We study the remote monitoring of two-state Markov sources over a shared wireless channel with destructive collisions. System performance is measured in terms of state estimation entropy (SEE) and state estimation error probability (SEEP), which quantify the receiver's uncertainty and decision error regarding the source state, respectively. We consider two transmission policies: a random strategy, where nodes access the channel independently of their state, and a reactive strategy, where transmissions occur only upon state changes. Our main contribution is a simple and explicit analytical characterization of the long-term average SEE and SEEP under both policies using a renewal–reward framework, alternative to the density evolution approach introduced in [1]. For random transmission, both metrics admit closed-form representations as expectations over the geometric steady-state age-of-information distribution. For reactive transmission, we show that estimation uncertainty and error accumulate exclusively through collision events, and derive their long-term averages via a collision-indexed Markov reward recursion.

We show that the probability distribution of the error exponent in i.i.d. code ensembles over classical-quantum (CQ) channels with arbitrary output states accumulates above a threshold that is strictly larger than the CQ random coding exponent (RCE) at low rates, while coinciding with it at rates close to the mutual information of the channel. This result, combined with the work by Dalai [1] and the recent ones by Renes [2] and Li and Yang [3], implies that the ensemble distribution of error exponents concentrates around the CQ RCE in the high rate regime. Moreover, in the same rate regime the threshold we derive coincides with the ensemble-average of the exponent, that is, the typical random coding (TRC) exponent [4].

We show that for a wide range of channels and code ensembles with pairwise-independent codewords, with probability tending to 1 with the code length, expurgating an arbitrarily small fraction of codewords from a randomly selected code results in a code attaining the expurgated exponent.

The statement of Theorem 1 in [1] should have read as follows.

We study a system in which terminals monitoring two-state Markov sources communicate towards a common receiver over a slotted ALOHA random access channel. We analyze the system performance in terms of state estimation entropy (SEE), which measures the uncertainty at the receiver about the sources’ state. Two channel access strategies are studied, one that is influenced by the source behaviour and one that is independent of it. By means of density evolution analysis, we show that the former can yield a remarkable reduction of the SEE.

This paper shows that the probability that the error exponent of a given code randomly generated from a pairwise-independent ensemble is smaller than a lower bound on the typical random-coding exponent tends to zero as the codeword length tends to infinity. This lower bound is known to be tight for i.i.d. ensembles over the binary symmetric channel and for constant-composition codes over memoryless channels. Our results recover both as special cases and remain valid for arbitrary alphabets, arbitrary channels—for example finite-state channels with memory—, and arbitrary pairwise-independent ensembles. We specialize our results to the i.i.d., constant-composition and cost-constrained ensembles over discrete memoryless channels and to ensembles over finite-state channels.

This paper shows that, for discrete memoryless channels, the error exponent of a randomly generated code with independent codewords converges in probability to its expectation—the typical error exponent. For high rates, the result follows from the fact that the random-coding error exponent and the sphere-packing error exponent coincide. For low rates, instead, the convergence is based on the fact that the union bound accurately characterizes the error probability. The paper also zooms into the behavior at asymptotically low rates, and shows that the normalized error exponent converges in distribution to the standard Gaussian or a Gaussian-like distribution. We also state several results on the convergence of the error probability and error exponent for generic ensembles and channels.

We derive a lower bound on the typical random-coding (TRC) exponent of pairwise-independent codeword ensembles used over a finite-state channel (FSC) at rates below capacity. Under some conditions, we also show that the probability of selecting a code from the ensemble with an error exponent larger than our lower bound tends to one as the codeword length tends to infinity. Our result, presented here for the FSC, also applies to compound channels.

We study the convergence in distribution of the error exponent of random codes, defined as the negative normalized logarithm of the probability of error, of both i.i.d. and constant-composition ensembles over discrete memoryless channels. For a constant number of messages, the distribution of the error exponent converges to that of the minimum of a set of independent normal random variables. For an increasing sub-exponential number of messages, the error exponent converges to a normal distribution, independent of the number of messages. As a byproduct, we provide a new method to prove the convergence to a normal distribution of an infinite number of random variables based on a modification of the Wasserstein metric.

