This paper presents a sensor-aided pose-aware beamwidth adaptation design for a conceptual extended reality (XR) Head-Mounted Display (HMD) equipped with a 2D planar array. The beam is tracked and adapted on the user side by leveraging HMD orientation estimates. The beamwidth adaptation scheme is effected by selective deactivation of elements in the 2D antenna array, employing the angular estimation covariance matrix to overlap the beam with the estimation confidence interval. The proposed method utilizes the estimation correlations to adapt the beamwidth along the confidence interval of these estimates. Compared to a beamwidth adaptation without leveraging estimation correlations, the proposed method demonstrates the gain of leveraging estimation correlations by improving the coverage area for a given outage probability threshold by approximately 16 %, or equivalently increasing the power efficiency up to 18 %.

In OFDM transmission system, phase noise (PN) caused by non-ideal oscillator induces inter carrier interference (ICI), which is problematic for operation of high order modulation, especially in mm-wave frequency bands. This paper develops two low-complexity and effective ICI compensation algorithms: (i) Direct de-ICI filtering approach which is agnostic to the exact locations of phase tracking reference signal (PTRS), and hence it can readily operate with existing 3GPP Rel-15 PTRS and (ii) Circulant ICI filter approximation which exploits the circulant matrix constructed by a PTRS sequence with cyclic structure to reduce the complexity of ICI compensation algorithm. Our results reveal that both algorithms significantly reduce the negative impact of phase noise on the link performance.

Direct air-to-ground (A2G) communications leveraging the fifth-generation (5G) new radio (NR) can provide high-speed broadband in-flight connectivity to aircraft in the sky. A2G network deployment entails optimizing various design parameters such as inter-site distances, number of sectors per site, and the up-tilt angles of sector antennas. The system-level design guidelines in the existing work on A2G network are rather limited. In this paper, a novel deep learning-based framework is proposed for efficient design and optimization of a 5G A2G network. The devised architecture comprises two deep neural networks (DNNs): the first DNN is used for approximating the 5G A2G network behavior in terms of user throughput, and the second DNN is developed as a function optimizer to find the throughput-optimal deployment parameters including antenna up-tilt angles and inter-site distances. Simulation results are provided to validate the proposed model and reveal system-level design insights.

A Non-terrestrial Network (NTN) comprising Low Earth Orbit (LEO) satellites can enable connectivity to underserved areas, thus complementing existing telecom networks. The high-speed satellite motion poses several challenges at the physical layer such as large Doppler frequency shifts. In this paper, an analytical framework is developed for statistical characterization of Doppler shift in an NTN where LEO satellites provide communication services to terrestrial users. Using tools from stochastic geometry, the users within a cell are grouped into disjoint clusters to limit the differential Doppler across users. Under some simplifying assumptions, the cumulative distribution function (CDF) and the probability density function (PDF) are derived for the Doppler shift magnitude at a random user within a cluster. The CDFs are also provided for the minimum and the maximum Doppler shift magnitude within a cluster. Leveraging the analytical results, the interplay between key system parameters such as the cluster size and satellite altitude is examined. Numerical results validate the insights obtained from the analysis.

Cache-enabled Device-to-Device (D2D) communication is widely recognized as one of the key components of the emerging fifth generation (5G) cellular network architecture. However, conventional half-duplex (HD) transmission may not be sufficient to provide fast enough content delivery over D2D links in order to meet strict latency targets of emerging D2D applications. In-band full-duplex (FD), with its capability of allowing simultaneous transmission and reception, can improve spectral efficiency and reduce latency by providing more content delivery opportunities. In this paper, we consider a finite network of D2D nodes in which each node is endowed with FD capability. We first carefully list all possible operating modes for an arbitrary device using which we compute the number of devices that are actively transmitting at any given time. We then characterize network performance in terms of the success probability, which depends on the content availability, signal-to-interference ratio (SIR) distribution, as well as the operating mode of the D2D receiver. Our analysis concretely demonstrates that caching dictates the system performance in lower target SIR thresholds whereas interference dictates the performance at the higher target SIR thresholds.

With the increasing network densification, it has become exceedingly difficult to provide traditional fiber backhaul access to each cell site, which is especially true for small cell base stations (SBSs). The increasing maturity of millimeter wave (mmWave) communication has opened up the possibility of providing high-speed wireless backhaul to such cell sites. Since mmWave is also suitable for access links, the third generation partnership project (3GPP) is envisioning an integrated access and backhaul (IAB) architecture for the fifth generation (5G) cellular networks in which the same infrastructure and spectral resources will be used for both access and backhaul. In this paper, we develop an analytical framework for IAB-enabled cellular network using which we provide an accurate characterization of its downlink rate coverage probability. Using this, we study the performance of two backhaul bandwidth (BW) partition strategies, (i) equal partition: when all SBSs obtain equal share of the backhaul BW, and (ii) load-based partition: when the backhaul BW share of an SBS is proportional to its load. Our analysis shows that depending on the choice of the partition strategy, there exists an optimal split of access and backhaul BW for which the rate coverage is maximized. Further, there exists a critical volume of cell-load (total number of users) beyond which the gains provided by the IAB-enabled network disappear and its performance converges to that of the traditional macro-only network with no SBSs.

