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Federated learning (FL) has recently emerged as a distributed machine learning paradigm for systems with limited and intermittent connectivity. This paper presents the new context brought to FL by satellite constellations, where the connectivity patterns are significantly different from the ones observed in conventional terrestrial FL. The focus is on large constellations in low Earth orbit (LEO), where each satellites participates in a data-driven FL task using a locally stored dataset. This scenario is motivated by the trend towards mega constellations of interconnected small satellites in LEO and the integration of artificial intelligence in satellites. We propose a classification of satellite FL based on the communication capabilities of the satellites, the constellation design, and the location of the parameter server. A comprehensive overview of the current state-of-the-art in this field is provided and the unique challenges and opportunities of satellite FL are discussed. Finally, we outline several open research directions for FL in satellite constellations and present some future perspectives on this topic., Copyright 2023 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works

The reliable provision of entangled qubits is an essential precondition in a variety of schemes for distributed quantum computing. This is challenged by multiple nuisances, such as errors during the transmission over quantum links, but also due to degradation of the entanglement over time due to decoherence. The latter can be seen as a constraint on the latency of the quantum protocol, which brings the problem of quantum protocol design into the context of latency-reliability constraints. We address the problem through hybrid schemes that combine: (1) indirect transmission based on teleportation and purification; (2) direct transmission, based on quantum error correction (QEC). The intuition is that, at present, the quantum hardware offers low fidelity, which demands purification; on the other hand, low latency can be obtained by QEC techniques. It is shown that, in the proposed framework, the purification protocol gives rise to asymmetries that can be exploited by asymmetric quantum error correcting code (QECC), which sets the basis for unique hybrid purification and coding design. Our results show that ad-hoc asymmetric codes give, compared to conventional QEC, a performance boost and codeword size reduction both in a single link and in a quantum network scenario., 27 pages, 11 figures, submitted to an IEEE journal

Efficient integration of reconfigurable intelligent surfaces (RISs) into the current wireless network standard is not a trivial task due to the overhead generated by performing channel estimation (CE) and phase-shift optimization. In this paper, we propose a framework enabling the coexistence between orthogonal-frequency division multiplexing (OFDM) and RIS technologies. Instead of wasting communication symbols for the CE and optimization, the proposed framework exploits the localization information obtainable by RIS-aided communications to provide a robust allocation strategy for user multiplexing. The results demonstrate the effectiveness of the proposed approach with respect to CE-based transmission methods., Submitted to ICC 2023, the copyright may be transferred without further notice

Sensing is envisioned as a key network function of the 6G mobile networks. Artificial intelligence (AI)-empowered sensing fuses features of multiple sensing views from devices distributed in edge networks for the edge server to perform accurate inference. This process, known as multi-view pooling, creates a communication bottleneck due to multi-access by many devices. To alleviate this issue, we propose a task-oriented simultaneous access scheme for distributed sensing called Over-the-Air Pooling (AirPooling). The existing Over-the-Air Computing (AirComp) technique can be directly applied to enable Average-AirPooling by exploiting the waveform superposition property of a multi-access channel. However, despite being most popular in practice, the over-the-air maximization, called Max-AirPooling, is not AirComp realizable as AirComp addresses a limited subset of functions. We tackle the challenge by proposing the novel generalized AirPooling framework that can be configured to support both Max- and Average-AirPooling by controlling a configuration parameter. The former is realized by adding to AirComp the designed pre-processing at devices and post-processing at the server. To characterize the end-to-end sensing performance, the theory of classification margin is applied to relate the classification accuracy and the AirPooling error. Furthermore, the analysis reveals an inherent tradeoff of Max-AirPooling between the accuracy of the pooling-function approximation and the effectiveness of noise suppression. Using the tradeoff, we optimize the configuration parameter of Max-AirPooling, yielding a sub-optimal closed-form method of adaptive parametric control. Experimental results obtained on real-world datasets show that AirPooling provides sensing accuracies close to those achievable by the traditional digital air interface but dramatically reduces the communication latency., Submitted to IEEE for possible publication

The Age of Incorrect Information (AoII) is a metric that can combine the freshness of the information available to a gateway in an Internet of Things (IoT) network with the accuracy of that information. As such, minimizing the AoII can allow the operators of IoT systems to have a more precise and up-to-date picture of the environment in which the sensors are deployed. However, most IoT systems do not allow for centralized scheduling or explicit coordination, as sensors need to be extremely simple and consume as little power as possible. Finding a decentralized policy to minimize the AoII can be extremely challenging in this setting. This paper presents a heuristic to optimize AoII for a slotted ALOHA system, starting from a threshold-based policy and using dual methods to converge to a better solution. This method can significantly outperform state-independent policies, finding an efficient balance between frequent updates and a low number of packet collisions., Accepted to IEEE ICC 2023

