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Non-Orthogonal Multiple Access (NOMA) is a Resource Sharing Mechanism (RSM) initially studied for 5G cellular networks and brought back to the agenda for 6G networks. While NOMA’s benefit at the level of a single cell has been properly established, assessing its performance at the scale of a cellular network remains an open research problem. This is mainly due to the inter-dependencies between scheduling, power control and inter-cell interference. Some algorithms have been proposed to optimize resource allocation in a multi-cell network, but they require a perfect and unrealistic knowledge of the whole channel states. In this paper, we leverage Bayesian Optimization techniques to build a versatile evaluation framework, able to assess the performance of multi-cell networks implementing a large variety of RSMs under a minimal set of assumptions. Subsequently, we illustrate how this evaluation framework can be used to compare the performance of several well-known RSMs under various fairness requirements and beamforming efficiencies. Our results show that, among the RSMs studied on a simple multi-cell network simulation, NOMA combined with a full reuse policy consistently emerges as the one able to achieve the highest end-users achievable rates under fairness constraints.

Federated learning (FL) is now recognized as a key framework for communication-efficient collaborative learning. Most theoretical and empirical studies, however, rely on the assumption that clients have access to pre-collected data sets, with limited investigation into scenarios where clients continuously collect data. In many real-world applications, particularly when data is generated by physical or biological processes, client data streams are often modeled by non-stationary Markov processes. Unlike standard i.i.d. sampling, the performance of FL with Markovian data streams remains poorly understood due to the statistical dependencies between client samples over time. In this paper, we investigate whether FL can still support collaborative learning with Markovian data streams. Specifically, we analyze the performance of Minibatch SGD, Local SGD, and a variant of Local SGD with momentum. We answer affirmatively under standard assumptions and smooth non-convex client objectives: the sample complexity is proportional to the inverse of the number of clients with a communication complexity comparable to the i.i.d. scenario. However, the sample complexity for Markovian data streams remains higher than for i.i.d. sampling. Our analysis is validated via experiments with real pollution monitoring time series data.

A standard assumption in the design of ultra-reliable low-latency communication systems is that the duration between message arrivals is larger than the number of channel uses before the decoding deadline. Nevertheless, this assumption fails when messages arrive rapidly and reliability constraints require that the number of channel uses exceed the time between arrivals. In this paper, we consider a broadcast setting in which a transmitter wishes to send two different messages to two receivers over Gaussian channels. Messages have different arrival times and decoding deadlines such that their transmission windows overlap. For this setting, we propose a coding scheme that exploits Marton’s coding strategy. We derive rigorous bounds on the achievable rate regions. Those bounds can be easily employed in point-to-point settings with one or multiple parallel channels. In the point-to-point setting with one or multiple parallel channels, the proposed achievability scheme is consistent with the normal approximation. In the broadcast setting, our scheme agrees with Marton’s strategy for sufficiently large numbers of channel uses and shows significant performance improvements over standard approaches based on time sharing for transmission of short packets.

This paper proposes coding schemes and information-theoretic converse results for the transmission of heterogeneous delay-constrained traffic over interference networks with random user activity and random data arrivals. The heterogeneous delay-constrained traffic is composed of delay-tolerant traffic and delay-sensitive traffic where only the former can benefit from transmitter and receiver cooperation since the latter is subject to stringent delay constraints. Even for the delay-tolerant traffic, the total number of cooperation rounds at transmitter and receiver sides is limited to D rounds. Each transmitter is assumed to be active with probability$\rho \in [{0,1}]$, and we study two different models for traffic arrival, each model reflecting a different application type. In Model 1, each active transmitter sends a delay-tolerant message, and with probability$\rho _{f} \in [{0,1}]$also transmits an additional delay-sensitive message; in Model 2, each active transmitter sends either a delay-sensitive message with probability$\rho _{f}$or a delay-tolerant message with probability$1- \rho _{f}$. For both models, we derive inner and outer bounds on the fundamental per-user multiplexing gain (MG) region of the symmetric Wyner network as well as inner bounds on the fundamental MG region of the hexagonal model. The per-user MG of an interference network describes the logarithmic growth of the largest average per-user rate that can be achieved over the network at high signal-to-noise ratios (SNR). Our inner and outer bounds on the per-user MG are generally close and coincide in special cases. They also show that when both transmitters and receivers can cooperate, then under Model 1, transmitting delay-sensitive messages hardly causes any penalty on the sum per-user MG, and under Model 2, operating at large delay-sensitive per-user MGs incurs no penalty on the delay-tolerant per-user MG and thus even increases the sum per-user MG. However, when only receivers can cooperate, the maximum delay-tolerant per-user MG that our bounds achieve at maximum delay-sensitive per-user MG is significantly decreased.

The random access procedure is a bottleneck to the development of wireless networks supporting the use cases of massive machine-type communication and ultra reliable and low-latency communication. Such networks are densely and massively popupated and must meet stringent latency and reliability requirements. Due to these characteristics, grant-free random access is envisioned to alleviate the control overhead generated by the classical random access procedure. However, active user detection and channel estimation algorithms are required. Existing algorithms assume that the activity of each device is homogeneous and independent, which is not the case in many applications (e.g., due to sensors observing a common phenomenon). In order to address this problem, we introduce a new flexible model taking into account a group-heterogeneous activity, using the framework of copula theory. It is then leveraged by a hybrid generalized approximate message passing algorithm to solve the active user detection and channel estimation problem. Our numerical results show that the user detection and channel estimation are both improved with this new algorithm w.r.t. state-of-the-art Bayesian algorithms, with gains up to 10 times fewer detection errors and 10 dB less channel estimation error.

We propose a framework for maximizing the number of machine-type devices connected in the uplink of a Narrow-band Internet of Things (NB-IoT) network using non-orthogonal multiple access (NOMA). The system is based on the fast-uplink grant (FUG), where the base station (BS) schedules the access for active devices requesting connection. This problem is a mixed-integer non-convex problem and real-time solutions using general solvers are computationally prohibitive. The proposed scheduling solution comprises efficient device clustering and optimum power allocation using a bipartite graph matching approach, termed connection throughput maximizing full matching with pruning (CTMBM). Different from the other solutions of state-of-the-art, our proposed scheme considers scheduling over multiple transmission time intervals while considering the transmission deadlines and quality of service (QoS) for the devices. Additionally, we provide a method for priority scheduling of a subset of devices. We compare our solution to the state-of-the-art schemes and analyze the achieved gains through Monte-Carlo computer simulations.

In predictive maintenance an important problem is to optimize the quantity of information to be transmitted at the control center to guarantee reliable fault detection while limiting sensor power consumption. This problem relies directly on the sensor configurations (e.g., sampling rate, coding, quantization) and the fault detection algorithm. To address this question, we introduce a codesign framework and an algorithm for joint optimization of the sensor configurations and the accuracy of the fault detection classifier. In a use case based on a dataset consisting of multiple sensor measurements and heating power levels known as the Twin House Experiment, we show that our algorithm can find efficient tradeoffs between sensor power consumption and classifier accuracy.

Industrial IoT (IIoT) is one of the major verticals targeted by the next generations of wireless networks. In order to provide industrial plants with features relying on wireless communications, the grant-free RA (GFRA) protocol appears to be a promising means for supporting massive ultra-reliable connectivity; at the same time, it is a critical bottleneck that requires an access point (AP) to be able to jointly perform active user detection and channel estimation (AUDaCE) to fulfill its main mission of allowing industrial wireless devices to access the core network. This mission is even harder when the GFRA requests are correlated because of event-driven activity triggers. This paper proposes a new tractable gaussian correlated activity (GCA) model for this scenario. The corresponding AUDaCE problem is then studied in the Bayesian compressed sensing (BCS) framework. An hybrid instance of the generalized AMP (GAMP) algorithm is derived and its capability to perform AUDaCE is numerically assessed by extensive Monte-Carlo simulations. The numerical results show gains of 2.5dB in channel estimation gain for twice less detection errors w.r.t. state-of-the-art algorithms.

