Section: New Results
Multi-User Communications
Fundamental limits : contributions in Multi-User Information Theory (MU-IT)
Interference channel with feedback
In this work [29], [44], [43], the
Simultaneous information and energy transmission
In this work [42], [25], [48], the fundamental limits of simultaneous information and energy transmission in the two-user Gaussian interference channel (G-IC) with and without feedback are fully characterized. More specifically, an achievable and converse region in terms of information and energy transmission rates (in bits per channel use and energy-units per channel use, respectively) are identified. In both cases, with and without feedback, an achievability scheme based on power-splitting, common randomness, rate splitting, block-Markov superposition coding, and backward decoding is presented. Finally, converse regions for both cases are obtained using some of the existing outer bounds for information transmission rates, as well as a new outer bound for the energy transmission rate.
Ultra-dense wireless networks
Ultra-dense networks represent an interesting model for future IoT networks. The analysis of these metworks relies on the association of stochastic geometry models with information theory in the finite blocklength regime. Considering an isolated wireless cell containing a high density of nodes, the fundamental limit can be defined as the maximal number of nodes the associate base station can serve under some system level constraints including maximal rate, reliability, latency and transmission power. This limit can be investigated in the downlink, modeled as a spatial continuum broadast channel (SCBC) as well as in the uplink modeled as a spatial continuum multiple access channel (SCMAC). In this work, we define the different steps towards the characterization of this fundamental limit, considering four figures of merit: energy efficiency, spectral efficiency, latency, reliabilty [13].
To address this question in the uplink scenario [10], we uses a large scale Multiple Access Channel (MAC) to model IoT nodes randomly distributed over the coverage area of a unique base station. The traffic is represented by an information rate spatial density
Broadcast channel in the Finite Blocklength regime
In order to analyse wireless networks with short packets, theoretical results in information theory for the finite blocklength regime in multi-user scenarios were missin. In [34], [33], we analyzed the performance of superposition coding for Gaussian broadcast channels with finite blocklength. To this end, we adapted two different achievability bounds, the dependence testing and the
Capacity sensitivity
In this work [22], [40], a new framework based on the notion of capacity sensitivity is introduced to study the capacity of continuous memoryless point-to-point channels. The capacity sensitivity reflects how the capacity changes with small perturbations in any of the parameters describing the channel, even when the capacity is not available in closed-form. This includes perturbations of the cost constraints on the input distribution as well as on the channel distribution. The framework is based on continuity of the capacity, which is shown for a class of perturbations in the cost constraint and the channel distribution. The continuity then forms the foundation for obtaining bounds on the capacity sensitivity. As an illustration, the capacity sensitivity bound is applied to obtain scaling laws when the support of additive
Performance evaluation of large scale systems
UNB networks performance evaluation
UNB (Ultra Narrow Band) stands out as one promising PHY solution for low-power, low-throughput and long-range IoT. The dedicated MAC scheme is RFTMA (Random Frequency and Time Multiple Access), where nodes access the channel randomly both in frequency and in time domain, without prior channel sensing. This blind randomness sometimes introduces interference and packet losses. In order to quantify the system performance, we have derived and exploited a theoretical expression of the outage probability in a UNB based IoT network, when taking into account both interference due to the spectral randomness and path loss due to the propagation [14], [5]. Besides, we also proposed to use the well-known SIC (Successive Interference Cancellation) to cancel the interference in a recursive way. We provided a theoretical analysis of network performance, when considering jointly SIC and the specific spectral randomness of UNB. We analytically and numerically highlighted the SIC efficiency in enhancing UNB system performance [26].
Wireless networks on FIT/CorteXlab
In this work we study the FIT/CorteXlab platform where all radio nodes are confined to an electromagnetically (EM) shielded environment and have flexible radio-frequency (RF) front-end for experimenting on software defined radio (SDR) and cognitive radio (CR). A unique feature of this testbed is that it offers roughly 40 SDR nodes that can be accessed from anywhere in the world in a reproducible manner: the electromagnetic shield prevents from external interference and channel variability. In this work [16] we show why it is important to have such a reproducible radio experiment testbed and we highlight the reproducibility by the channel characteristics between the nodes of the platform. We back our claims with a large set of measurements done in the testbed, that also refines our knowledge on the propagation characteristics of the testbed.
One of the major goals of the 5G technology roadmap is to create disruptive innovation for the efficient use of the radio spectrum to enable rapid access to bandwidth-intensive multimedia services over wireless networks. The biggest challenge toward this goal lies in the difficulty in exploiting the multicast nature of the wireless channel in the presence of wireless users that rarely access the same content at the same time. Recently, the combined use of wireless edge caching and coded multicasting has been shown to be a promising approach to simultaneously serve multiple unicast demands via coded multicast transmissions, leading to order-of-magnitude bandwidth efficiency gains. However, a crucial open question is how these theoretically proven throughput gains translate in the context of a practical implementation that accounts for all the required coding and protocol overheads. In [3], in collaboration with Nokia Bell Labs, New Jersey, we first provide an overview of the emerging caching- aided coded multicast technique, including state-of-the-art schemes and their theoretical performance. We then focus on the most competitive scheme proposed to date and describe a fully working prototype implementation in CorteXlab, one of the few experimental facilities where wireless multiuser communication scenarios can be evaluated in a reproducible environment. We use our prototype implementation to evaluate the experimental performance of state-of-the-art caching-aided coded multicast schemes compared to state-of-the-art uncoded schemes, with special focus on the impact of coding computation and communication overhead on the overall bandwidth efficiency performance. Our experimental results show that coding overhead does not significantly affect the promising performance gains of coded multicasting in small-scale realworld scenarios, practically validating its potential to become a key next generation 5G technology.