Low Earth orbit (LEO) satellite systems enable close to global coverage and are therefore expected to become important pillars of future communication standards. However, a particular challenge faced by LEO satellites is the high orbital velocities due to which a precise channel estimation is difficult. We model this influence as an erroneous angle of departure (AoD), which corresponds to imperfect channel state information (CSI) at the transmitter (CSIT). Poor CSIT and non-orthogonal user channels degrade the performance of space-division multiple access (SDMA) precoding by increasing inter-user interference (IUI). In contrast to SDMA, there is no IUI in orthogonal multiple access (OMA), but it requires orthogonal time or frequency resources for each user. Rate-splitting multiple access (RSMA), unifying SDMA, OMA, and non-orthogonal multiple access (NOMA), has recently been proven to be a flexible approach for robust interference management considering imperfect CSIT. In this paper, we investigate RSMA as a promising strategy to manage IUI in LEO satellite downlink systems caused by non-orthogonal user channels as well as imperfect CSIT. We evaluate the optimal configuration of RSMA depending on the geometrical constellation between the satellite and users., This article is presented in part at the 2023 International ITG 26th Workshop on Smart Antennas and 13th Conference on Systems, Communications, and Coding

The trade-off between reliability, latency, and energy-efficiency is a central problem in communication systems. Advanced hybrid automated repeat request (HARQ) techniques can reduce the number of retransmissions required for reliable communication, but they have a significant computational cost. On the other hand, strict energy constraints apply mainly to devices, while the access point receiving their packets is usually connected to the electrical grid. Therefore, moving the computational complexity required for HARQ schemes from the transmitter to the receiver may provide a way to overcome this trade-off. To achieve this, we propose the Reinforcement-based Adaptive Feedback (RAF) scheme, in which the receiver adaptively learns how much additional redundancy it requires to decode a packet and sends rich feedback (i.e., more than a single bit), requesting the coded retransmission of specific symbols. Simulation results show that the RAF scheme achieves a better trade-off between energy-efficiency, reliability, and latency, compared to existing HARQ solutions and a fixed threshold-based policy. Our RAF scheme can easily adapt to different modulation schemes, and since it relies on the posterior probabilities of the codeword symbols at the decoder, it can generalize to different channel statistics.

A reconfigurable intelligent surface (RIS) can shape the wireless propagation channel by inducing controlled phase shift variations to the impinging signals. Multiple works have considered the use of RIS by time-varying configurations of reflection coefficients. In this work we use the RIS to control the channel coherence time and introduce a generalized discrete-time-varying channel model for RIS-aided systems. We characterize the temporal variation of channel correlation by assuming that a configuration of RIS' elements changes at every time step. The analysis converges to a randomized framework to control the channel coherence time by setting the number of RIS' elements and their phase shifts. The main result is a framework for a flexible block-fading model, where the number of samples within a coherence block can be dynamically adapted., Comment: 6 pages, 4 figures, conference paper

The use of Reconfigurable Intelligent Surfaces (RIS) technology to extend coverage and allow for better control of the wireless environment has been proposed in several use cases, including Ultra-Reliable Low-Latency Communications (URLLC), communications. However, the extremely challenging latency constraint makes explicit channel estimation difficult, so positioning information is often used to configure the RIS and illuminate the receiver device. In this work, we analyze the effect of imperfections in the positioning information on the reliability, deriving an upper bound to the outage probability. We then use this bound to perform power control, efficiently finding the minimum power that respects the URLLC constraints under positioning uncertainty. The optimization is conservative, so that all points respect the URLLC constraints, and the bound is relatively tight, with an optimality gap between 1.5 and 4.5~dB., Comment: Submitted to ICC 2023, the copyright may be transferred without further notice

We investigate the coexistence of massive and critical Internet of Things (IoT) services in the context of the unsourced multiple access (UMA) framework introduced by Polyanskiy (2017), where all users employ a common codebook and the receiver returns an unordered list of decoded codewords. This setup is suitably modified to introduce heterogeneous traffic. Specifically, to model the massive IoT service, a standard message originates independently from each IoT device as in the standard UMA setup. To model the critical IoT service, we assume the generation of alarm messages that are common for all devices. This setup requires a significant redefinition of the error events, i.e., misdetections and false positives. We further assume that the number of active users in each transmission attempt is random and unknown. We derive a random-coding achievability bound on the misdetection and false positive probabilities of both standard and alarm messages on the Gaussian multiple access channel. Using our bound, we demonstrate that orthogonal network slicing enables massive and critical IoT to coexist under the requirement of high energy efficiency. On the contrary, we show that nonorthogonal network slicing is energy inefficient due to the residual interference from the alarm signal when decoding the standard messages., Comment: submitted to IEEE Transactions on Communications, extended version of a paper presented at Asilomar 2022

The emergence of mega-constellations of interconnected satellites has a major impact on the integration of cellular wireless and non-terrestrial networks (NTN). This paper studies the problem of running a federated learning (FL) algorithm within a low Earth orbit (LEO) constellation of satellites connected with intra-orbit inter-satellite links (ISL). Satellites apply on-board machine learning and transmit the local parameters to the parameter server (PS). The main contribution is a novel approach to enhance FL in satellite constellations using intra-orbit ISLs. The key idea is to rely on the predictability of satellite visits to create a system design in which ISLs mitigate the impact of intermittent connectivity and transmit the aggregated parameters to the PS. We first devise a synchronous FL, which is then extended towards an asynchronous FL for the case of sparse satellite visits to the PS. An efficient use of the satellite resources is attained by sparsification-based compression the aggregated parameters of each orbit before forwarding to the PS. Performance is evaluated in terms of accuracy and the required size of data to be transmitted. The numerical results indicate a faster convergence rate of the presented approach compared with the state-of-the-art FL on satellite constellations.