In grant-free random access, a key question is how devices should utilize resources without coordination. One standard solution to this problem are strategies where devices randomly select time-slots based on an optimized stochastic allocation rule. However, the optimization of this allocation rule requires accurate knowledge of which devices have been active in previous frames. As user identification algorithms are subject to errors, the expected throughput of the optimized allocation can be highly suboptimal. In this paper, we propose algorithms for optimization of device time-slot allocations that mitigate the impact of user identification errors. We show that when the activity distribution with and without errors is known, then our algorithm converges with probability one to a stationary point. When the activity distributions are not available, we introduce new theoretically-motivated heuristics which significantly improve the expected throughput over existing algorithms and approach the performance when errors are not present.

With the proliferation of cheap sensors and the ubiquity of cloud and edge computing, predictive/condition-based maintenance is expected to play an important role in smart homes and buildings. Nevertheless, a key difficulty is ensuring that sensors provide data of sufficient quality in order to reliably detect building (e.g., heating system) degradation in systems or comfort. At the same time, sensor utilization should be limited as much as possible in order to minimize power consumption, and increase the lifetimes of batteries. A solution to this problem requires careful codesign of sensor communication and data analytics. In this article, we introduce a formulation of this codesign problem, which is based on an optimization problem to jointly design how often data is collected and compression levels in order to balance the quality of fault detection with the quantity of transmitted data. To solve the optimization problem, we apply a differentiable search algorithm based on a variant of stochastic gradient descent for discrete optimization problems. We apply our codesign framework and solve the resulting optimization problem using data obtained from a building comfort experiment known as the Twin House Experiment. We also provide an extension of our algorithm to a dynamic variant of the codesign framework, where comfort levels and power consumption penalties are time varying. Numerical results show that our algorithm rapidly finds an efficient tradeoff between classifier accuracy and sensor power consumption.

Wyner's soft-handoff network is considered where transmitters simultaneously send messages of enhanced mobile broadband (eMBB) and ultra-reliable low-latency communication (URLLC) services. Due to the low-latency requirements, the URLLC messages are transmitted over fewer channel uses compared to the eMBB messages. To improve the reliability of the URLLC transmissions, we propose a coding scheme with finite blocklength codewords that exploits dirty-paper coding (DPC) to precancel the interference from eMBB transmissions. Rigorous bounds are derived for the error probabilities of eMBB and URLLC transmissions achieved by our scheme. Numerical results illustrate that they are lower than for standard time-sharing.

To improve reliability in latency-critical applications, a point-to-point communication system with heterogeneous decoding deadlines is considered. Unlike existing work, this system allows for a message to arrive before the decoding deadline of a prior message. A new coding scheme with finite blocklength codewords is introduced exploiting the dirty paper coding principle. Rigorous bounds are derived for achievable error probabilities. Moreover, numerical results illustrate that the proposed scheme outperforms time sharing for a wide range of blocklengths.

We develop a framework for maximizing the number of transmitted packets for devices in a Narrowband Internet of Things (NB-IoT) network using non-orthogonal multiple access (NOMA) in the downlink. The base station (BS) chooses one of the multiple available physical resource blocks (PRBs) that are well separated in frequency for a device, giving them the advantage of exploiting frequency diversity. The scheduling strategy focuses on the two-fold problem involving efficient device clustering and optimum power allocation. This problem is a mixed-integer non-convex problem. We propose a bipartite graph matching approach, termed minimum weight full matching with pruning (MWFMP), to address the problem over multiple PRBs and solve it under the quality-of-service (QoS), allowable PRB, power budget, and interference constraints. Additionally, we provide a comparison with a greedy heuristic, the multi-PRB stratified device allocation (MPSDA), where we extend our previous work for a single PRB connectivity problem. Furthermore, we compare our algorithms to orthogonal multiple access (OMA) scheduling, which is prevalent in legacy LTE networks. We show that our algorithms steadily outperform the connectivity performance offered by OMA.

In this paper, we apply an multi-agent reinforcement learning (MARL) framework allowing the base station (BS) and the user equipments (UEs) to jointly learn a channel access policy and its signaling in a wireless multiple access scenario. In this framework, the BS and UEs are reinforcement learning (RL) agents that need to cooperate in order to deliver data. The comparison with a contention-free and a contention-based baselines shows that our framework achieves a superior performance in terms of goodput even in high traffic situations while maintaining a low collision rate. The scalability of the proposed method is studied, since it is a major problem in MARL and this paper provides the first results in order to address it.

Impulsive noise, where large amplitudes arise with a relatively high probability, arises in many communication systems including interference in Low Power Wide Area Networks. A challenge in coping with impulsive noise, particularly alpha-stable models, is that tractable expressions for the log-likelihood ratio (LLR) are not available, which has a large impact on soft-input decoding schemes, e.g., low-density parity-check (LDPC) packets. On the other hand, constraints on packet length also mean that pilot signals are not available resulting in non-trivial approximation and parameter estimation problems for the LLR. In this paper, a new unsupervised parameter estimation algorithm is proposed for LLR approximation. In terms of the frame error rate (FER), this algorithm is shown to significantly outperform existing unsupervised estimation methods for short LDPC packets (on the order of 500 symbols), with nearly the same performance as when the parameters are perfectly known. The performance is also compared with an upper bound on the information-theoretic limit for the FER, which suggests that in impulsive noise further improvements require the use of an alternative code structure other than LDPC.

A standard assumption in the design of ultra-reliable low-latency communication systems is that the duration between message arrivals is larger than the number of channel uses before the decoding deadline. Nevertheless, this assumption fails when messages rapidly arrive and reliability constraints require that the number of channel uses exceeds the time between arrivals. In this paper, we study channel coding in this setting by jointly encoding messages as they arrive while decoding the messages separately, allowing for heterogeneous decoding deadlines. For a scheme based on power sharing, we analyze the probability of error in the finite blocklength regime. We show that significant performance improvements can be obtained for short packets by using our scheme instead of standard approaches based on time sharing.

In this paper, we investigate the impact of side information (SI) on the performance of physical layer security (PLS) under correlated fading channels. By considering non-causally known SI at the transmitter and exploiting the copula technique to describe the fading correlation, we derive closed-from expressions for the average secrecy capacity (ASC) and secrecy outage probability (SOP) under positive/negative dependence conditions. We indicate that considering such knowledge at the transmitter is beneficial for system performance and ensures reliable communication with higher rates, as it improves the SOP and brings higher values of the ASC.

In this paper, a real-valued function that approximates the cumulative distribution function (CDF) of a finite sum of real-valued independent and identically distributed random vectors is presented. The approximation error is upper bounded by an expression that is easy to calculate. As a byproduct, an upper bound and a lower bound on the CDF are obtained. Finally, in the case of lattice and absolutely continuous random variables, the proposed approximation is shown to be identical to the saddlepoint approximation of the CDF.

This paper analyses the multiplexing gain (MG) achievable over Wyner’s symmetric network with random user activity and random arrival of mixed-delay traffic. The mixed-delay traffic is composed of delay-tolerant traffic and delay-sensitive traffic where only the former can benefit from transmitter and receiver cooperation since the latter is subject to stringent decoding delays. The total number of cooperation rounds at transmitter and receiver sides is limited to D rounds. We derive inner and outer bounds on the MG region. In the limit as D$\rightarrow\infty$, the bounds coincide and the results show that transmitting delaysensitive messages does not cause any penalty on the sum MG. For finite D our bounds are still close and prove that the penalty caused by delay-sensitive transmissions is small.

