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. INDEX TERMS Design optimization, queueing analysis, stochastic processes, wireless networks.

Abstract. 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, . . . , 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 ≤ k ≤ 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. For the infinite capacity symmetric model, we provide an elementary proof of a result by Cohen which gives the solution of the functional equation in terms of an infinite product with explicit zeroes and poles.

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—where no alarm is considered—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.

The demand for wireless connectivity has grown exponentially over the last years. By 2030 there should be around 17 billion of mobile-connected devices, with monthly data traffic in the order of thousands of exabytes. Although the Fifth Generation (5G) communications systems present far more features than Fourth Generation (4G) systems, they will not be able to serve this growing demand and the requirements of innovative use cases. Therefore, Sixth Generation (6G) Networks are expected to support such massive connectivity and guarantee an increase in performance and quality of service for all users. To deal with such requirements, several technical issues need to be addressed, including novel multiple-antenna technologies. Then, this survey gives a concise review of the main emerging Multiple-Input Multiple-Output (MIMO) technologies for 6G Networks such as massive MIMO (mMIMO), extremely large MIMO (XL-MIMO), Intelligent Reflecting Surfaces (IRS), and Cell-Free mMIMO (CF-mMIMO). Moreover, we present a discussion on how some of the expected key performance indicators (KPIs) of some novel 6G Network use cases can be met with the development of each MIMO technology.

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