In this work, we show that a pair of entangled qubits can be used to compute a product privately. More precisely, two participants with a private input from a finite field can perform local operations on a shared, Bell-like quantum state, and when these qubits are later sent to a third participant, the third participant can determine the product of the inputs, but without learning more about the individual inputs. We give a concrete way to realize this product computation for arbitrary finite fields of prime order., Comment: 8 pages

The uplink from a very small aperture terminal (VSAT) towards multiple satellites is considered, in this paper. VSATs can be equipped with multiple antennas, allowing parallel transmission to multiple satellites. A low-complexity precoder based on imperfect positional information of the satellites is presented. The probability distribution of the position uncertainty and the statistics of the channel elements are related by the characteristic function of the position uncertainty. This knowledge is included in the precoder design to maximize the mean signal-to-leakage-and-noise ratio (SLNR) at the satellites. Furthermore, the performance w.r.t. the inter-satellite distance is numerically evaluated. It is shown that the proposed approach achieves the capacity for perfect position knowledge and sufficiently large inter-satellite distances. In case of imperfect position knowledge, the performance degradation of the robust precoder is relatively small., Comment: Accepted for presentation at IEEE International Conference on Communications (ICC) 2023; 6 pages, 4 Figures

To obviate the control of reflective intelligent surfaces (RISs) and the related control overhead, recent works envisioned autonomous and self-configuring RISs that do not need explicit use of control channels. Instead, these devices, named hybrid RISs (HRISs), are equipped with receiving radio-frequency (RF) chains and can perform sensing operations to act independently and in parallel to the other network entities. A natural problem then emerges: as the HRIS operates concurrently with the communication protocols, how should its operation modes be scheduled in time such that it helps the network while minimizing any undesirable effects? In this paper, we propose an orchestration framework that answers this question revealing an engineering trade-off, called the self-configuring trade-off, that characterizes the applicability of self-configuring HRISs under the consideration of massive multiple-input multiple-output (mMIMO) networks. We evaluate our proposed framework considering two different HRIS hardware architectures, the power- and signal-based HRISs that differ in their hardware complexity. The numerical results show that the self-configuring HRIS can offer significant performance gains when adopting our framework., Comment: 31 pages, 7 figures, submitted to an IEEE journal

The research on Reconfigurable Intelligent Surfaces (RISs) has dominantly been focused on physical-layer aspects and analyses of the achievable adaptation of the propagation environment. Compared to that, the questions related to link/MAC protocol and system-level integration of RISs have received much less attention. This paper addresses the problem of designing and analyzing control/signaling procedures, which are necessary for the integration of RISs as a new type of network element within the overall wireless infrastructure. We build a general model for designing control channels along two dimensions: i) allocated bandwidth (in-band and out-of band) and ii) rate selection (multiplexing or diversity). Specifically, the second dimension results in two transmission schemes, one based on channel estimation and the subsequent adapted RIS configuration, while the other is based on sweeping through predefined RIS phase profiles. The paper analyzes the performance of the control channel in multiple communication setups, obtained as combinations of the aforementioned dimensions. While necessarily simplified, our analysis reveals the basic trade-offs in designing control channels and the associated communication algorithms. Perhaps the main value of this work is to serve as a framework for subsequent design and analysis of various system-level aspects related to the RIS technology., Comment: Submitted to IEEE TWC, the copyright may be transferred without further notice

Reconfigurable intelligent surfaces (RISs) with their potential of enabling a programmable environment comprise a promising technology to support the coexistence of enhanced mobile broadband (eMBB) and ultra-reliable-low-latency communication (URLLC) services. In this paper, we propose a RIS-assisted scheme for multiplexing hybrid eMBB-URLLC uplink traffic. Specifically, the scheme relies on the computation of two RIS configurations, given that only eMBB channel state information (CSI) is available. The first configuration optimizes the eMBB quality of service, while the second one mitigates the eMBB interference in the URLLC traffic. Analyzing the outage probability achieved by the scheme, we demonstrate that a RIS can improve the reliability of URLLC transmissions even in the absence of URLLC CSI., Comment: 6 pages, 2 figures, conference paper submitted to 2023 IEEE Globecom

The central challenge in massive machine-type communications (mMTC) is to connect a large number of uncoordinated devices through a limited spectrum. The typical mMTC communication pattern is sporadic, with short packets. This could be exploited in grant-free random access in which the activity detection, channel estimation, and data recovery are formulated as a sparse recovery problem and solved via compressed sensing algorithms. This approach results in new challenges in terms of high computational complexity and latency. We present how data-driven methods can be applied in grant-free random access and demonstrate the performance gains. Variations of neural networks for the problem are discussed, as well as future challenges and potential directions., Comment: in IEEE Communication Magazine vol:60, iss:11, 2022

In this work, we study the trade-off between the reliability and the investment cost of an unmanned aerial system (UAS) consisting of a set of unmanned aerial vehicles (UAVs) carrying radio access nodes, called portable access points (PAPs)), deployed to serve a set of ground nodes (GNs). Using the proposed algorithm, a given geographical region is equivalently represented as a set of circular regions, where each circle represents the coverage region of a PAP. Then, the steady-state availability of the UAS is analytically derived by modelling it as a continuous time birth-death Markov decision process (MDP). Numerical evaluations show that the investment cost to guarantee a given steady-state availability to a set of GNs can be reduced by considering the traffic demand and distribution of GNs., 5 Pages, 6 Figures, Conference: VTC2022-FAll (Workshops)