Machine learning (ML) starts to be widely used to enhance the performance of multi-user multiple-input multiple-output (MU-MIMO) receivers. However, it is still unclear if such methods are truly competitive with respect to conventional methods in realistic scenarios and under practical constraints. In addition to enabling accurate signal reconstruction on realistic channel models, MU-MIMO receive algorithms must allow for easy adaptation to a varying number of users without the need for retraining. In contrast to existing work, we propose an machine learning (ML)-enhanced MU-MIMO receiver that builds on top of a conventional linear minimum mean squared error (LMMSE) architecture. It preserves the interpretability and scalability of the LMMSE receiver, while improving its accuracy in two ways. First, convolutional neural networks (CNNs) are used to compute an approximation of the second-order statistics of the channel estimation error which are required for accurate equalization. Second, a CNN-based demapper jointly processes a large number of orthogonal frequency-division multiplexing (OFDM) symbols and subcarriers, which allows it to compute better log likelihood ratios (LLRs) by compensating for channel aging. The resulting architecture can be used in the up- and downlink and is trained in an end-to-end manner, removing the need for hard-to-get perfect channel state information (CSI) during the training phase. Simulation results demonstrate consistent performance improvements over the baseline which are especially pronounced in high mobility scenarios.

This paper introduces an upper-bound on the absolute difference between: (a) the cumulative distribution function (c.d. f.) of the sum of a finite number of independent and identically distributed (i.i.d) random variables; and (b) a saddlepoint approximation of such c.d.f. This upperbound is general and particularly precise in the regime of large deviations. This result is used to study the dependence testing (DT) bound on the minimum decoding error probability (DEP) in memoryless channels. Within this context, the main results include new lower and upper bounds on the DT bound. As a byproduct, an upper bound on the absolute difference between the exact value of the DT bound and its saddlepoint approximation is obtained. Numerical analysis of these bounds are presented for the case of the binary symmetric channel and the additive white Gaussian noise channel, in which the new bounds are observed to be tight.

Recently, there has been a proliferation of wireless communication technologies in unlicensed bands for the Internet of Things. A key question is whether these networks can coexist given that they have different power levels, symbol periods, and access protocols. The main challenge is to characterize the impact of mutual interference arising from distinct uncoordinated networks. It is known that when interferers form a homogeneous Poisson point process and transmit only on a single subband, the interference is often well-modeled by the heavy-tailed α-stable distribution. In this paper, we focus on the scenario where interferers transmit on multiple subbands. Under a policy where each interferer independently accesses each band with probability p, we provide an exact characterization of the interference random vector. Exploiting this characterization, we derive optimal linear combining weights and an analytical approximation for the bit error rate (BER), accurate for large transmit power. A key observation is that the expression for the BER admits an interpretation in terms of an array gain and a fractional diversity gain.

As the Internet of Things (IoT) is largely supported by wireless communication networks in unlicensed bands, there has been a proliferation of technologies that use a large variety of protocols. An ongoing challenge is how these networks can coexist given that they have different power levels, symbol periods, and access protocols. In this paper, we study the statistics of interference due to IoT networks that transmit small amounts of data. A key observation is that sets of active devices change rapidly, which leads to impulsive noise channels. Moreover, these devices operate on multiple partially overlapping resource blocks. As such, we characterize the joint distribution and propose a tractable model based on copulas. Using our copula model, we derive closed-form achievable rates. This provides a basis for resource allocation and network design for coexisting IoT networks.

Despite the huge number of contributions dealing with the evaluation of cellular networks performance, tackling with more and more complex systems including multi-tier networks or MIMO systems, the fundamental limits in terms of capacity in an information theory sense is not known for these networks. Stochastic geometry helped doing a step forward, relying on Palm theory and providing coverage statistic at the network scale. However, this statistic is not sufficient to establish a fundamental limit, namely to characterise a Shannon capacity region of the network. In this paper, we propose a new approach exploiting the cell capacity of the Spatial Continuum Broadcast Channel (SCBC) recently introduced for an isolated cell. The network capacity is linked to the cells' geometry statistics in a Voronoi tessellation. The fundamental limit is characterised by the minimal average cell power required in a network modelled as a Point Process (PP) to achieve a desired rate distribution. A direct relation is established between this minimum average power and the partial area statistics of the cells geometry, which constitute a sufficient statistic. Our approach is validated through Monte-Carlo simulations.

UNB (Ultra Narrow Band) is one of the technologies dedicated to low-power wide-area communication for IoT, currently exploited by SigFox. The specificity of UNB is the Aloha-type channel access scheme, both asynchronized in time and frequency domain. This randomness can cause partial spectral interference. In this paper, we take advantage of the spatial diversity of multiple base stations to improve the UNB performance, by using selection combining. In the presence of pathloss and spectral randomness of UNB, the channels are considered correlated. A theoretical analysis of outage probability is demonstrated by considering this correlation, for the case of 2 base stations. This methodology of probability computing can be extended to general K BSs. The diversity of multiple receivers is proved to be beneficial in enhancing the performance of UNB networks. This gain is shown to be related to the density of the base stations, as well as the distance between each of them.

In this paper, an achievable η-Nash equilibrium (η-NE) region for the two-user Gaussian interference channel with noisy channel-output feedback is presented for all η ≥ 1. This result is obtained in the scenario in which each transmitter-receiver pair chooses its own transmit-receive configuration in order to maximize its own individual information transmission rate. At an η-NE, any unilateral deviation by either of the pairs does not increase the corresponding individual rate by more than η bits per channel use.

In this paper, the benefits of channel-output feedback in the Gaussian interference channel (G-IC) are studied under the effect of additive Gaussian noise. Using a linear deterministic (LD) model, the signal to noise ratios (SNRs) in the feedback links beyond which feedback plays a significant role in terms of increasing the individual rates or the sum-rate are approximated. The relevance of this work lies in the fact that it identifies the feedback SNRs for which in any G-IC, one of the following statements is true: (a) feedback does not enlarge the capacity region; (b) feedback enlarges the capacity region and the sum-rate is greater than the largest sum-rate without feedback; and (c) feedback enlarges the capacity region but no significant improvement is observed in the sum-rate.

In this paper, the capacity region of the linear deterministic interference channel with noisy channel-output feedback (LD-IC-NF) is fully characterized. The proof of achievability is based on random coding arguments and rate splitting, block-Markov superposition coding, and backward decoding. The proof of the converse reuses some of the existing outer bounds and includes new ones obtained using genie-aided models. Following the insight gained from the analysis of the LD-IC-NF, an achievability region and a converse region for the two-user Gaussian interference channel with noisy channel-output feedback (G-IC-NF) are presented. Finally, the achievability region and the converse region are proven to approximate the capacity region of the G-IC-NF to within 4.4 bits.

Fast varying active transmitter sets are a key feature of wireless communication networks with very short transmissions arising in machine-to-machine communications. A consequence is that the interference is dynamic, leading to non-Gaussian statistics. In this paper, we study the behavior of large scale communication networks in the presence of isotropic α-stable interference, which forms a model for dynamic interference. We first characterize the achievable rate of each link by considering a non-Gaussian input distribution, which is shown to outperform a Gaussian input. Moreover, we analyze the area spectral efficiency, which is the total rate per square meter. Our analysis suggests that analogously to the common model of slowly varying active transmitter sets, dense networks maximize the area spectral efficiency.

In this paper, we develop a powerful analytical model of wireless network with Superposition Coding (SC), also referred to as Non Orthogonal Multiple Access (NOMA). This model allows to establish a closed form expression of the minimum power a base station need to transmit, for a user to achieve a given SINR (signal to interference plus noise ratio) whatever its location over the area covered by the base station. It moreover allows to establish a closed form expression of the minimum total transmit power of a base station. These closed form expressions allow to establish performance of wireless networks, by minimizing the base stations transmit powers. As an application, we show that these closed form expressions allow to quantify the energetic performance, spectral efficiency, total throughput and the coverage of a BS, in a simple and quick way.

