This paper presentssharpinequalities for the level crossing rate of a stochastic process composed of the product of independent stochastic processes. The inequalities, which are simple to state, enlighten the contribution of each process individually. Additionally, we derive an exact formulation when the conditioned pointwise derivative of each process follows a Gaussian distribution. As application examples, the results are exercised in different scenarios using the$\alpha\text{-}\mu $and$\kappa\text{-}\mu$fading models, which encompass several other well-known models such as Semi-Gaussian, Rayleigh, Rice, Nakagami-m, and Weibull. We provide unprecedented closed-form formulations for the level crossing rate bounds of the product of these widely-known fading processes. Notably, there are no closed forms for the level crossing rate of these products. Therefore, our bounds supply a benchmark for this metric, with one of them serving as an excellent approximation of the exact metric.

This work introduces a new perspective for physical media sharing and radio access in multiuser communication by jointly considering (i) the meaning of the transmitted message and (ii) its function at the end user. Specifically, we have defined a scenario where multiple users (sensors) employ an event-trigger transmission scheme to communicate their own state value concerning a predetermined event. On the receiver side, there is an alarm monitoring system, whose function is to decide whether such a predetermined event has happened in a certain time period and, if yes, in relation to which user. The proposed solution leverages the lack of explicit use of a predetermined spectrum resource – which defines an energy slot – to infer that no event has happened, thus building an implicit communication channel. When an event occurs at a given sensor, a sequence of “use” and “lack of use” instances for such a spectrum resource will be transmitted as a sequence of “on” and “off” values with respect to the occupancy of the energy slot. The receiver’s role is to detect such a sequence to identify that an event has happened and in which sensor. This direct map from the data acquisition to the transmission is the basis of semantic-functional communication. The challenge of this scheme is to construct a coding–decoding scheme where the receiver can effectively recover the states of the different sensors (in terms of the occurrence of the events) with high fidelity. We have demonstrated the high efficacy of the proposed nonorthogonal solution when the transmitters select a random code, and the receiver only detects whether the energy slot is used (i.e., there is no actual demodulation so that there is no packet collision when two or more sensors are transmitting). We have shown the proposed method leads to a better event transmission efficiency than an adaptation of well-known techniques like the orthogonal-based TDMA and the random-access-based slotted ALOHA when the same number of limited resources is employed. Remarkably, for almost all studied cases, the proposed method asymptotically achieves 100% efficiency and 0% error probability, while consistently outperforming TDMA and slotted ALOHA variations.

This paper presents new analytical results for evaluating the ALOHA-like multi-class random access wireless network’s performance. The proposed model is motivated by the growth of low-power wireless networks that employ random access protocols. In particular, we compare our analytical formulation with system-level simulations of Long Range (LoRa) technology. We show that the proposed formulation provides an accurate approximation of LoRaWAN performance capturing its main trade-offs. The main contributions are (i) an extensive analysis of the impact of different LoRa spreading factors (SFs) allocation strategies, including area intersection among SFs, which is little explored in the literature and represents the optimal approach under some conditions; and (ii) the optimal proportion of users that maximizes the network throughput for each class and for each allocation strategy considered in the paper.

This paper investigates the performance of a wireless network that consists of two pairs of transmitter-receiver sharing the same channel, modeled using two coupled queues. In this analysis, we use the power metric \mathscr P, defined as the ratio of throughput and mean delay, to understand the compromise between these two metrics. We show that, when the users' transmit power levels are adjusted to maximize \mathscr P, two transmission regimes emerge. When the coupling degree between the queues is strong, but the traffic is not heavy, there will be plenty of opportunities for non-concurrent transmissions. Our analysis shows that, in this case, the best strategy is to prioritize one user over the other through appropriate transmit powers adjustment and to use the highest modulation order available. On the other hand, for heavy traffic, none of the users should be prioritized, and there is an optimum combination of robust modulation orders and transmit power ratio to achieve the best performance.

The paper deals with load balancing between one-server queues on a circle by a local choice policy. Each one-server queue has a Poissonian arrival of customers. When a customer arrives at a queue, he joins the least loaded queue between this queue and the next one, ties solved at random. Service times have exponential distribution. The system is stable if the arrival-to-service rate ratio called load is less than one. When the load tends to zero, we derive the first terms of the expansion in this parameter for the stationary probabilities that a queue has 0 to 3 customers. We investigate the error, comparing these expansion results to numerical values obtained by simulations. Then we provide the asymptotics, as the load tends to zero, for the stationary probabilities of the queue length, for a fixed number of queues. It quantifies the difference between policies with this local choice, no choice and the choice between two queues chosen at random.

Machine-to-Machine communication (M2M) or machine type communication (MTC) is the form of communication in which devices communicate with each other and with servers on the Internet without human intervention, defining the new concept known as Internet of Things (IoT). The machine type communication generates a lot of new services and, with them, big problems and challenges that must be addressed. A major challenge is to define the behavior of a new traffic generated by the devices, that is the goal of this work. We propose a traffic model for the uplink traffic, which is composed of deterministic and stochastic parts, and perform a study of throughput, delay and packet loss for this uplink traffic in a central node of the wireless sensor network.