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This letter presents sufficient conditions for the existence and uniqueness of the limiting stationary distribution in random access Poisson networks with packet queueing and under Rayleigh fading and a general path loss model. This system model is traditionally used in the literature assuming uniqueness of the stationary distribution. We demonstrate here through a counterexample that this assumption might not always hold. From the sufficient conditions, an interesting and perhaps counterintuitive result emerged, that is, the arrival rate of packets per node greater than 1/e guarantees uniqueness of the limiting distribution. When that is the case, then setting the medium access probability to 1 minimizes the proportion of unstable nodes.

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.

A wireless network with unsaturated traffic and N classes of users sharing a channel under random access is analyzed here. Necessary and sufficient conditions for the network stability are derived, along with simple closed formulas for the stationary packet transmission success probabilities and mean packet delays for all classes under stability conditions. We also show, through simple and elegant expressions, that the channel sharing mechanism in the investigated scenario can be seen as a process of partitioning a well-defined quantity into portions, each portion assigned to each user class, the size of which determined by system parameters and performance metrics of that user class. Using the derived expressions, optimization problems are then formulated and solved to minimize the mean packet delay and to maximize the channel throughput per unit of area. These results indicate that the proposed analysis is capable of assessing the trade-off involved in radio-resource management when different classes of users are considered.

Internet of Things (IoT) is pushing the Internet to the next level, bringing the number of connected devices to an unprecedented amount, creating new services and improving old services like the metering system. The advanced meter infrastructure (AMI) measures, collects and analyzes the distribution and consumption of utilities such as water, electricity, and gas, which are of vital importance for the implementation of smart cities. In this paper, we employ LoRa, which is a low power wide area network technology (LPWAN), for the communication of meter devices and network server, and we study the coexistence of two kinds of messages: regular and alarm events. Our focus is on the analysis of the alarm events, which can be characterized by emergency situations and require ultra-reliability. We investigated the feasibility of the alarms for a smart metering scenario through simulation campaigns and a mathematical model. By assigning a different spreading factor (SF) to the device depending on whether the event is regular or alarm, we assessed the system performance. We evaluate the availability, reliability, and quantity of alarms that satisfy the restricted requirements of alarms events and do not compromise the performance of regular events. The best performance for regular events at SF-7 was obtained when alarm events are allocated to SF-8, whereas the other combinations are affected for a stronger interference.

This paper analyzes the feasibility of the coexistence of telemetry and alarm messages employing Long-Range Wide-Area Network (LoRaWAN) technology in industrial environments. The regular telemetry messages come from periodic measurements from the majority of sensors while the alarm messages come from sensors whose transmissions are triggered by rarer (random) events that require highly reliable communication. To reach such a strict requirement, we propose here strategies of allocation of spreading factor, by treating alarm and regular (telemetry) messages differently. The potential of such allocation strategies has also been investigated under retransmission and diversity of gateways. Both indoor industrial plant and open-field scenarios are investigated. We compare the proposed solution with a benchmark scenario&mdash, where no alarm is considered&mdash, by using system level simulation. Our results show that it is possible to achieve high reliability with reasonably low delay for the alarm messages without significantly affecting the performance of the regular links.

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.

A simple analytical solution is proposed for the stationary loss system of two parallel queues with finite capacity K, in which new customers join the shortest queue, or one of the two with equal probability if their lengths are equal. The arrival process is Poisson, service times at each queue have exponential distributions with the same parameter, and both queues have equal capacity. Using standard generating function arguments, a simple expression for the blocking probability is derived, which as far as we know is original. Using coupling arguments and explicit formulas, comparisons with related loss systems are then provided. Bounds are similarly obtained for the average total number of customers, with the stationary distribution explicitly determined on $$\{K, \ldots , 2K \}$$ , and elsewhere upper bounded. Furthermore, from the balance equations, all stationary probabilities are obtained as explicit combinations of their values at states (0, k) for $$0 \le k \le K$$ . These expressions extend to the infinite capacity and asymmetric cases, i.e., when the queues have different service rates. For the initial symmetric finite capacity model, the stationary probabilities of states (0, k) can be obtained recursively from the blocking probability. In the other cases, they are implicitly determined through a functional equation that characterizes their generating function. The whole approach shows that the stationary distribution of the infinite capacity symmetric process is the limit of the corresponding finite capacity distributions. Finally, application of the results for limited capacity to mean-field models for large bike-sharing networks with a local JSQ policy is briefly discussed.