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. Hence, in this paper, we propose to use the well-known SIC (Successive Interference Cancellation) to cancel the interference in a recursive way. We provide a theoretical analysis of network performance, when considering jointly SIC and the specific spectral randomness of UNB. We analytically and numerically highlight the SIC efficiency in enhancing UNB system performance.

In this paper, the η-Nash equilibrium (η-NE) region of the two-user linear deterministic interference channel (IC) with noisy channel-output feedback is characterized for all η > 0. The η-NE region, a subset of the capacity region, contains the set of all achievable information rate pairs that are stable in the sense of an η-NE. More specifically, given an η-NE coding scheme, there does not exist an alternative coding scheme for either transmitter-receiver pair that increases the individual rate by more than η bits per channel use. Existing results such as the η-NE region of the linear deterministic IC without feedback and with perfect output feedback are obtained as particular cases of the result presented in this paper.

In this paper, we analyze the performance of superposition coding for Gaussian broadcast channels with finite blocklength. To this end, we adapt two different achievability bounds, the dependence testing and the κβ bounds introduced by Polyanskiy et al. in 2010 to the broadcast setting. The distinction between these bounds lies in fixing either the input or the output distributions of the channel. For the first case of the dependence testing bound, an upper bound on the average error probability of the system is derived whereas for the latter, lower bounds on the maximal code sizes of each user are presented1.

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 paper 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 L-1/2 transmitters where L is prime. Due to the linear growth in complexity with respect to number of transmitters, our proposed scheme is feasible for systems with large numbers of transmitters. Our novel decoder can minimize the effect of additive Gaussian noise at the receiver side. Simulation results show that the proposed decoder outperforms zero-forcing decoder.

The envisioned Internet of Things (IoT) will involve a massive deployment of objects connected through wireless cells. While commercial solutions are already available, the fundamental limits of such networks in terms of node density, achievable rates or reliability are not known. To address this question, this paper 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 ρ(x). This model, referred to as the Spatial Continuum Multiple Access Channel, is defined as the asymptotic limit of a sequence of discrete MACs. The access capacity region of this channel is defined as the set of achievable information rate spatial densities achievable with vanishing transmission errors and under a sum-power constraint. Simulation results validate the model and show that this fundamental limit theoretically achievable when all nodes transmit simultaneously over an infinite time, may be reached even with a relatively small number of simultaneous transmitters (typically around 20 nodes) which gives credibility to the model. The results also highlight the potential interest of non-orthogonal transmissions for IoT uplink transmissions when compared to an ideal time sharing strategy.

This paper proposes a new model called spatial continuum asymmetric channels to study the channel capacity region of asymmetric scenarios in which either one source transmits to a spatial density of receivers or a density of transmitters transmit to a unique receiver. This approach is built upon the classical broadcast channel (BC) and multiple access channel (MAC). For the sake of consistency, the study is limited to Gaussian channels with power constraints and is restricted to the asymptotic regime (zero-error capacity). The reference scenario comprises one base station in Tx or Rx mode, a spatial random distribution of nodes (resp. in Rx or Tx mode) characterized by a probability spatial density of users u(x) where each of them requests a quantity of information with no delay constraint, thus leading to a requested rate spatial density ρ(x). This system is modeled as an ∞-user asymmetric channel (BC or MAC). To derive the fundamental limits of this model, a spatial discretization is first proposed to obtain an equivalent BC or MAC. Then, a specific sequence of discretized spaces is defined to refine infinitely the approximation. Achievability and capacity results are obtained in the limit of this sequence while the access capacity region DΩ(Pm) is defined as the set of requested rates spatial densities ρ(x) that are achievable with a transmission power Pm. The uniform capacity defined as the maximal symmetric achievable rate is also computed.

In this paper, an achievability region and a converse region for the two-user Gaussian interference channel with noisy channel-output feedback (G-IC-NOF) are presented. The achievability region is obtained using a random coding argument and three well-known techniques: rate splitting, superposition coding and backward decoding. The converse region is obtained using some of the existing perfect-output feedback outer-bounds as well as a set of new outer-bounds that are obtained by using genie-aided models of the original G-IC-NOF. Finally, it is shown that the achievability region and the converse region approximate the capacity region of the G-IC-NOF to within a constant gap in bits per channel use.

UNB is dedicated to long range and low power transmission in IoT networks. The channel access is Random-FTMA, where nodes select their time and frequency in a random and continuous way. This randomness leads to a new behavior of the interference which has not been theoretically analyzed yet, when considering the pathloss of nodes located randomly in an area. In this paper, in order to quantify the system performance, we derive and exploit a theoretical expression of the packet error rate in a UNB based IoT network, when taking into account both interference due to the spectral randomness and path loss due to the propagation.

This paper presents a simple and effective method to study the spectral and energy efficiency (SE-EE) trade-off in cellular networks, an issue that has attracted significant recent interest in the wireless community. The proposed theoretical framework is based on an optimal radio resource allocation of transmit power and bandwidth for the downlink direction, applicable for an orthogonal cellular network. The analysis is initially focused on a single cell scenario, for which in addition to the solution of the main SE-EE optimization problem, it is proved that a traffic repartition scheme can also be adopted as a way to simplify this approach. By exploiting this interesting result along with properties of stochastic geometry, this work is extended to a more challenging multicell environment, where interference is shown to play an essential role and for this reason several interference reduction techniques are investigated. Special attention is also given to the case of low signal-to-noise ratio (SNR) and a way to evaluate the upper bound on EE in this regime is provided. This methodology leads to tractable analytical results under certain common channel properties, and thus allows the study of various models without the need for demanding system-level simulations.

In the context of radiolocation in Wireless Body Area Networks (WBANs), nodes positions can be estimated through time-based ranging algorithms. For instance, the distance separating a couple of nodes can be estimated accurately by measuring the Round Trip Time of Flight of an Impulse Radio Ultra Wideband (IR-UWB) link. This measure usually relies on two or three messages transactions. Such exchanges take time and a rapid mobility of the nodes can reduce the ranging accuracy and consequently impact nodes localization process. In this paper, we quantify this localization error by confronting two broadcast-based optimized implementations of the three-way ranging algorithm with real mobility traces, acquired through a motion capture system. We then evaluate, in the same scenarios, the impact of the MAC-level scheduling of the packets within a TDMA frame localization accuracy. The results, obtained with the WSNet simulator, show that MAC scheduling can be utilized to mitigate the effect of nodes mobility.

The purpose of this paper is to evaluate the impact of the node speed on the ranging estimation for location applications with Wireless Body Area Networks (WBAN). While estimated with the 3-Way ranging protocol (3-WR), this distance between two nodes placed on the body can be affected by the human movements. Thus, we study theoretically the ranging error with the 3-WR, based on a perfect channel, a MAC layer based on TDMA using two scheduling strategies (Single node localization (P2P-B) and Aggregated & Broadcast (A&B)) and a PHY layer based on Ultra Wideband (IR-UWB). We demonstrate the accuracy of the model, and show that the distance error is highly correlated with the speed of nodes, while the associated mobility model has an impact on the design of MAC strategies by simulation.

The exponentially growing traffic in cellular networks induced standardization groups to focus on spectral efficiency (SE) and providers to densify their networks in crowded areas. The price to pay is a significant reduction of the energy efficiency (EE). As a result, more balanced EE-SE solutions have attracted significant interest lately in the wireless community. However, the Pareto optimal bound of this problem is so far not well established. This paper makes a step by defining precisely this bound in a typical cell where the interference-plus-noise distribution is known. An analytical EE-SE bound is derived considering an optimal superposition coding mode and also three sub-optimal time-frequency sharing approaches. The typical noise-plus-interference distribution used in this paper is obtained from Poisson distributed cellular network simulations validated by the Greentouch reference model, but the analytical results broadly apply to any other reference distribution.