In this paper, we propose a novel approach for downlink transmission from a satellite swarm towards a ground station (GS). These swarms have the benefit of much higher spatial separation in the transmit antennas than traditional satellites with antenna arrays, promising a massive increase in spectral efficiency. The resulting precoder and equalizer have very low demands on computational complexity, inter-satellite coordination and channel estimation. This is achieved by taking knowledge about the geometry between satellites and GS into account. For precoding, each satellite only requires its angles of departure (AoDs) towards the GS and it turns out that almost optimal rates can be achieved if the satellites transmit independent data streams. For the equalizer, the GS requires only knowledge about the angles of arrival (AoAs) from all satellites. Furthermore, we show that, by choosing a proper inter-satellite distance, the proposed low-complexity approach achieves the theoretical upper bound in terms of data rate. This optimal inter-satellite distance is obtained analytically under simplifying assumption and provides a heuristic for practical scenarios. Furthermore, a novel approach to increase the robustness of the proposed precoder and equalizer against imperfect AoD and AoA knowledge is proposed by exploiting the statistics of the estimation error., 32 pages, 12 figures, submitted to IEEE Transactions on Wireless Communications. arXiv admin note: text overlap with arXiv:2112.08791

There are three generic services in 5G: enhanced mobile broadband (eMBB), ultra-reliable low-latency communications (URLLC), and massive machine-type communications (mMTC). To guarantee the performance of heterogeneous services, network slicing is proposed to allocate resources to different services. Network slicing is typically done in an orthogonal multiple access (OMA) fashion, which means different services are allocated non-interfering resources. However, as the number of users grows, OMA-based slicing is not always optimal, and a non-orthogonal scheme may achieve a better performance. This work aims to analyse the performances of different slicing schemes in uplink, and a promising scheme based on rate-splitting multiple access (RSMA) is studied. RSMA can provide a more flexible decoding order and theoretically has the largest achievable rate region than OMA and non-orthogonal multiple access (NOMA) without time-sharing. Hence, RSMA has the potential to increase the rate of users requiring different services. In addition, it is not necessary to decode the two split streams of one user successively, so RSMA lets suitable users split messages and designs an appropriate decoding order depending on the service requirements. This work shows that for network slicing RSMA can outperform NOMA counterpart, and obtain significant gains over OMA in some region.

The grant-free access is envisioned as one of the enablers of the ultra-reliable low-latency communications. Yet, when there are many devices that tend to be active only intermittently, the fully orthogonal resource allocation is largely inefficient. The solution is to employ a common, shared pool of resources and account for the fact that some collisions and interference will inevitably occur. In this contribution we study the reliability aspects of such multi-user uplink communication scenario over a shared pool of channel resources, where intermittently active devices utilize multiple transmissions (K-repetition coding) to achieve diversity. We focus on two access methods -- one where devices choose the K slots at random and one where the access patterns are deterministic and follow a specific code design, namely the Steiner System. We analyze the problem under two signal models that involve different complexity for the receiver. Firstly, a model which treats collisions as destructive, i.e. only those K' among K transmissions that do not contain interference can be used and combined. Second, where receiver is capable of utilizing all K replicas and applies maximum ratio combining (MRC) treating interference as noise. Furthermore, in both cases we investigate the receiver with and without successive interference cancellation (SIC) capabilities. As one of the main contributions of this work, we develop useful approximations and bounds for the outage probabilities in the aforementioned scenarios that match very closely the simulation results. We also show that deterministic patterns have the potential to significantly outperform fully random selection, both in terms of raw performance and by simplifying the system design.

Despite the extensive use of a centralized approach to design receivers at the base station for massive multiple-input multiple-output (M-MIMO) systems, their actual implementation is a major challenge due to several bottlenecks imposed by the large number of antennas. One way to deal with this problem is by fully decentralizing the classic zero-forcing receiver across multiple processing nodes based on the gradient descent method. In this paper, we first explicitly relate this decentralized receiver to a distributed version of the Kaczmarz algorithm and to the use of the successive interference cancellation (SIC) philosophy to mitigate the residual across nodes. In addition, we propose two methods to further accelerate the initial convergence of these iterative decentralized receivers by exploring the connection with the Kaczmarz algorithm: 1) a new Bayesian distributed receiver, which can eliminate noise on an iteration basis; 2) a more practical method for choosing the relaxation parameter. The discussion also consider spatial non-stationarities that arise when the antenna arrays are extremely large (XL-MIMO). We were able to improve the numerical results for both spatially stationary and non-stationary channels, but mainly the non-stationary performance can still be improved compared to the centralized ZF receiver. Future research directions are provided with the aim of further improving the applicability of the receiver based on the principle of successive residual cancellation (SRC)., conference, 7 figures

In edge inference, an edge server provides remote-inference services to edge devices. This requires the edge devices to upload high-dimensional features of data samples over resource-constrained wireless channels, which creates a communication bottleneck. The conventional solution of feature pruning requires that the device has access to the inference model, which is unavailable in the current scenario of split inference. To address this issue, we propose the progressive feature transmission (ProgressFTX) protocol, which minimizes the overhead by progressively transmitting features until a target confidence level is reached. The optimal control policy of the protocol to accelerate inference is derived and it comprises two key operations. The first is importance-aware feature selection at the server, for which it is shown to be optimal to select the most important features, characterized by the largest discriminant gains of the corresponding feature dimensions. The second is transmission-termination control by the server for which the optimal policy is shown to exhibit a threshold structure. Specifically, the transmission is stopped when the incremental uncertainty reduction by further feature transmission is outweighed by its communication cost. The indices of the selected features and transmission decision are fed back to the device in each slot. The optimal policy is first derived for the tractable case of linear classification and then extended to the more complex case of classification using a convolutional neural network. Both Gaussian and fading channels are considered. Experimental results are obtained for both a statistical data model and a real dataset. It is seen that ProgressFTX can substantially reduce the communication latency compared to conventional feature pruning and random feature transmission.