For random-coding ensembles with pairwise-independent codewords, we show that the probability that the exponent of a given code from the ensemble being smaller than an upper bound on the typical random-coding exponent is vanishingly small. This upper bound is known to be tight for i.i.d. ensembles over the binary symmetric channel and for constant-composition codes over memoryless channels. Our result recovers these as special cases and remains valid for arbitrary alphabets and channel memory, as well as arbitrary ensembles with pairwise independent codewords.

This paper studies the error exponent of i.i.d. randomly generated codes used for transmission over discrete memoryless channels with maximum likelihood decoding. Specifically, this paper shows that the error exponent of a code, defined as the negative normalized logarithm of the probability of error, converges in probability to the typical error exponent. For high rates, the result is a consequence of the fact that the random-coding error exponent and the sphere-packing error exponent coincide. For low rates, instead, the proof of convergence is based on the fact that the union bound accurately characterizes the probability of error.

Besides being part of the Internet of Things (IoT), drones can play a relevant role in it as enablers. The 3D mobility of UAVs can be exploited to improve node localization in IoT networks for, e.g., search and rescue or goods localization and tracking. One of the widespread IoT communication technologies is Long Range Wide Area Network (LoRaWAN), which allows achieving long communication distances with low power. In this work, we present a drone-aided localization system for LoRa networks in which a UAV is used to improve the estimation of a node's location initially provided by the network. We characterize the relevant parameters of the communication system and use them to develop and test a search algorithm in a realistic simulated scenario. We then move to the full implementation of a real system in which a drone is seamlessly integrated into Swisscom's LoRa network. The drone coordinates with the network with a two-way exchange of information which results in an accurate and fully autonomous localization system. The results obtained in our field tests show a ten-fold improvement in localization precision with respect to the estimation provided by the fixed network. Up to our knowledge, this is the first time a UAV is successfully integrated in a LoRa network to improve its localization accuracy.

Video streaming from remotely controlled moving platforms such as drones have stringent constraints in terms of delay. In some applications such videos have to provide real-time visual feedback to the pilot with an acceptable distortion while satisfying high-quality requirements at playback. Furthermore the output rate of the source encoder required to achieve a target distortion depends on the speed of the platform. Motivated by this, we consider a novel source model which takes the source speed into account and derive its rate-distortion region. A transmission strategy based on successive joint encoding, which efficiently takes the source correlation into account, is then considered for transmission over a block fading channel. Our numerical results show that such scheme largely enhances over an independent coding scheme in terms of on-line distortion while approaching the playback distortion performance of an optimal encoder as the group of pictures size grows.

We study the problem of caching optimization in heterogeneous networks with mutual interference and per-file rate constraints from an energy efficiency perspective. A setup is considered in which two cache-enabled transmitter nodes and a coordinator node serve two users. We analyze and compare two approaches: 1) a cooperative approach where each of the transmitters might serve either of the users and 2) a non-cooperative approach in which each transmitter serves only the respective user. We formulate the cache allocation optimization problem so that the overall system power consumption is minimized while the use of the link from the master node to the end users is spared whenever possible. We also propose a low-complexity optimization algorithm and show that it outperforms the considered benchmark strategies. Our results indicate that significant gains both in terms of power saving and sparing of master node's resources can be obtained when full cooperation between the transmitters is in place. Interestingly, we show that in some cases storing the most popular files is not the best solution from a power efficiency perspective.

Small cells will play an important role in the fifth generation mobile networks. As recent works pointed out, a significant improvement in energy efficiency can be obtained if small base stations (SBSs) are provided with storage capabilities. In this paper, we study the problem of caching optimization in the presence of interference with and without cooperation between the SBSs. We consider a setup in which two SBSs and one macro base station (MBS) are connected through a wireless backhaul link. Cooperation is applied following the Han-Kobayashi rate splitting approach and its variation including common information. Our results show that applying cooperation to caching systems yields significant gains in terms of power and provide indications on how much interference can be tolerated which, in turn, has impact on the network design both in terms of frequency reuse planning and SBS deployment.