With the increasing demand of wireless applications, current radio transceivers are challenged by the requirement of high data rate and high flexibility. Full-Duplex Dual-Band OFDM radio transceiver is a very promising radio technique to approach this goal. However, the mutual undesirable signal leakages due to the I/Q imbalance in the Full-Duplex Dual-Band RF front-end lead to a significant performance degradation in the radio link. In this paper, a practical and suitable digital I/Q imbalance estimation and compensation method for mitigating the I/Q imbalance in this flexible radio transceivers is developed and evaluated. The developed I/Q imbalance estimation method is based on the character of the frequency-flat-fading of the self-interference channel. The ADS-Matlab co-simulation results show that the developed digital compensation method can significantly reduce the impact of the I/Q imbalance on the Full-Duplex Dual-Band OFDM radio receivers.

We present in this paper a new medium access control (MAC) scheme devoted to orthogonal frequency division multiple access (OFDMA) systems which aims at reducing collision probabilities during the channel request period. The proposed MAC relies on the classical carrier sense multiple access/collision avoidance (CSMA/CA) protocol with RTS / CTS (“Request To Send” / “Clear To Send”) mechanism. The proposed method focus on the collision probability of RTS messages exploiting a multi-channel configuration for these messages while using the whole band for data transmissions. The protocol may be interpreted as an asynchronous frequency multiplexing of RTS messages. This method achieves strong performance gains in terms of throughput and latency especially in crowded networks.

Ultra narrow band transmission (UNB) systems have already been deployed and have proved to be ultra-efficient for point-to-point communications. This paper presents this technology and gives some insights on the scalability of UNB for a multi-point to point network. This configuration corresponds to an uplink scenario where multiple nodes compete to send their packets, with neither coordination nor feedback from the sink. In particular, we present and analyze two multiple access schemes based on random frequency selection: discrete random FDMA (DR-FDMA) and the new continuous random FDMA (CR-FDMA). An ideal system where the carrier frequencies are exactly obtained is first considered and extended to a more realistic case, with rough carrier frequencies. We analyze the system performance in terms of bit error rate and outage probability. The presented results clearly show that, even if in the ideal case, the DR-FDMA scheme outperforms the CR-FDMA scheme; in the realistic case, both schemes lead to similar performance. Thus, this paper highlights the fact that the use of CR-FDMA is very relevant in a realistic network as it bypasses the need of an accurate carrier frequency control, and thus permits the use of even the cheapest transmitters without loss of performance.

The issue of energy efficiency (EE) in Orthogonal Frequency-Division Multiple Access (OFDMA) wireless networks is discussed in this paper. Our interest is focused on the promising concept of base station (BS) sleep mode, introduced recently as a key feature in order to dramatically reduce network energy consumption. The proposed technical approach fully exploits the properties of stochastic geometry, where the number of active cells is reduced in a way that the outage probability, or equivalently the signal to interference plus noise (SINR) distribution, remains the same. The optimal EE gains are then specified with the help of a simplified but yet realistic BS power consumption model. Furthermore, the authors extend their initial work by studying a non-singular path loss model in order to verify the validity of the analysis and finally, the impact on the achieved user capacity is investigated. In this context, the significant contribution of this paper is the evaluation of the theoretically optimal energy savings of sleep mode, with respect to the decisive role that the BS power profile plays.

Relay channels have been extensively studied in the literature since the seminal paper by Cover and El Gamal. Nevertheless, characterizing the capacity of relay channels still presents open issues. While numerous works addressed this problem with constant powers or targeted the sum-rate optimization, computing the capacity in the case of a global power constraint was less studied. In this paper, we introduce the concept of virtual nodes to derive analytical expressions of the relay channel capacity as a function of the total power. This transformation leads to simple closed-form expressions of the upper bound and decode-and-forward (DF) lower bound on the capacity of the full- and half-duplex relay channels. The half-duplex study is separated into low and high signal-to-noise ratio (SNR) cases. The impact of these approximations is evaluated and found to achieve a large part of the maximal capacity in the worst case where the equivalent received SNR is neither low nor high, typically between 0-10dB.

A matching theoretic approach to study the partner selection in cooperative relaying is followed. Partner selection is considered as a special stable roommate problem where each player ranks its partners by some criterion. Each agent aims here at finding a “good” partner in order to exploit efficiently the spatial diversity achieved with cooperation. We adapt Irving's algorithm [3] for determining the partners of each player. The ranking criterion here is chosen to be outage probability such that each player comprises its own preference list according to outage probability from the lowest to the highest. The first player in the preference list provides the lowest outage probability. We introduce a decentralized version of Irving's algorithm. Then, we compare the results obtained by stable-matching with the global optimum and random selection results. From the computational results, we observe that stable-matching results are near to global optimum as well as superior than random selection in terms of average outage probability.

Existing methods of self-interference cancellation have greatly reduced the strong self-interference signal for the practical design of Full-Duplex (FuDu) wireless systems. However, current FuDu wireless is hard to be put into practice due to the reason that residual self-interference after interference cancellation is still much stronger than the thermal noise. In this paper, a wideband FuDu OFDM system with a single path self-interference channel is developed based on active analog self-interference cancellation (AASIC) at the RF component. Furthermore, a mathematical model of the wideband FuDu OFDM wireless system and the AASIC at the RF component are presented and elaborated. The performance of this FuDu system is evaluated by ADS-Matlab co-simulation based on the IEEE 802.11g system parameters. The comparison of the spectrum power of signals before and after the AASIC and the bite error rate (BER) performance of the FuDu OFDM wireless system show that the strong self-interference can be significantly reduced to almost noise level.

We propose to analyze the impact of vehicular scattering on both individual users and global throughput of a LTE heterogeneous network. The studied network consists of a real world hexagonal configuration with 7 three-sector Macro Base Stations and 15 added Small Cells. Propagation modeling is site-specific and the main contribution of this paper relies on the introduction of channel dynamics due to vehicular traffic flow crossing radio links. Connection losses and throughput degradations due to vehicle passing are observed for individual users. The global throughput gain achieved by offloading Macro Base Stations is reduced but remains attractive.

In this paper, we study the optimal power allocations in cooperative multiple access channels (CMACs), where we aim at maximizing the rate achievable by both sources simultaneously rather than the sum of achievable rates. Separating our study between the coherent and non-coherent case, we obtain closed-form expressions for the optimal power allocations w.r.t. the outer bounds of the capacity region, as well as decode-and-forward and non-cooperative inner bounds.We point out during our resolution that the general CMAC model behaves as a multiple access relay channel (MARC), where a “virtual” relay node is introduced to represent the cooperation between the sources. This equivalent model simplifies the original power allocation problem. We finally show that the general cut-set outer bound on the capacity region of the equivalent MARC matches exactly the tightest known outer bound on the capacity region of the original CMAC.

Bit Error Rate (BER) is a key parameter used to evaluate the performance of radio communication systems. In this paper, a realistic BER of radio MRC diversity systems is predicted based on the Multi-Resolution Frequency Domain ParFlow (MRFDPF) model. The prediction takes into account the correlations among diversity branches and makes no assumptions of the correlation model. The predicted realistic BER for MRC diversity systems can be very useful to many wireless applications, such as, adaptive modulation and coding (AMC) scheme, or optimal power allocation.

This paper studies a significant problem in green networking called switching off base stations in case of cooperating service providers by means of stochastic geometric and coalitional game tools. The coalitional game herein considered is played by service providers who cooperate in switching off base stations. When they cooperate, any mobile is associated to the nearest BS of any service provider. Given a Poisson point process deployment model of nodes over an area and switching off base stations with some probability, it is proved that the distribution of signal to interference plus noise ratio remains unchanged while the transmission power is increased up to preserving the quality of service. The coalitional game behavior of a typical player is called to be hedonic if the gain of any player depends solely on the members of the coalition to which the player belongs, thus, the coalitions form as a result of the preferences of the players over their possible coalitions' set. We utilize the Nash-stable core for determining the coalitions of service providers.