In 1940s, Claude Shannon developed the information theory focusing on quantifying the maximum data rate that can be supported by a communication channel. Guided by this, the main theme of wireless system design up until 5G was the data rate maximization. In his theory, the semantic aspect and meaning of messages were treated as largely irrelevant to communication. The classic theory started to reveal its limitations in the modern era of machine intelligence, consisting of the synergy between IoT and AI. By broadening the scope of the classic framework, in this article we present a view of semantic communication (SemCom) and conveying meaning through the communication systems. We address three communication modalities, human-to-human (H2H), human-to-machine (H2M), and machine-to-machine (M2M) communications. The latter two, the main theme of the article, represent the paradigm shift in communication and computing. H2M SemCom refers to semantic techniques for conveying meanings understandable by both humans and machines so that they can interact. M2M SemCom refers to effectiveness techniques for efficiently connecting machines such that they can effectively execute a specific computation task in a wireless network. The first part of the article introduces SemCom principles including encoding, system architecture, and layer-coupling and end-to-end design approaches. The second part focuses on specific techniques for application areas of H2M (human and AI symbiosis, recommendation, etc.) and M2M SemCom (distributed learning, split inference, etc.) Finally, we discuss the knowledge graphs approach for designing SemCom systems. We believe that this comprehensive introduction will provide a useful guide into the emerging area of SemCom that is expected to play an important role in 6G featuring connected intelligence and integrated sensing, computing, communication, and control., Comment: This is an invited paper for Journal of Communications and Information Networks

With the advent of 5G technology, the notion of latency got a prominent role in wireless connectivity, serving as a proxy term for addressing the requirements for real-time communication. As wireless systems evolve towards 6G, the ambition to immerse the digital into the physical reality will increase. Besides making the real-time requirements more stringent, this immersion will bring the notions of time, simultaneity, presence, and causality to a new level of complexity. A growing body of research points out that latency is insufficient to parameterize all real-time requirements. Notably, one such requirement that received a significant attention is information freshness, defined through the Age of Information (AoI) and its derivatives. The objective of this article is to investigate the general notion of timing in wireless communication systems and networks and its relation to effective information generation, processing, transmission, and reconstruction at the senders and receivers. We establish a general statistical framework of timing requirements in wireless communication systems, which subsumes both latency and AoI. The framework is made by associating a timing component with the two basic statistical operations, decision and estimation. We first use the framework to present a representative sample of the existing works that deal with timing in wireless communication. Next, it is shown how the framework can be used with different communication models of increasing complexity, starting from the basic Shannon one-way communication model and arriving to communication models for consensus, distributed learning, and inference. Overall, this paper fills an important gap in the literature by providing a systematic treatment of various timing measures in wireless communication and sets the basis for design and optimization for the next-generation real-time systems.

Device-to-device (D2D) underlaid cellular network, enabled with radio frequency energy harvesting (RFEH), and enhanced interference management schemes is a promising candidate to improve spectral and energy efficiency of next generation wireless networks. In this paper, we propose a time division duplexing (TDD)-based protocol, in which allows the devices to harvest energy from the downlink transmissions of the base station, while controlling the interference among D2D and cellular communication in the uplink. We propose two schemes for transmission coordination, based on fixed transmission probability (FTP) and adaptive transmission probability (ATP), respectively. In FTP, the D2D transmitters that have harvested enough energy can initiate data transmission with a fixed probability. Differently from this, in ATP a device utilizes its sensing capability to get improved coordination and interference control among the transmitting devices. We evaluate the network performance by presenting an accurate energy model and leveraging tools from stochastic geometry. The results on outage probability and D2D sum-rate reveal the importance of transmission coordination on network performance. These observations led to a solution for choosing the parameters of the ATP scheme that achieves an optimal tradeoff between the D2D outage probability and number of transmitting users.

When considering unidirectional communication for unmanned aerial vehicles (UAVs) as flying Base Stations (BSs), either uplink or downlink, the system is limited through the co-channel interference that takes place over line-of-sight (LoS) links. This paper considers two-way communication and takes advantage of the fact that the interference among the ground devices takes place through non-line-of-sight (NLoS) links. UAVs can be deployed at the high altitudes to have larger coverage, while the two-way communication allows to configure the transmission direction. Using these two levers, we show how the system throughput can be maximized for a given deployment of the ground devices., 10 pages, 3 figures, Submitted for publication

An important ingredient of the future 5G systems will be Ultra-Reliable Low-Latency Communication (URLLC). A way to offer URLLC without intervention in the baseband/PHY layer design is to use interface diversity and integrate multiple communication interfaces, each interface based on a different technology. In this work, we propose to use coding to seamlessly distribute coded payload and redundancy data across multiple available communication interfaces. We formulate an optimization problem to find the payload allocation weights that maximize the reliability at specific target latency values. In order to estimate the performance in terms of latency and reliability of such an integrated communication system, we propose an analysis framework that combines traditional reliability models with technology-specific latency probability distributions. Our model is capable to account for failure correlation among interfaces/technologies. By considering different scenarios, we find that optimized strategies can in some cases significantly outperform strategies based on $k$-out-of-$n$ erasure codes, where the latter do not account for the characteristics of the different interfaces. The model has been validated through simulation and is supported by experimental results., Accepted for IEEE Transactions on Communications

