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 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.

Abstract Device‐to‐device (D2D) communication has attracted a great deal of attention in the last few years due to its potential to enhance wireless network capacity and reduce energy consumption, among other benefits. Here, the problem of maximisation of the performance of a D2D network in a scenario in which D2D users share communication channels with users of a cellular network is investigated. Using stochastic geometry tools, the problems of maximisation of the performance metrics area spectral efficiency (ASE) and energy efficiency (EE) of the D2D network by adjusting the density, transmit power, and link throughput of D2D users are formulated and solved. The maximisation of ASE and EE is performed by imposing that the successful transmission probabilities of both D2D and cellular networks are not below given minimum acceptable levels. Based on the derived formulation, the effects of several parameters on the network performance are assessed. The study shows the existence of three possible operating regimes for the D2D network, according to the behaviours (increasing or decreasing) of ASE and EE when the quality of the D2D links increases.

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.

Cognitive radio technology enables two wireless networks, namely a primary network and a secondary network, to operate in the same geographic region sharing the same spectrum. Primary users have priority to access the spectrum without taking into account the presence of secondary users, while secondary users have to limit their interference in order not to disturb the operation of primary users. This work analyses a cognitive network in which the secondary network can adapt its parameters, in order to exploit any available opportunity for secondary capacity improvement, under the restriction that these adjustments cannot cause any additional harm to primary users. Using Poisson point process modelling, the authors present a closed‐form formulation to adjust the secondary modulation order, user density, and transmit power, in order to maximise the secondary capacity, without causing any additional disturbance to primary users, and keeping the quality of secondary transmissions above a minimum acceptable level. The formulation proposed allows us to gain meaningful insights regarding the interrelationship involving some network parameters and performance metrics.

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.

The problem of throughput optimization in decentralized wireless networks with spatial randomness under queue stability and packet loss constraints is investigated in this paper. Two key performance measures are analyzed, namely the effective link throughput and the network spatial throughput. Specifically, the tuple of medium access probability, coding rate, and maximum number of retransmissions that maximize each throughput metric is analytically derived for a class of Poisson networks, in which packets arrive at the transmitters following a geometrical distribution. Necessary conditions so that the effective link throughput and the network spatial throughput are stable and achievable under bounded packet loss are determined, as well as upper bounds for both cases by considering the unconstrained optimization problem. Our results show in which system configuration stable achievable throughput can be obtained as a function of the network density and the arrival rate. They also evince conditions for which the per-link throughput-maximizing operating points coincide or not with the aggregate network throughput-maximizing operating regime.

Results of measurement campaigns carried out aiming at the development of a tool for design, deployment, and analysis of RFID systems are shown. Particularly, in this paper, the radio path loss from an RFID reader towards the test tag and back to the reader is characterized at the 915 MHz band. The path loss is estimated based on the received signal strength measured at the reader, for different reader-tag separation distances and different antenna tag heights. Several propagation scenarios have been considered, including outdoor and indoor environments for which an extensive number of typical real manufacturing plants have been chosen. The field data are then compared to a proposed novel, improved version of the classical 2-ray path loss model, adjusted to also include the non-omnidirectional antenna radiation patterns at the reader and tag sides. To the best of the authors' knowledge, the scope and reach of the measurements as well as the proposed path loss model are new.

This paper introduces a novel approach to evaluate the performance of ad hoc networks based on their spatial capacity, defined as the maximum spatial spectral efficiency supported by the network while a zero outage probability is guaranteed for all communication links. Specifically, the spatial capacity together with upper and lower bounds is derived in closed-form for networks where transmitters follow a Poisson point process and their respective receivers are located at a fixed distance. In this scenario, the spatial capacity is achieved using a rate adaptation technique that adjusts the link spectral efficiency in accordance with the distance between the receivers and their closest interferers. Besides, the spatial capacity is analytically proved to be always greater than or equal to the maximum spatial spectral efficiency achieved when a fixed spectral efficiency and an unbounded outage probability are considered. Numerical results show that the spatial-capacity-achieving setting leads to a spatial spectral efficiency about 125% higher than the one reached with the fixed spectral efficiency strategy.

In this paper, a new measure of outage-constrained network area spectral efficiency, coined as stable transmission capacity, is introduced, which is achievable under finite delay and queue-length stability. Specifically, this framework extends the transmission capacity formulation to scenarios with packet retransmissions and transmitters' queues with independent packet arrivals. This approach is applied to single-hop wireless networks with nodes being spatially distributed as Poisson point process, slotted ALOHA medium access protocol, packet arrivals following a geometrical distribution, and bounded number of retransmissions. The stable transmission capacity is then obtained as the solution of a constrained optimization problem with respect to the probability that a transmitter access the network, the link spectral efficiency, and the maximum number of retransmissions. Using the unconstrained stable transmission capacity as an upper bound, it is shown under which operating points and network parameters such limit can be achieved. Our numerical results also evince how the spatial density and the arrival process affect the network performance.