In this paper, we consider the performance of coded wireless communication systems experiencing non-frequency selective fading channels in shadowed environments. The quality of service (QoS) in a wireless network is dependent on the packet error outage (PEO). We address the problem of finding a tractable expression for the coded PEO over Nakagami-m channels with shadowing, considering multilevel modulations, various block and convolutional channel coding schemes and hard decision decoding. In order to obtain the coded PEO, an inversion of the coded packet error probability (PEP) w.r.t. the signal to noise ratio (SNR) is needed. To this end, we propose an invertible approximation for the coded PEP w.r.t. the uncoded bit error probability (BEP) in Nakagami-m fading channels which is accurate for all BEPs of interest. The BEP itself depends on the average SNR and we hence make use of previous results on the inversion of the uncoded BEP w.r.t. the SNR in Nakagami-m fading channels, holding for M-PSK and M-QAM signals. We were thus able to obtain a reliable closed form expression for the coded PEO in flat fading and shadowing channels. The theoretical findings are verified by means of simulations.

Body area networks (BANs), referring to embedded wireless systems in, on, and around bodies, are expected to take an important role for health, leisure, sports, and all the facets of our daily life. In many cases, several BANs coexist in a small area, resulting in very strong inter-BAN interference, which seriously disturbs intra-BAN communications. The goal of this paper is to decrease inter-BAN interference by cooperative scheduling, hence increasing packet reception rate (PRR) of intra-BAN communications. Cooperative scheduling here is divided into two sub-problems: single-BAN scheduling as an assignment problem and multi-BAN concurrent scheduling as a game. For the first sub-problem, a low complexity algorithm, horse racing scheduling, is proposed, which achieves near-optimal PRR for the BAN performing scheduling. For the second sub-problem, we prove the existence of a set of mixed strategy Nash equilibria (MSNE). Then, we propose a distributed cooperative scheduling scheme, which efficiently achieves higher PRR than the MSNE without degrading fairness.

The main goal of this work is to incorporate security in an existing ultra wideband (UWB) network. We present an embedding method where a tag is added at the physical layer and superimposed to the UWB-impulse radio signal. The tag should be added in a transparent way so that guaranteeing compatibility with existing receivers ignoring the presence of the tag. We discuss technical details of the new embedding method. In addition, we discuss embedding strength and we analyze robustness performance. We demonstrate that the proposed embedding technique meets all the system design constraints.

This paper presents a propagation model generating time series of large-scale power variations for small-cell radio links intersected by vehicular traffic. The model combines stochastic processing and geometric computation. For each road crossing a link, a two-state process parameterized by mobility statistics represents the obstruction status. When the status is set to obstructed, a fluctuation pattern is generated. Based on previously published measurements, both mobility statistics and time series results are validated through the comparison of respectively inter-obstruction duration distributions and outage probabilities. The proposed model avoids resource-consuming iterative propagation prediction while providing realistic and frequency adaptive results.

With the great expansion of wireless communications, jamming becomes a real threat. We propose a new model to evaluate the robustness of a communication system to jamming. The model results in more scenarios to be considered ranging from the favorable case to the worst case. The model is applied to a TH-UWB radio. The performance of such a radio in presence of the different jamming scenarios is analyzed. We introduce a mitigation solution based on stream cipher that restricts the jamming problem of the TH-UWB communication to the more favorable case while preserving confidentiality.

In this paper, we aim at characterizing the gain induced by using relay channels in a linear network under both capacity constraint and realistic energy model. We express a general model based on a convex optimization problem. Then, we use numerical tools to obtain results on the outer and inner bounds of the capacity of the full and half duplex relay channel. We then further this study with more complex networks based on relay channels, especially networks formed by a linear chain of nodes. We describe the Pareto optimal solutions of the minimization problem with respect to the consumed energy and latency in such a linear network. From the simple case of the linear multi-hop network, we study the gains when implementing a linear chain of relay channels and compare these results to the simpler multi-hop transmission.

This paper addresses the distributed power adaptation (DPA) problem on the downlink for wireless cellular networks. As a consequence of uncoordinated local scheduling decisions in classical networks, the base stations produce mutual uncontrolled interference on their co-channel users. This interference is of a variable nature, and is hardly predictable, which leads to suboptimal scheduling and power control decisions. While some works propose to introduce cooperation between BS, in this work we propose instead to introduce a model of power variations, called trajectories in the powers space, to help each BS to predict the variations of other BS powers. The trajectories are then updated using a Model Predictive Control (MPC) to adapt transmit powers according to a trade-off between inertia (to being predictable) and adaptation to fit with capacity needs. A Kalman filter (KF) is used for the interference prediction. In addition, the channel gains are also predicted, in order to anticipate channel fading states. This scheme can be seen as a dynamic distributed uncoordinated power control for multichannel transmission that fits the concept of self-optimised and self-organised wireless networks (SON). By using the finite horizon MPC, the transmit powers are smoothly adapted to progressively leave the current trajectory toward the optimal trajectory. We formulate the optimisation problem as the minimisation of the utility function of the difference between the target powers and MPC predicted power values. The presented simulation results show that in dynamic channel conditions, the benefit of our approach is the reduction of the interference fluctuations, and as a consequence a more accurate interference prediction, which can further lead to a more efficient distributed scheduling, as well as the reduction of the overall power consumption.

One of the most powerful ways to achieve transmission reliability over wireless links is to employ efficient coding techniques. This paper investigates the performance of a transmission over a relay channel where information is protected by two layers of coding. In the first layer, transmission reliability is ensured by fountain coding at the source. The second layer incorporates network coding at the relay node. Thus, fountain coded packets are re-encoded at the relay in order to increase packet diversity and reduce energy consumption. Performance of the transmission is measured by the total number of transmissions needed until the message is successfully decoded at the destination. We show through both analytical derivations and simulations that adding network coding capabilities at the relay optimizes system resource consumption. When the source uses a random linear fountain code, the proposed two-layer encoding becomes more powerful as it reduces the transmission rate over the direct link between the source and the destination.

In the context of heterogeneous networks, femtocells are very promising. In order to properly simulate their behavior and their impact on the macrocell layer, it is necessary to be able to simulate the radio coverage of femtocells. Hence ParFlow is a possible deterministic model that can be used for such simulation. In this paper two implementations of ParFlow are presented: time domain and frequency domain. The performance are compared and the advantages/drawbacks of each model are investigated.

In this paper, we propose an autonomous radio resource allocation and optimization scheme that chooses the transmit power and precoding vector among codebooks for multiple antennas transmitters to improve spectral and power efficiency and provide user fairness. Network self-optimization is an essential feature for supporting the cell densification in future wireless cellular systems. The proposed self-optimization is inspired by Gibbs sampler. We show that it can be implemented in a distributed manner and nevertheless achieves system-wide optimization which improves network throughput, power utilization efficiency, and overall service fairness. In addition, we extend the work and include power pricing to parametrize and enhance energy efficiency further. Simulation results show that the proposed scheme can outperform today's default modes of operation in network throughput, energy efficiency, and user fairness.

Multi-cell processing, also called Coordinated Multiple Point (CoMP), is a promising distributed technique that uses neighbour cells' antennas. It is expected to be the part of next generation cellular standards such as LTE-A. Small cell networks in dense urban environments are limited by interferences and CoMP can strongly take advantage of this fact to improve cell-edge users' throughput. The present study introduces a distributed criterion for mobiles to select their optimal set of Base Stations (BS) to perform CoMP, and evaluates the impact of this association on the fairness and the total cell throughput. For that, we use a known theoretical expression for the capacity outage probability of CoMP under Rayleigh fading and evaluate the goodputs of antennas associations. The proposed criterion is used in combination with alpha-fair resource allocation to perform a joint double-objective optimization of fairness and efficiency.

In this paper we propose to use finite difference propagation methods to evaluate the wide band properties of the fast fading. For this purpose we adapted the MR-FDPF propagation model to simulate large bandwidth by combining numerous narrow band simulations. The results are compared with a channel sounder measurement campaign covering a band width of up to 70 MHz. It is verified that fading characteristics in wireless channels varies with frequency and the MR-FDPF method is capable for simulating this variation of fadings for wide band systems.