Ultra-reliable low latency communication (URLLC) is an important new feature brought by 5G, with a potential to support a vast set of applications that rely on mission-critical links. In this article, we first discuss the principles for supporting URLLC from the perspective of the traditional assumptions and models applied in communication/information theory. We then discuss how these principles are applied in various elements of the system design, such as use of various diversity sources, design of packets and access protocols. The important messages are that there is a need to optimize the transmission of signaling information, as well as a need for a lean use of various sources of diversity., Submitted to IEEE Network; Revised after 1st round of review; Title changed after 2nd review

Ultra-Reliable Low Latency Communication (URLLC) is one of the distinctive features of the upcoming 5G wireless communication, going down to packet error rates (PER) of $10^{-9}$. In this paper we discuss the statistical properties of the wireless channel models that are relevant for characterization of the lower tail of the Cumulative Distribution Function (CDF). We show that, for a wide range of channel models, the outage probability at URLLC levels can be approximated by a simple power law expression, whose exponent and offset depend on the actual channel model. The main insights from the analysis can be summarized as follows: (1) the two-wave model and the impact of shadowing in combined models lead to pessimistic predictions of the fading in the URLLC region; (2) the CDFs of models that contain single cluster diffuse components have slopes that correspond to the slope of a Rayleigh fading, and (3) multi-cluster diffuse components can result in different slopes. We apply our power law approximation results to analyze the performance of receiver diversity schemes for URLLC-relevant statistics and obtain a new simplified expression for Maximum Ratio Combining (MRC) in channels with power law tail statistics., Submitted to IEEE Transactions on Wireless Communications

We consider a monitoring application where sensors periodically report data to a common receiver in a time division multiplex fashion. The sensors are constrained by the limited and unpredictable energy availability provided by Energy Harvesting (EH), and by the channel impairments. To maximize the quality of the reported data, the packets transmitted contain newly generated data blocks together with up to $r - 1$ previously unsuccessfully delivered ones, where $r$ is a design parameter; such blocks are compressed, concatenated and encoded with a channel code. The scheme applies lossy compression, such that the fidelity of the individual blocks is traded with the reliability provided by the channel code. We show that the proposed strategy outperforms the one in which retransmissions are not allowed. We also investigate the tradeoff between the value of $r$, the compression and coding rates, under the constraints of the energy availability, and, once $r$ has been decided, use a Markov Decision Process (MDP) to optimize the compression/coding rates. Finally, we implement a reinforcement learning algorithm, through which devices can learn the optimal transmission policy without knowing a priori the statistics of the EH process, and show that it indeed reaches the performance obtained via MDP., Comment: Submitted to IEEE Transactions on Communications

An important novelty of 5G is its role in transforming the industrial production into Industry 4.0. Specifically, Ultra-Reliable Low Latency Communications (URLLC) will, in many cases, enable replacement of cables with wireless connections and bring freedom in designing and operating interconnected machines, robots, and devices. However, not all industrial links will be of URLLC type; e.g. some applications will require high data rates. Furthermore, these industrial networks will be highly heterogeneous, featuring various communication technologies. We consider network slicing as a mechanism to handle the diverse set of requirements to the network. We present methods for slicing deterministic and packet-switched industrial communication protocols at an abstraction level that is decoupled from the specific implementation of the underlying technologies. Finally, we show how network calculus can be used to assess the end-to-end properties of the network slices., Comment: Submitted to IEEE Network

We present a novel access protocol for crowd scenarios in massive MIMO (Multiple-input multiple-output) systems. Crowd scenarios are characterized by a large number of users with intermittent access behavior, whereby orthogonal scheduling is infeasible. In such scenarios, random access is a natural choice. The proposed access protocol relies on two essential properties of a massive MIMO system, namely asymptotic orthogonality between user channels and asymptotic invariance of channel powers. Signal processing techniques that take advantage of these properties allow us to view a set of contaminated pilot signals as a graph code on which iterative belief propagation can be performed. This makes it possible to decontaminate pilot signals and increase the throughput of the system. Numerical evaluations show that the proposed access protocol increases the throughput with 36%, when having 400 antennas at the base station, compared to the conventional method of slotted ALOHA. With 1024 antennas, the throughput is increased by 85%., arXiv admin note: text overlap with arXiv:1505.05726

We present a communication solution tailored specifically for DC microgrids (MGs) that exploits: (i) the communication potential residing in power electronic converters interfacing distributed generators to powerlines and (ii) the multiple access nature of the communication channel presented by powerlines. The communication is achieved by modulating the parameters of the primary control loop implemented by the converters, fostering execution of the upper layer control applications. We present the proposed solution in the context of the distributed optimal economic dispatch, where the generators periodically transmit information about their local generation capacity, and, simultaneously, using the properties of the multiple access channel, detect the aggregate generation capacity of the remote peers, with an aim of distributed computation of the optimal dispatch policy. We evaluate the potential of the proposed solution and illustrate its inherent trade-offs., Comment: Submitted to MACOM 2016