We study a queueing system operated with packet level coding. More specifically, we derive a closed form upper bound on the queueing delay as well as an expression for the decoding delay of a system operated with systematic network coding. Unlike previous works, the delay is considered on a per-packet basis rather than per-block, thus taking into account the low-latency property of systematic codes. Furthermore we study the tradeoff between the coding gain and the decoding delay defining the “achievable” region (packet loss vs. delay) for finite block lengths.

This paper studies the sum throughput maximization of the return-link in multi-beam satellite systems. Considering bursty communication scenarios with different users' data request probabilities, we develop an efficient scheduling scheme using genetic algorithms (GAs). Moreover, we consider co-channel interference (CCI) and adjacent channel interference (ACI). We consider a receiver with and without interference cancelation. Using a simplified channel model, we evaluate the proposed scheduler in a multi-beam system. The proposed GA-based scheduler approaches the throughput of an optimal scheduler based on exhaustive search with substantially less implementation complexity.

We study video streaming over a slow-fading wireless channel. In a streaming application, video packets are required to be decoded and displayed in the order they are transmitted as the transmission goes on. This results in per-packet delay constraints, and the resulting channel can be modeled as a physically degraded fading broadcast channel with as many virtual users as the number of packets. In this paper, we study two important quality of user experience (QoE) metrics, namely throughput and interdecoding delay. We introduce several transmission schemes, and compare their throughput and maximum interdecoding delay performances. We also introduce a genie-aided scheme, which provides theoretical bounds on the achievable performance. We observe that adapting the transmission rate at the packet level, i.e., periodically dropping a subset of the packets, leads to a good tradeoff between the throughput and the maximum interdecoding delay. We also show that an approach based on initial buffering leads to an asymptotically vanishing packet loss rate at the expense of a relatively large initial delay. For this scheme, we derive a condition on the buffering time that leads to throughput maximization.

In a streaming application video packets are required to be decoded and displayed in the order they are transmitted as the transmission continues. This results in per-packet delay constraints, and in the wireless setting the resulting channel can be modeled as a physically degraded fading broadcast channel with as many virtual users as the number of packets. Two important quality of user experience (QoE) metrics, throughput and inter-decoding delay, are considered jointly, and lower and upper bounds on both metrics are presented.

Streaming transmission over a block fading channel is studied assuming that the transmitter receives a new message at each channel block at a constant rate, which is fixed by an underlying application. A common deadline is assumed for all the messages, at which point the receiver tries to decode as many messages as possible. Various achievable schemes are proposed and compared with an informed transmitter upper bound in terms of average throughput. It is shown that the adaptive joint encoding (aJE) scheme is asymptotically optimal; that is, it achieves the ergodic capacity as the transmission deadline goes to infinity; and it closely follows the upper bound in the case of a finite transmission deadline. On the other hand, in the presence of multiple receivers with different signal-to-noise ratios (SNR), memoryless transmission (MT), generalized time-sharing (gTS) and superposition transmission (ST) schemes are shown to be more robust than the joint encoding (JE) scheme as they have gradual performance degradation with the decreasing SNR.

We propose two new protocols based on physical layer network coding for collision resolution in multiple access networks. When a collision occurs the receiver decodes the sum of the collided packets and after a number of transmissions, equal to or slightly higher than the number of original packets, it can recover all of them. One of the proposed protocols based on fountain codes can resolve collisions by sending out just one acknowledgement (ACK), thus being particularly suited to networks with large round trip delays such as satellite networks. We carry out a comparison of the average delay achieved by the proposed schemes with other access techniques, and show how the performance can be improved with little coordination at the receiver.

We consider the two-way relay channel with random access for the cases of symmetric and asymmetric channel statistics in the low SNR regime. We propose three different schemes implementing different physical layer techniques for collision recovery and channel adaptation and obtain analytical throughput expressions. We compare the proposed schemes with several benchmarks in order to study their bandwidth gains in practical scenarios.

Two new schemes are proposed for collision resolution in slotted ALOHA networks based on multi-user physical-layer network coding (MU PHY NC). In the proposed random access schemes, a collision of a generic number of packets can be recovered decoding the XOR of the original messages, such that the signal resulting from the collision is exploited rather than being discarded. Two different schemes that differ in terms of the amount of control information that needs to be transmitted from the access point, are studied.