With the recent outbreak of the COVID-19 pandemic, major industries and academic institutions throughout the world have moved into a work-from-home situation, which resulted in a huge demand for networking resources. In particular, several home users are demanding simultaneously high data rates to support online video streaming applications, like Webex and Zoom. Therefore, it is expected that in these situations the quality of experience of online users may be severely affected or deteriorated, especially as the number of simultaneous active online users increases. In this paper, we use the Neyman-Scott Cluster Process from Stochastic Geometry to model the spatial patterns of online home users and analyze the throughput that could be achieved by a various numbers of online home users who are accessing the internet concurrently.

Vehicular networks are gaining a huge momentum as a mean for an intelligent transportation system that can address numerous problems related to traffic monitoring, accidents, autonomous driving, etc. However, the deployment of vehicular networks is a big challenge for vehicles manufacturers and governments in terms of responsibility and cost. Compared to related research efforts that assume a fixed medium access probability (MAP) of nodes, this paper presents an analytical model using the stochastic geometry tool where we derive the MAP of DSRC nodes in a network composed of vehicles (DSRC nodes) that are located on a system of roads. We then model the roads using a Poisson line process (PLP) and the locations of nodes on each road as a homogeneous 1D Poisson point process (PPP). Also, we model the MAP based on the IEEE 802. 11p standard, where we consider the effect of interference and the carrier sense multiple access with collision avoidance (CSMA/CA). We validated the analytical model against Monte Carlo simulations to prove its accuracy and reliability. The importance of our work stems from the fact that the developed MAP model contributes to the understanding of future DSRC network deployments.

This paper develops a framework to study multi-hop relaying in a vehicular network consisting of vehicles and Road Side Units (RSUs), and the effect of this relaying on the network coverage and the communication delay. We use a stochastic geometry model that consists of a combination of Poisson Line Process (PLP) and 1D Poisson Point Process (PPP) to reliably characterize the vehicular network layout and the locations of the vehicles and the RSUs. Using this model, we analyze the effect of the different network parameters on the coverage provided by the RSUs to the vehicles. Then, we investigate how the uncovered vehicles can receive their intended packets by relaying them through multiple hops that form connected paths to the RSUs. We also analyze the delay introduced to packet delivery due to multi-hop relaying. Namely, we present results that illustrate the coverage gains achieved through multi-hop relaying and the delays induced. Such results could be used by network planners and operators to decide on the different configurations and operational parameters of the vehicular network to suit particular scenarios and objectives.

Carrier Aggregation (CA) has been evolving with all releases of LTE due to its large benefits. However, LTE is based on OFDM which suffers from its high Peak-to-Average-Power-Ratio (PAPR), therefore inducing non-linearities and causing deterioration in the power efficiency of the High Power Amplifier (HPA). Although the PAPR problem has been extensively tackled, there remains a need for techniques that can cope with current system designs. We therefore propose in this paper a new distortion-less PAPR reduction method that is characterized by its high performance and significantly lower complexity when compared to existing methods. We refer to this technique as the Peak Valley Alignment (PVA) method. It is inspired from the sequence alignment techniques used in bioinformatics. We show that the performance attained by optimization-based methods can be approximately achieved through the use of heuristics at a much lower complexity.

The increasing demand on data and services is pushing LTE network operators toward extending their operations to the unlicensed spectrum. The licensed assisted access (LAA) technology is a promising technology to exploit the unlicensed bands and increase the overall LTE network capacity. However, there is a need for characterizing the network performance of LAA operators as their number scale in the unlicensed bands. Hence, in this paper, we develop a framework based on stochastic geometry to model the coexistence of LAA operators. The area system throughput is utilized to analyze the performance imbalance that results from the coexistence of a large number of operators. We validate the accuracy of the proposed model against Monte Carlo simulations and we shed the light on the severe impact of such co-existence on the performance of some operators where their area system throughput may get drastically reduced.