We consider a common object (data) that each mobile in the medium is interested to receive, and which can be obtained from any base station transmitting the data. For example, the broadcast object could be streaming transmission of a sport or cultural event, or it could be some signaling such as a beacon for time synchronization or for power control purposes. This problem can be conceived as a coalition game played by mobiles which we call as association game of mobiles. This game has an incentive to form grand coalition where all players join to the game. We prove that using Bondareva-Shapley theorem, this coalition game has a non-empty core which means that grand coalition is stable. Then, we examine the cost allocation policy for different methods such as egalitarian allocation, proportional repartition of total cost, the Shapley value and the nucleolus. We also conclude that if the nucleolus is used as the cost allocation algorithm, the players maintain the grand coalition satisfying the minimization of total cost for broadcast transmission.

We deal with the analytical performance study of orthogonal space-time block codes (OSTBC) applied to multiple-input multiple-output (MIMO) systems experiencing non-frequency selective fast fading and shadowing. We address the problem of finding a tractable closed-form expression for the symbol error outage (SEO) over Rice fading channels in shadowing environments. In order to obtain the SEO, a symbol error probability (SEP) inversion w.r.t. the average signal to noise ratio (ASNR) is needed since no invertible SEP approximations are available in literature. We propose an accurate approximation for the SEP in Rice fading channels. This new approximation is proved to be invertible w.r.t. the ASNR and this expression thus facilitates the derivation of a tight approximation of the SEO in lognormal shadowing environments.

Relay attacks pose a real threat to the security of wireless communications. Distance bounding protocols have been designed to thwart these attacks. In this paper, we study the way to adapt distance bounding protocols to time-hopping ultra wide band (TH-UWB) radios. Two protocols are proposed which are based on the milestones of the TH-UWB radio: the time-hopping sequence and the mapping code. The security and the different merits of those protocols are analyzed.

Cooperative MIMO (CMIMO) communications have transformed channel fading from a negative factor that should be mitigated into a positive factor that can be exploited in wireless networks to improve capacity. Meanwhile, CMIMO scheme has been proved to be an effective solution to improve the energy efficiency of a network. However, an inherent feature of wireless channels, unreliability caused by channel fading is neglected in related studies. In this paper, on the basis of an unreliable link model, the trade-off between the energy consumption and the transmission delay of CMIMO scheme is investigated from the viewpoint of cross-layer, and a lower bound of energy-delay tradeoff is provided which offers a deep insight into the benefits of CMIMO compared with classical multi-hop communications. Moreover, a cross-layer framework is introduced to optimize the parameters at the physical and protocol layers.

This paper concentrates on characterizing energy, latency and capacity trade-offs in multi-hop wireless ad-hoc networks. Therefore, a multiobjective framework is proposed to derive the Pareto-optimal set of solutions with respect to these three criteria. The work presented in this paper assumes a linear network where transmission powers and relay positions are optimization variables. We study the asymptotic state where the distance between source and destination is very high such that the number of hops tends to infinite. Two types of traffic are considered in the following. First, low rate traffic is analyzed by characterizing the multiobjective performance of a single packet transmission using an interference free multi-hop relaying strategy. Second, a continuous flow of packets from a unique source is considered. In the first case, we show an important theorem which states that all Pareto optimal solutions with respect to delay and energy metrics provide the same target SNR at the receiver side. In the second case, our analytical results highlight how the energy/delay Pareto front moves when considering a capacity constraint and the optimal re-use factor is derived.

During the last decade, many works were devoted to improving the performance of relaying techniques in ad hoc networks. One promising approach consists in allowing the relay nodes to cooperate, thus using spatial diversity to increase the capacity of the system. However, this approach introduces an overhead in terms of information exchange, increasing the complexity of the receivers. A simpler way of exploiting spatial diversity is referred to as opportunistic routing. In this scheme, a cluster of nodes still serves as relay candidates but only a single node in the cluster forwards the packet. This paper proposes a thorough analysis of opportunistic routing efficiency under different realistic radio channel conditions. The study aims at finding the best trade-off between two objectives: energy and latency minimizations, under a hard reliability constraint. We derive an optimal bound, namely, the Pareto front of the related optimization problem, which offers a good insight into the benefits of opportunistic routing compared with classical multi- hop routing.

Body Area Networks (BAN) offer amazing perspectives to instrument and support humans in many aspects of their life. Among all possible applications, this paper focuses on body monitoring applications having a body equipped with a set of sensors transmitting in real-time their measures to a common sink. The underlying network topology is a star topology which is quite usual in the broad scope of wireless sensor networks. Therefore, a classical superframe structure as proposed in 802.15.3 or 802.15.4 seems to comply with the needs of such an application. Basically however, the specificities of the BAN channel can reduce the performance of such protocol. Indeed, channel time variations make the star structure unstable and temporary subject to a high packet error rate. A multi-hop mesh topology cannot counteract this problem efficiently, since the pathloss attenuation in a BAN environment is almost independent with the emitter-receiver distance. In this paper, we address this issue by considering the topology of a BAN network as a time-varying fully connected network instead of a star structure. We then show how an opportunistic cooperative mechanism based on a decode-and-forward protocol can address this issue. We derive a performance criterion based on a packet error rate outage and we discuss the implementation of this scheme in the classical superframe structure.

In UWB Impulse Radio (UWB-IR), non coherent reception with energy collection might suffer from dispersive channels. This paper proposes an energy selective receiver based on a threshold device. Multipath detection decisions are weighted by a confidence coefficient and combined, following an optimum Bayesian decision rule that takes into account both multipaths and symbol coding. Simulations on realistic channels show that this low complexity receiver outperforms energy collectors and provides performances close to quasi-optimum non coherent receivers.

This paper discusses medium access control (MAC) issues for a body area network (BAN), whose physical layer is Ultrawide Band Impulse radio (UWB-IR). In some particular situations, the MAC layer of a BAN can not rely on a TDMA solution with a beacon emission by a coordinator, as it may be most of the time. We propose a beacon-free MAC layer, based on a collaborative version of the preamble sampling approach. This is designed to address the regulatory LDC constraints, which UWB devices must comply to. Simulations are presented to show that this protocol looks quite interesting and future work is introduced.

During the last decade, many works were devoted to improving the performance of relaying techniques in ad hoc networks. One promising approach consists in allowing the relay nodes to cooperate, thus using spatial diversity to increase the capacity of the system. However, this approach introduces an overhead in terms of information exchange, increasing the complexity of the receivers. A simpler way of exploiting spatial diversity is referred to as opportunistic routing. In this scheme, a cluster of nodes still serves as relay candidates but only a single node in the cluster forwards the packet. In this paper, we put forward an analytical framework to optimize the opportunistic communication scheme in order to minimize the energy consumption. Meanwhile, the optimizations of node density and the transmission power are analyzed for different ranges of relay candidates in Rayleigh block fading and additive white gaussian noise (AWGN) channels. In the energy consumption viewpoint, the analyses indicate that the opportunistic communication is more efficient in Rayleigh block fading channel than that in AWGN channel.

This letter addresses the problem of finding a tractable expression for the symbol error outage (SEO) in flat Nakagami-m fading and shadowing channels. We deal with M-ary phase shift keying (M-PSK) and quadrature amplitude modulation (M-QAM) which extends our previous results on BPSK signaling. We propose a new tight approximation of the symbol error probability (SEP) holding for M-PSK and M-QAM signals which is accurate over all signal to noise ratios (SNRs) of interest. We derive a new generic expression for the inverse SEP which facilitates the derivation of a tight approximation of the SEO in a lognormal shadowing environment.