Applications enabled by Cooperative Intelligent Transport Systems (C-ITS) represent a major step towards making the road transport system safer and more efficient (green), and thus suited for a sustainable future. Wireless communication between vehicles and road infrastructure is an enabler for high-performance C-ITS applications. State-of-the-art communication systems for supporting low-latency C-ITS applications are based on IEEE 802.11 medium access control (MAC) and physical (PHY) layers. In this paper, we argue that a well-designed 5G system can complement or even replace these systems. We will review the C-ITS application requirements and explain how these are well aligned with the foreseen generic 5G service of ultra-reliable machine-type communication (uMTC). Key technology components suitable for constructing the uMTC service are identified: reliable service composition (RSC) and device-to-device (D2D) links for all-to-all broadcast communication, operational at high mobility and with varying degree of network assistance. Important problems for future studies, including radio-resource management, medium access control, and physical layer challenges, are discussed., Comment: Fixed typos. Last paragraph of Sec. 3 modified to stress applicability to V2X comm. Submitted to IEEE Communications Magazine, July 2015

This paper analyzes two-tier heterogeneous cellular network with decoupled downlink and uplink access. The basic performance benefits of uplink/downlink decoupling have been recently introduced. Here we provide a more elaborate treatment of the decoupling mechanism by analyzing spectral and energy efficiency of the system, as the joint improvement of these two features is crucial for the upcoming 5G systems. Contrary to the common assumption of a homogeneous user domain, we analyze two-tier user domain, whose transmit powers depend purely on the association process. The derived joint association probabilities and the distributions of the distance to the serving base station give deeper insight into the fundamentals of a system with decoupled access. The rigorous theoretical analysis shows that decoupling of downlink and uplink with two-level uplink power adaptation improves both, spectral and energy efficiency of the system., 6 pages; 6 figures; Submitted to the IEEE International Conference on Communications (ICC 2015)

Our traditional notion of a cell is changing dramatically given the increasing degree of heterogeneity in 4G and emerging 5G systems. Rather than belonging to a specific cell, a device would choose the most suitable connection from the plethora of connections available. In such a setting, given the transmission powers differ significantly between downlink (DL) and uplink (UL), a wireless device that sees multiple Base Stations (BSs) may access the infrastructure in a way that it receives the downlink (DL) traffic from one BS and sends uplink (UL) traffic through another BS. This situation is referred to as Downlink and Uplink Decoupling (DUDe). In this paper, the capacity and throughput gains brought by decoupling are rigorously derived using stochastic geometry. Theoretical findings are then corroborated by means of simulation results. A further constituent of this paper is the verification of the theoretically derived results by means of a real-world system simulation platform. Despite theoretical assumptions differing from the very complete system simulator, the trends in the association probabilities and capacity gains are similar. Based on the promising results, we then outline architectural changes needed to facilitate the decoupling of DL and UL., Comment: 26 pages, 10 figures, submitted to IEEE Transactions on Wireless Communications

Wireless cellular networks feature two emerging technological trends. The first is the direct Device-to-Device (D2D) communications, which enables direct links between the wireless devices that reutilize the cellular spectrum and radio interface. The second is that of Machine-Type Communications (MTC), where the objective is to attach a large number of low-rate low-power devices, termed Machine-Type Devices (MTDs) to the cellular network. MTDs pose new challenges to the cellular network, one if which is that the low transmission power can lead to outage problems for the cell-edge devices. Another issue imminent to MTC is the \emph{massive access} that can lead to overload of the radio interface. In this paper we explore the opportunity opened by D2D links for supporting MTDs, since it can be desirable to carry the MTC traffic not through direct links to a Base Station, but through a nearby relay. MTC is modeled as a fixed-rate traffic with an outage requirement. We propose two network-assisted D2D schemes that enable the cooperation between MTDs and standard cellular devices, thereby meeting the MTC outage requirements while maximizing the rate of the broadband services for the other devices. The proposed schemes apply the principles Opportunistic Interference Cancellation and the Cognitive Radio's underlaying. We show through analysis and numerical results the gains of the proposed schemes., 12 Pages, 9 Figures, Submitted to JSAC "Device-to-Device Communications in Cellular Networks" on the 20th of May 2013

Two-way relaying in wireless systems has initiated a large research effort during the past few years. While one-way relay with a single data flow introduces loss in spectral efficiency due to its half-duplex operation, two-way relaying based on wireless network coding regains part of this loss by simultaneously processing the two data flows. In a broader perspective, the two-way traffic pattern is rather limited and it is of interest to investigate other traffic patterns where such a simultaneous processing of information flows can bring performance advantage. In this paper we consider a scenario beyond the usual two-way relaying: a four-way relaying, where each of the two Mobile Stations (MSs) has a two-way connection to the same Base Station (BS), while each connection is through a dedicated Relay Station (RS). While both RSs are in the range of the same BS, they are assumed to have antipodal positions within the cell, such that they do not interfere with each other. We introduce and analyze a two-phase transmission scheme to serve the four-way traffic pattern defined in this scenario. Each phase consists of combined broadcast and multiple access. We analyze the achievable rate region of the new schemes for two different operational models for the RS, Decode-and-Forward (DF) and Amplify-and-Forward (AF), respectively. We compare the performance with a state-of-the-art reference scheme, time sharing is used between the two MSs, while each MS is served through a two-way relaying scheme. The results indicate that, when the RS operates in a DF mode, the achievable rate regions are significantly enlarged. On the other hand, for AF relaying, the gains are rather modest. The practical implication of the presented work is a novel insight on how to improve the spatial reuse in wireless cellular networks by coordinating the transmissions of the antipodal relays., 20 pages,10 figures