The proliferation of high data-rate applications and services in next-generation WLANs, as well as the significant increase in the number of Wi-Fi devices, is triggering the search for more bandwidth. For this, the Federal Communications Commission (FCC) is considering a proposal to permit devices, such as those that use the IEEE 802.11 (Wi-Fi) protocol, to operate in the 5.9 GHz band allocated to the intelligent transportation system (ITS). However, the nature of these bands poses a challenge since ITS dedicated short range communications (DSRC) networks use them to share safety-critical messages and may be subject to severe interference from other coexisting transmissions. We discuss the impact of coexistence of Wi-Fi networks on the performance of DSRC through an analytical framework based on stochastic geometry. We consider the recent IEEE 802.11ax Wi-Fi standard, and analyze uplink and downlink transmissions, with voice and background traffic being the highest and lowest priority traffic, respectively. We also validate the fixed contention window size of the derived stochastic geometry model using NS-3 simulations. The proposed framework can serve to increase awareness among regulatory bodies of the extent to which coexistence will adversely affect the performance of DSRC.

The proliferation of multimedia applications and services increased the demand on data and the requirement by operators to improve the experience of their users. This has motivated the extension of cellular technologies, such as Long Term Evolution (LTE) toward using the unlicensed bands. However, the nature of these bands poses a challenge since there is uncontrolled interference from other coexisting transmissions. We discuss in this paper the issue of efficient coexistence of LTE operators in the unlicensed bands through an optimization framework that is based on performance metrics obtained using stochastic geometry. The proposed optimization framework allows for obtaining optimized network topologies that maximize the benefit of LTE operators looking to deploy their networks in the unlicensed bands.

With the increasing demand on higher data rates to enhance the user experience, one possible solution would be to extend the cellular technology such as LTE toward the unlicensed bands. Initially, LTE was designed based on the frequency re-use factor of one and which has lead to higher capacity in several deployment scenarios. This happens when LTE exclusively uses the licensed spectrum where interference can be controlled. On the other hand, when LTE uses the unlicensed spectrum, other technologies such as WiFi will coexist and hence LTE will be subject to uncontrolled interference while it is expected to achieve a fair coexistence with such technologies. Given these constraints, we discuss in this paper the utilization of frequency re-use factor of one for LTE in the unlicensed band. In this case and subject to regulations of utilizing unlicensed bands, LTE will use the Listen before talk (LBT) mechanism with other radio access technologies. Thus, using tools from stochastic geometry, we model and analyze the effect of such scenario while comparing it to the case where LTE considers LBT mechanism with other LTE transmissions. Our analysis shows interesting performance gains that can be achieved by LTE in terms of rate coverage probability.

Carrier Aggregation started to appear since release 10 of LTE, and offers higher data rates, but at the cost of increased Peak-to-Average-Power-Ratio (PAPR). This paper studies the distribution of PAPR through analyzing the Crest Factor (CF) which is the square root of the PAPR of the Carrier Aggregated OFDM (CA-OFDM) signals used in the downlink of LTE-A. Although the base station is not power constrained, the increased PAPR can adversely affect performance in terms of energy efficiency and coverage. We model the distribution of the CF by adopting the Level Crossing Rate analysis to approximate the peak distribution of the CA-OFDM signal which can be characterized as a bandlimited complex Gaussian process. The expression of the distribution is derived for an arbitrary number of component carriers for both contiguous and non-contiguous aggregation, where simulations show good agreement with the derived analytical expressions. The derived expression is applied to model the Selective Mapping technique used for PAPR reduction.

The growing demand on data to enhance the user experience has motivated research toward increasing the efficiency of spectrum utilization by extending cellular technology, such as LTE, toward unlicensed bands. In order to study the fair coexistence of LTE and Wi-Fi, we consider the IEEE 802.11ax Wi-Fi standard, where we use stochastic geometry to model and analyze the coexistence of LTE with simultaneous uplink and downlink IEEE 802.11ax transmissions. Mainly, we consider LTE with continuous transmissions (no protocol change), LTE with discontinuous transmissions (LTE-U), and licensed-assisted access (LAA) coexistence mechanisms. In addition, we focus on single unlicensed frequency band transmissions, where the locations of Wi-Fi access points, Wi-Fi stations (users), and LTE eNodeBs (eNBs) are modeled as three independent homogeneous Poisson point processes. Then, we derive analytical expressions for a set of performance metrics, which are the medium access probability, signal-to-interference-plus-noise ratio coverage probability, density of successful transmissions, and Shannon throughput probability for both uplink and downlink of IEEE 802.11ax in addition to LTE. Our analysis quantifies both single-user and multi-user operation modes of the IEEE802.11ax and show that LTE-U or LAA can be a good neighbor for IEEE 802.11ax for different traffic types.