As synchronization preambles represent a great overhead on wireless data packets, it could be interesting to powerful them. Fine synchronization solves this problem by homogenizing clock drift values on network regions. When coupled with any clock bias consensus method (coarse synchronization), fine synchronization allows the setup of time-based medium multiplexing schemes (TDMA, Slotted-ALOHA, ...) . This paper deals with a lightweight method able to perform the computation of local clock drift corrections using simple interaction rules between neighbor nodes. The solution proposed in this work has the main advantage to be robust to measurement noise while having the technologically interesting ability to drive clock drifts towards an average consensus.

In wireless multi-hop networks, there is a growing need for the performance evaluation of protocols and distributed applications. Due to the high complexity of analytical models and the difficulty of setting up large scale testbeds, simulations are generally considered as the most convenient methodology for evaluating the performance of wireless systems. However, evaluating a protocol can be a tedious task as it depends on several factors including the physical layer modeling and the dimensioning of protocol or environment parameters. As a consequence inferring an overall performance for a protocol is a real issue. In this paper, we highlight some main factors that may affect the accuracy of the performance evaluation of protocols using simulations. First, we focus on the physical layer (PHY) modeling which represent a key point for the sake of realism and confidence. Second, we discuss the impact of some protocol parameters on the behavior of the evaluated protocols.

Energy efficiency is a hot topic in Wireless Sensor Networks (WSNs) because of the limited power supply. Routing strategies have a major impact on total energy consumption of network. Long-hop routing strategies demand substantial transmission power but are capable of reducing energy consumed by relay nodes. Short-hop routing strategies are just the reverse. This paper explores how multi-hop routing strategies are more energy efficient for periodic monitoring applications. We propose an energy efficiency metric for periodic monitoring applications, referred to as the Energy Distance Ratio per bit (EDRb). The concept of unreliable links is integrated into the proposed energy model to take transmission errors into account. By minimizing EDRb, an optimal hop distance is obtained for which related parameters such as optimal transmission power, optimal signal noise ratio (SNR) and optimal bit error rate (BER) are found in Rayleigh fading environment. On the basis of the obtained optimal hop distance, the low bound of mean EDRb for multi- hop path is computed. Finally, theoretical results are compared to simulations. It is shown that the network's lifetime can be extended significantly by optimizing the hop length in a classical routing scheme.

The roll-out density of wireless local area networks (WLANs) has recently witnessed a dramatic increase and is currently reaching saturation levels. The frequency bands designated to WLANs does not suffice any more to provide non-overlapping, and hence interference-free, communication bands. A large body of research has been dedicated to a wide variety of optimum maximum likelihood sequence estimation (MLSE) and sub-optimum in-band interference mitigation techniques. Our contribution lies in a reduction of the state-space of a MLSE detector in the case of a desired WLAN receiver experiencing delayed interference from some other transmitters operating in partially overlapping spectral bands and over independent frequency-selecting block-fading channels. Based on the formulation of the optimum receiver, we derive a sub-optimum receiver of reduced complexity and demonstrate its satisfactory performance in the context of strong interference.

The deployment of wireless local area networks (WLANs) has recently gained in popularity with roll-out densities often reaching saturation levels. The frequency bands designated to WLANs do thus not suffice anymore to provide non-overlapping, and hence interference-free, communication. Prior research has therefore been dedicated to a wide variety of mainly cochannel interference mitigation techniques. Our contribution lies in the performance analysis of the more realistic case of spatially close WLAN systems interfering asynchronously in DSSS mode and on adjacent channels. The authors expose the performance of optimum and sub-optimum multiuser detection maximum likelihood sequence estimators (MUD-MLSEs) under varying conditions, e.g. level of interference, degree of spectral overlap, etc. This facilitates a better understanding and design of future interference-limited WLAN systems. The performance results are also important to spectrum policy makers, allowing to knowledgeably estimate the degree of tolerated interference in license exempt bands.

Several softwares have been developed for computer-aided design of radio networks. The first constitutive element of such a tool is the propagation modelling algorithm. The second is the planning process providing positions and setup of access points. The last one concerning the frequency channel allocation problem (FAP) is the focus of this paper. Many works devoted to this problem exploit a graph-based modelling that leads to an under-constrained problem as interference between mobile nodes are not taken into account. In this paper a new QoS-based FAP criterion is formulated. This QoS criterion measures the overall throughput taking downlink interference into account. We show on an example that our FAP model outperforms usual graph-based FAP approaches concerning the effective SINR obtained at mobile nodes. Results are based on realistic simulations exploiting a simulator called WILDE (Wireless Lan DEsign) and implementing the MR-FDPF propagation algorithm.

This paper describes an automatic wireless LAN access points planning approach based on a multicriteria modelling and solving. A realistic and efficient wLAN planning approach can not only assess usual objectives based on radio coverage. It has to further implement a Quality of Service (QoS) constraint. In this work, a QoS criterion is defined as the mean available bandwidth per user, derived from a Markov-based performance evaluation model of the medium access control (MAC) layer behavior. Optimizing both coverage and QoS objectives results in finding the optimal trade-off between these concurrent criteria. Rather than optimizing a weighted sum of the optimization criteria that provides a single solution, it is herein proposed to develop a dedicated multicriteria search algorithm. Its main feature is to provide several solutions, each one representing a peculiar tradeoff between the objectives. The planning process estimates for each solution the optimal number of APs and their placement. The AP's coverage is estimated with a powerful multi-resolution radio propagation simulator previously described. This paper presents results for a QoS oriented planning process providing a predefined minimum per-user throughput. The example provided herein applies for 200 users distributed over a 12600 m2building floor.

International audience

We have recently proposed an original 2D multi-resolution algorithm for solving a TLM-like formulation of the Indoor propagation problem. This approach is referred to as MR-FDPF (multi-resolution frequency domain parflow). In this paper, a fast and simple extension for predicting radio coverage in multifloored building is proposed. Because a full 3D is time consuming, three 2.5D schemes are investigated and compared. The accuracy of MR-FDPF is firstly assessed in a single floor configuration. Results exhibit a RMSE of about 3.5 dB, after an automatic calibration. Then 2.5D extensions are evaluated on a multifloored building. The more sophisticated one yields a RMSE of about 4.4 dB for the inter-level prediction. The potential of this approach and the obvious limitations when compared to a true 3D approach are discussed.

This paper proposes an automatic base station planning approach. This approach does not only try to assess usual objectives such as radio coverage, but further implements a quality of service (QoS) constraint. This criterion is here defined as the mean available bandwidth per user. Its computation takes the medium access control (MAC) layer behavior, the multiple bit rates of IEEE 802.11b and the coverage area of each access point (AP) into account. A Markov chain is used to evaluate the available bandwidth of each cell independently. This is sensible because a non-overlapping criterion between cells is used during the planning phase to avoid interference between adjacent cells. The planning process estimates an optimal number of APs and their placement minimizing an aggregate criterion using a Tabu meta-heuristic. The AP's coverage is estimated with a powerful multi-resolution radio propagation simulator previously described. This paper presents results for a QoS oriented planning process providing a predefined minimum peruser throughput. The example provided herein applies for 100 users distributed over a 12600 m2building floor

The increase of potential applications of wireless networks in indoor environments calls for robust and efficient tools for predicting the wave propagation in such complex environments. The ParFlow technique is a discrete approach which accurately reflects the behavior of wave propagation but in turn requires very high computation and time resources. Initially this method has been implemented in a parallel architecture to reduce the computation time. A new resolution scheme is proposed to solve the discrete ParFlow equations. This approach is based on a multi-resolution formulation in the Fourier domain. The major result of our approach is that the computation complexity may be settled in two parts. Firstly, the multi-resolution pyramid is built (taking into account the geometry arrangement of the indoor environment). Secondly, the propagation from a point source is evaluated through the soft pyramidal architecture with a high gain in terms of computational efficiency. We guess that this approach could increase the interest of the ParFlow technique which could be more accurate than ray-tracing methods at least in a theoretical point of view.