We use the term protocol coding to denote the communication strategies in which information is encoded through the actions taken by a certain communication protocol. In this work we investigate strategies for protocol coding via combinatorial ordering of the labelled user resources (packets, channels) in an existing, primary system. This introduces a new, secondary communication channel in the existing system, which has been considered in the prior work exclusively in a steganographic context. Instead, we focus on the use of secondary channel for reliable communication with newly introduced secondary devices, that are low-complexity versions of the primary devices, capable only to decode the robustly encoded header information in the primary signals. In Part I of the work we have characterized the capacity of the secondary channel through information-theoretic analysis. In this paper we consider practical strategies for protocol coding inspired by the information-theoretic analysis. It turns out that the insights from Part I are instrumental for devising superior design of error-control codes. This is demonstrated by comparing the error performance to the "na"{\i}ve" strategy which is presumably available without carrying out the analysis in Part I. These results are clearly outlining both the conceptual novelty behind the discussed concept of secondary channel as well as its practical applicability., Comment: Submitted to IEEE Trans. Communications

The vast existing wireless infrastructure features a variety of systems and standards. It is of significant practical value to introduce new features and devices without changing the physical layer/hardware infrastructure, but upgrade it only in software. A way to achieve it is to apply protocol coding: encode information in the actions taken by a certain (existing) communication protocol. In this work we investigate strategies for protocol coding via combinatorial ordering of the labelled user resources (packets, channels) in an existing, primary system. Such a protocol coding introduces a new secondary communication channel in the existing system, which has been considered in the prior work exclusively in a steganographic context. Instead, we focus on the use of secondary channel for reliable communication with newly introduced secondary devices, that are low-complexity versions of the primary devices, capable only to decode the robustly encoded header information in the primary signals. We introduce a suitable communication model, capable to capture the constraints that the primary system operation puts on protocol coding. We have derived the capacity of the secondary channel under arbitrary error models. The insights from the information-theoretic analysis are used in Part II of this work to design practical error-correcting mechanisms for secondary channels with protocol coding., Comment: Submitted to IEEE Trans. Communications. arXiv admin note: text overlap with arXiv:1011.5739

This paper concerns application of feedback in LT codes. The considered type of feedback is acknowledgments, where information on which symbols have been decoded is given to the transmitter. We identify an important adaptive mechanism in standard LT codes, which is crucial to their ability to perform well under any channel conditions. We show how precipitate application of acknowledgments can interfere with this adaptive mechanism and lead to significant performance degradation. Moreover, our analysis reveals that even sensible use of acknowledgments has very low potential in standard LT codes. Motivated by this, we analyze the impact of acknowledgments on multi layer LT codes, i.e. LT codes with unequal error protection. In this case, feedback proves advantageous. We show that by using only a single feedback message, it is possible to achieve a noticeable performance improvement compared to standard LT codes.

While there are continuous efforts to introduce new communication systems and standards, it is legitimate to ask the question: how can one send additional bits by minimally changing the systems that are already operating? This is of a significant practical interest, since it has a potential to generate additional value of the systems through, for example, introduction of new devices and only a software update of the access points or base stations, without incurring additional cost for infrastructure hardware installation. The place to look for such an opportunity is the communication protocol and we use the term *protocol coding* to refer to strategies for sending information by using the degrees of freedom available when one needs to decide the actions taken by a particular communication protocol. In this paper we consider protocol coding that gives a rise to *secondary communication channels*, defined by combinatorial ordering of the user resources (packets, channels) in a primary (legacy) communication system. We introduce communication models that enable us to compute the capacity of such secondary channels under suitable restrictions imposed by the primary systems. We first show the relation to the capacity of channels with causal channel state information at the transmitter (CSIT), originally considered by Shannon. By using the specific communication setup, we develop an alternative framework for achieving the capacity and we discuss coding strategies that need to be used over the secondary channels. We also discuss some practical features of the secondary channels and their applications that add value to the existing wireless systems., Replaced with a two-part paper

A cognitive radio can operate as a secondary system in a given spectrum. This operation should use limited power in order not to disturb the communication by primary spectrum user. Under such conditions, in this paper we investigate how to maximize the spectral efficiency in the secondary system. A secondary receiver observes a multiple access channel of two users, the secondary and the primary transmitter, respectively. We show that, for spectrally-efficient operation, the secondary system should apply Opportunistic Interference Cancellation (OIC). With OIC, the secondary system decodes the primary signal when such an opportunity is created by the primary rate and the power received from the primary system. For such an operation, we derive the achievable data rate in the secondary system. When the primary signal is decodable, we devise a method, based on superposition coding, by which the secondary system can achieve the maximal possible rate. Finally, we investigate the power allocation in the secondary system when multiple channels are used. We show that the optimal power allocation with OIC can be achieved through intercepted water-filling instead of the conventional water-filling. The results show a significant gain for the rate achieved through an opportunistic interference cancellation., Comment: submitted to IEEE Journal on Selected Areas in Communications "Cognitive Radio: Theory and Applications", March 2007