Carrier aggregation (CA) is a key enabling technique to increase the bandwidth of users in order to meet the increasing demand on peak data rates for emerging services and applications. However one of the main practical challenges that comes with CA is the severe increase in the peak-to-average-power ratio (PAPR) of the aggregated time domain NxSC-FDMA signal. This issue is critical for the user equipment (UE) in the uplink as it affects the efficiency of the power amplifier (PA) and hence the transmission coverage. In this paper, a novel two stage PAPR reduction scheme based on frequency spacing aware Discrete Fourier Transform (FSA-DFT) is proposed. Several CA scenarios were analyzed using the proposed technique. Experimental results show that the proposed technique provides a significant reduction in the PAPR of aggregated NxSC-FDMA signal.

Abstract This paper presents a faulty node detection approach for wireless sensor networks that aggregate measurement data on their way toward the sink (base station). The approach is based on the idea of commanding sensor nodes on the aggregation paths to temporarily stop including their readings in the received aggregated readings from their upstream neighbors. The scheme is dependent on the ability of the sink to detect faulty nodes through changes in the received aggregated readings at the sink using a Markov Chain Controller (MCC). The algorithm that is run in the sink uses the MCC to assign a state to each sensor node based on transitions that are triggered by receiving aggregated path readings, and accordingly deduces the nodes that may be faulty. The experimental results show at least 98% detection rate at the cost of reasonable detection delays and generated wireless network traffic. Copyright © 2016 John Wiley & Sons, Ltd.

In LTE-Advanced, carrier aggregation (CA) is a key enabling technique to increase the peak data rates of users and enhance the mobility management in heterogeneous networks (HetNets) using dual connectivity solutions. Several CA schemes have been proposed with a maximum of five LTE Release 8 component carriers (CCs) where the NxSC-FDMA has been chosen as the bandwidth extension scheme for the uplink. This enables the extension of the bandwidth allocated to a user up to 100 MHz while maintaining backward compatibility with LTE release 8 legacy users. However, CA leads to a severe increase in the peak-to-average-power ratio (PAPR) of the aggregated time domain NxSC-FDMA signal at the user equipment (UE). This is an important issue as it affects the power amplifier (PA) efficiency and hence the coverage of transmissions. In this paper, we propose a low- complexity post-IFFT technique to reduce the PAPR of carrier aggregated NxSC-FDMA signals in the uplink of LTE-Advanced. Several case studies of CA were analyzed by using the proposed technique. Simulation results show that the PAPR improvement is 2.5 dB for the case of 2 CCs at only about 4% of the complexity required by the partial selective mapping (PSLM) technique to achieve the same PAPR reduction.

The demand for high data rates in both the uplink and the downlink has motivated the use of carrier aggregation (CA) of several portions of the spectrum up to 100 MHz in LTE-Advanced, while maintaining backward compatibility with LTE release 8. One of the main practical challenges that comes with CA is the severe increase of peak-to-average-power-ratio (PAPR) of the corresponding generated time-domain OFDM signal, thus affecting the power amplifier (PA) efficiency, and hence the transmission coverage. This paper proposes a low-complexity joint interleaving technique to reduce the PAPR of carrier aggregated signals. Several CA scenarios were analyzed using our proposed technique. Simulation results demonstrate that our proposed technique can achieve the same PAPR reduction performance as that of the partial selective mapping (PSLM) technique with 66% reduction in terms of real multiplication and addition operations for the case of three aggregated component carriers (CCs).

In LTE-Advanced, carrier aggregation (CA) allows the extension of the bandwidth allocated to a certain user up to 100 MHz. In particular, the NxSC-FDMA has been selected as the uplink extension scheme. However, one of the main practical challenges that comes with CA is the severe increase in the peak-to-average-power ratio (PAPR) of the aggregated time domain NxSC-FDMA signal. The PAPR increase is an important issue as it affects the efficiency of the power amplifier (PA) at the user equipment (UE) and equivalently the transmission coverage of the LTE-Advanced system. In this paper we propose a PAPR reduction technique based on the well-known Karhunen-Loeve Transform (KLT) to reduce the PAPR of the NxSC-FDMA signals. Several CA scenarios were analyzed using the proposed technique and simulation results show that the performance of the PAPR has improved by 1.5 dB in case of carrier aggregation of two CCs.