexity and the theoretical study of such a system can be difficult, i.e. obtain criteria such as the Bit Error Rate or Logarithm of Likelihood Ratio (LLR). Some studies are available for diagonal form precoders, but it is often difficult to deal with a precoder that chooses between different forms to adapt to the channel state, as in the case for the max-dmin precoder. In this paper, we propose a new approximation of the mutual information (MI) which is expressed as a function of the minimal distance. Indeed, our recent works permit us to obtain the probability density function of the minimal distance, and, this is the main point, to deal with the multi-forms. The MI can then be averaged over the statistics of the channel and the result is available for any MIMO system and any modulation size for the example of max-dmin.

In this paper, we study the effect of optimal power allocation on the performance of communication systems using hybrid-automatic repeat request (HARQ) protocols with a limited maximum number of transmission rounds. We formulate the optimization problem aiming to minimize the total average power consumption in order to achieve a target performance constraint, where the total power consumption stands for the sum of the transmission power and the processing power consumed in the decoding. Our analysis relies on the characterization of an information-theoretic bound on the decoding power of any modern code to achieve a specified bit error probability while operating at a certain gap from the capacity. As this bound is built on the sphere-packing analysis, the present study focuses on message-passing decoders. We find that the implementation of power-adaptive HARQ reduces the total average power consumption even when taking decoding power into consideration, compared with reference systems.

Linear closed-loop MIMO precoders are attractive owing to their scalability. They can significantly improve the received signal via optimization of pertinent criterion. The solution of max-dminprecoding is optimal for 4-QAM as it utilizes the channel state information at the transmitter (CSIT) to minimize the system error probability making it very attractive. However, as M increases the solution which is dependent on channel angle gets complex, due to its multi-form precoder search. Motivated by a requirement to provide MIMO system evaluation parameters to upper layer protocol(s) as a function of precoder optimization criterion, we propose deriving a general expression for the probability density function (pdf) of max-dmin. Our approach applies numerical approximations to derive the system bit error rate (BER) and ergodic capacity for any values of M, nr, and nt, and with b = 2 data streams. Results show that the performance of our numerical approximation approach is close to the analytical simulation method.

Multiple-input, Multiple-output (MIMO) techniques have proven their potentiality for transmissions in the public transport domain even in specific propagation context such as tunnels. When perfect channel state information (CSI) is available at the transmitter, performance improvement is allowed through a precoding operation. However, the performances of a such closed-loop MIMO system depend on the spatial correlation of the channel and the available CSI. In this paper, we considered three cases: an uncorrelated MIMO Rayleigh channel and two correlated channels in tunnel (medium and high correlation). The channel matrices are obtained by computing individual complex impulse responses using ray-tracing simulations with realistic geometric configurations of antennas in a one-way tunnel. The channel is then modelized thanks to the well-known Kronecker model. Therefore, we compared two recent precoders (max-dmin and P-OSM) based on the minimal Euclidean distance criterion. We demonstrated the full diversity of P-OSM and simulated the BER.

A precoder based on the exact optimization of the minimum Euclidean distance dminbetween signal points at the receiver side is proposed for MIMO-OFDM systems using a 16-QAM modulation. Assuming that channel state information (CSI) can be made available at the transmitter, the channel is diagonalized and a precoder can be derived. A numerical approach shows that the precoder design depends on the channel characteristics, leading to 8 different precoder expressions. Comparisons with maximum signal-to-noise ratio (SNR) strategy and other precoders based on criteria, such as water-filling (WF), minimum mean square error (MMSE), and maximization of the minimum singular value of the global channel matrix, are performed to illustrate the significant bit-error-rate (BER) improvement of the proposed precoder. In order to make its implementation easier, it is shown that it can be expressed by only two ways without significant performance degradation.