In this work we investigate whether it is preferable to have a large number of short single-hop links or a small number of long single-hops in a multi-hop wireless network. We derive analytical expressions to compute the metric aggregate multi-hop information efficiency under different hopping strategies, and analyze the trade-off involving robustness of single-hop links, interference and hopping strategy.

In this paper we investigate the transmission capacity of wireless networks when packet retransmissions are allowed. We consider networks modeled as a homogeneous Poisson point process operating under different medium access control schemes, namely unslotted and slotted ALOHA, and CSMA with carrier sensing at the transmitter and with carrier sensing at the receiver. For these scenarios, we derive analytical expressions to compute the maximum number of retransmissions attempts that leads to the optimal transmission capacity. Numerical results based on our formulation show that CSMA with carrier sensing at the receiver (asynchronous transmissions) reaches the highest maximum transmission capacity when traffic intensity is low, while slotted ALOHA (synchronous transmissions) is the best choice when traffic intensity is high.

We introduce multi-hop aggregate information efficiency (MIEA), a comprehensive metric that captures several performance-affecting factors of wireless ad hoc networks in a unified formulation. This metric is then employed to analyze such networks with respect to their spectral efficiencies, network loads, and hopping strategies. The analysis reveals that the hopping strategy that achieves maximum information efficiency is that of multiple short hops with no more than a single packet retransmission allowed at each hop, as opposed to the alternative of fewer long-haul hops with multiple packet retransmissions. The implementation of that preferred strategy withstanding, it is found furthermore that the most efficient networks typically exhibit about 65 % of link outage probability, which corroborates similar findings obtained in different network settings and using different metrics. Bearing in mind that link outage is a function not only of deterministic parameters such as node density, but also of design parameters such as modulation, our analysis also shows that the modulation scheme that optimizes the aggregate information efficiency is in fact a function of node density. In that respect, our metric and method is shown to be useful to determining the modulation scheme that optimizes the performance of a network with a certain node density.

In this paper we evaluate the effects of modulation and coding schemes on the performance of ad hoc networks. The analysis is based on analytical expressions derived for the aggregate information efficiency and the average packet delay in ad hoc networks. Modulation and error correcting coding directly affect the trade-offs involving spectral efficiency, interference immunity and channel reuse in a wireless network. Results of numerical analysis show that lower modulation orders and high coding rates are preferable when one wants to maximize the aggregate information efficiency and minimize the average packet delay.

The performance analysis of multihop wireless networks requires appropriate performance measures in order to take into consideration the intrinsic characteristics of this type of networks. The information efficiency is a measure of how efficiently bits of information are transmitted in multihop networks. In this paper we investigate the performance of a multihop network, by evaluating its total information efficiency, defined as the sum of the amount of information efficiency of all active one-hop links at a given time. By using the total information efficiency as a performance measure, we are able to evaluate the effects of channel reuse throughout the network and analyze the resulting tradeoffs involving different modulation schemes, different transmission ranges and the propagation effects.

Spatial division multiple access (SDMA) is recognized as a promising technique for improving capacity in future cellular systems, by exploiting the spatial filtering capability of adaptive antennas. In SDMA systems, in-cell users can share the same channel, making the channel allocation strategy play an important role in the system performance. In this paper, we analyze by simulation different strategies for channel allocation in cellular systems employing adaptive antennas and SDMA technique. Results show that high performance in SDMA systems is achieved by balancing channel reuse among cells with channel reuse within cells. Attempts to maximize channel reuse within cells may increase excessively cochannel interference, limiting capacity. Results also show that, while carried traffic is not severely affected by high level of user mobility, other performance parameters, such as the number of channel reassignment requests, are strongly affected by user mobility.

Summary Co-channel interference is recognized as one of the major factors that limits the capacity and link quality of a wireless communications system. An appropriate understanding of the statistical behavior of the co-channel interference is therefore required when analyzing and designing techniques that mitigate its undesired effects. The total co-channel interference in a wireless communications system is usually modeled as the sum of lognormally distributed signals, and is generally assumed to be itself lognormally distributed. Based on this assumption, several methods for estimating the moments of the resulting lognormal distribution have been proposed. The accuracy of these methods has been studied in previous works, under the assumption of having all summand signals (individual interference signals) identically distributed. Such an assumption rarely holds in practical cases of emerging wireless communications systems, where co-channel interference may stem from far-away macrocells and nearby transmitters, causing the interference signals to have different moments. In this paper we present an analysis of the accuracy of two popular methods for computing the moments of a sum of lognormal random variables, namely Wilkinson’s method and Schwartz and Yeh’s method, for the general case when the summands have different mean values and standard deviations in decibel units. We show that Schwartz and Yeh’s method provides better accuracy than Wilkinson’s method and is virtually invariant with the difference of the mean values and standard deviations of the summands. Copyright © 2001 John Wiley & Sons, Ltd.