Cognitive networks
Game theory based approaches
In [4], a generalization of the satisfaction equilibrium (SE) for games in satisfaction form (SF) is presented. This new solution concept is referred to as the generalized satisfaction equilibrium (GSE). In games in SF, players choose their actions to satisfy an individual constraint that depends on the actions of all the others. At a GSE, players that are unsatisfied are unable to unilaterally deviate to be satisfied. The concept of GSE generalizes the SE in the sense that it allows mixed-strategy equilibria in which there exist players who are unable to satisfy their individual constraints. The pure-strategy GSE problem is closely related to the constraint satisfaction problem and finding a pure-strategy GSE is proven to be NP-hard. The existence of at least one GSE in mixed strategies is proven for the class of games in which the constraints are defined by a lower limit on the expected utility. A dynamics referred to as the satisfaction response is shown to converge to a GSE in certain classes of games. Finally, Bayesian games in SF and the corresponding Bayesian GSE are introduced. These results provide a theoretical framework for studying service-level provisioning problems in communications networks as shown by several examples.
Device-to-device (D2D) communications can enhance spectrum and energy efficiency due to direct proximity communication and frequency reuse. However, such performance enhancement is limited by mutual interference and energy availability, especially when the deployment of D2D links is ultra-dense. In this contribution [9], we present a distributed power control method for ultra-dense D2D communications underlaying cellular communications. In this power control method, in addition to the remaining battery energy of the D2D transmitter, we consider the effects of both the interference caused by the generic D2D transmitter to others and interference from all others' caused to the generic D2D receiver. We formulate a mean-field game (MFG) theoretic framework with the interference mean-field approximation. We design the cost function combining both the performance of the D2D communication and cost for transmit power at the D2D transmitter. Within the MFG framework, we derive the related Hamilton-Jacobi-Bellman (HJB) and Fokker-Planck-Kolmogorov (FPK) equations. Then, a novel energy and interference aware power control policy is proposed, which is based on the Lax-Friedrichs scheme and the Lagrange relaxation. The numerical results are presented to demonstrate the spectrum and energy efficiency performances of our proposed approach. Index Terms—Device-to-device communication, mean field game, spectrum efficiency, energy efficiency.
Learning approaches
Fast initialization of cognitive radio systems is a key problem in a variety of wireless communication systems, particularly for public safety organizations in emergency crises. In the initialization problem, the goal is to rapidly identify an unoccupied frequency band. In this contribution [21], we formalize the initialization problem within the framework of active hypothesis testing. We characterize the optimal scanning policy in the case of at most one free band and show that the policy is computationally challenging. Motivated by this challenge for the implementation of the optimal policy and the need to cope with an unknown number of interferers larger than one, we propose the constrained DGF algorithm. We show that for strict constraints on the maximum number of observations, the constrained DGF algorithm can outperform the error probability of the state-of-the-art C-SPRT algorithm by an order of magnitude, for comparable average delays.
Asynchronous transmissions in VLC
In a visible light communications system (VLC), light sources are responsible for both illumination, communications and positioning. These light sources inevitably interfere each others at the receiver. To retain the appealing advantage that VLC systems can reuse existing lighting infrastructure, using an extra network to control or synchronize the light sources should be avoided. This work [31] proposes an uncoordinated multiple access scheme for VLC systems with positioning capability. The proposed scheme does not require a central unit to coordinate the transmission of the transmitters. Transmitters can be asynchronous with one another and with the receiver. Each transmitter is allocated a unique codeword with L chips for a system with up to
Contributions in other application fields
Smart Grids
The advanced operation of future electricity distribution systems is likely to require significant observability of the different parameters of interest (e.g., demand, voltages, currents, etc.). Ensuring completeness of data is, therefore, paramount. In this context, an algorithm for recovering missing state variable observations in electricity distribution systems is presented in [47]. The proposed method exploits the low rank structure of the state variables via a matrix completion approach while incorporating prior knowledge in the form of second order statistics. Specifically , the recovery method combines nuclear norm minimization with Bayesian estimation. The performance of the new algorithm is compared to the information-theoretic limits and tested trough simulations using real data of an urban low voltage distribution system. The impact of the prior knowledge is analyzed when a mismatched covariance is used and for a Markovian sampling that introduces structure in the observation pattern. Numerical results demonstrate that the proposed algorithm is robust and outperforms existing state of the art algorithms.
In addition, Gaussian random attacks that jointly minimize the amount of information obtained by the operator from the grid and the probability of attack detection are presented in [38]. The construction of the attack is posed as an optimization problem with a utility function that captures two effects: firstly, minimizing the mutual information between the measurements and the state variables; secondly, minimizing the probability of attack detection via the Kullback-Leibler (KL) divergence between the distribution of the measurements with an attack and the distribution of the measurements without an attack. Additionally, a lower bound on the utility function achieved by the attacks constructed with imperfect knowledge of the second order statistics of the state variables is obtained. The performance of the attack construction using the sample covariance matrix of the state variables is numerically evaluated. The above results are tested in the IEEE
Molecular Communications
Molecular communications is emerging as a technique to support coordination in nanonetworking, particularly in biochemical systems. In complex biochemical systems such as in the human body, it is not always possible to view the molecular communication link in isolation as chemicals in the system may react with chemicals used for the purpose of communication. There are two consequences: either the performance of the molecular communication link is reduced; or the molecular link disrupts the function of the biochemical system. As such, it is important to establish conditions when the molecular communication link can coexist with a biochemical system. In this work [45], we develop a framework to establish coexistence conditions based on the theory of chemical reaction networks. We then specialize our framework in two settings: an enzyme-aided molecular communication system; and a low-rate molecular communication system near a general biochemical system. In each case, we prove sufficient conditions to ensure coexistence.