The growing complexity of heterogeneous cellular networks (HetNets) has necessitated a variety of user and base station (BS) configurations to be considered for realistic performance evaluation and system design. This is directly reflected in the HetNet simulation models proposed by standardization bodies, such as the 3rd Generation Partnership Project (3GPP). Complementary to these simulation models, stochastic geometry-based approach, modeling the locations of the users, and the K tiers of BSs as independent and homogeneous Poisson point processes (PPPs), has gained prominence in the past few years. Despite its success in revealing useful insights, this PPP-based K-tier HetNet model is not rich enough to capture spatial coupling between user and BS locations that exists in real-world HetNet deployments and is included in 3GPP simulation models. In this paper, we demonstrate that modeling a fraction of users and arbitrary number of BS tiers alternatively with a Poisson cluster process (PCP) captures the aforementioned coupling, thus bridging the gap between the 3GPP simulation models and the PPP-based analytic model for HetNets. We further show that the downlink coverage probability of a typical user under maximum signal-tointerference-ratio (SIR) association can be expressed in terms of the sum-product functionals over PPP, PCP, and its associated offspring point process, which are all characterized as a part of our analysis. We also show that the proposed model converges to the PPP-based HetNet model as the cluster size of the PCPs tends to infinity. Finally, we specialize our analysis based on general PCPs for Thomas and Matérn cluster processes. Special instances of the proposed model closely resemble the different configurations for BS and user locations considered in 3GPP simulations.

This paper develops a new approach to the modeling and analysis of heterogeneous cellular networks (HetNets) that accurately incorporates coupling across the locations of users and base stations, which exists due to the deployment of small cell base stations (SBSs) at the places of high user density (termed user hotspots in this paper). Modeling the locations of the geographical centers of user hotspots as a homogeneous Poisson point process (PPP), we assume that the users and SBSs are clustered around each user hotspot center independently with two different distributions. The macrocell BS locations are modeled by an independent PPP. This model is consistent with the user and SBS configurations considered by 3GPP. Using this model, we study the performance of a typical user in terms of coverage probability and throughput for two association policies: 1) Policy 1, under which a typical user is served by the open-access BS that provides maximum averaged received power and 2) Policy 2, under which the typical user is served by the small cell tier if the maximum averaged received power from the open-access SBSs is greater than a certain power threshold; and macro tier otherwise. A key intermediate step in our analysis is the derivation of distance distributions from a typical user to the open-access and closed-access interfering SBSs. Our analysis demonstrates that as the number of SBSs reusing the same resource block increases, coverage probability decreases, whereas throughput increases. Therefore, contrary to the usual assumption of orthogonal channelization, it is reasonable to assign the same resource block to multiple SBSs in a given cluster as long as the coverage probability remains acceptable. This approach to HetNet modeling and analysis significantly generalizes the state-of-the-art approaches that are based on modeling the locations of BSs and users by independent PPPs.

With the increasing network densification, it has become exceedingly difficult to provide traditional fiber backhaul access to each cell site, which is especially true for small cell base stations (SBSs). The increasing maturity of millimeter wave (mm-wave) communication has opened up the possibility of providing high-speed wireless backhaul to such cell sites. Since mm-wave is also suitable for access links, the third generation partnership project (3GPP) is envisioning an integrated access and backhaul (IAB) architecture for the fifth generation (5G) cellular networks in which the same infrastructure and spectral resources will be used for both access and backhaul. In this paper, we develop an analytical framework for IAB-enabled cellular network using which its downlink rate coverage probability is accurately characterized. Using this framework, we study the performance of three backhaul bandwidth (BW) partition strategies: 1) equal partition: when all SBSs obtain equal share of the backhaul BW; 2) instantaneous load-based partition: when the backhaul BW share of an SBS is proportional to its instantaneous load; and 3) average load-based partition: when the backhaul BW share of an SBS is proportional to its average load. Our analysis shows that depending on the choice of the partition strategy, there exists an optimal split of access and backhaul BW for which the rate coverage is maximized. Further, there exists a critical volume of cell-load (total number of users) beyond which the gains provided by the IAB-enabled network disappear and its performance converges to that of the traditional macro-only network with no SBSs.

This paper develops a comprehensive framework for the performance analysis of user-centric capacity-driven small cell deployments, where small cell BSs (SBSs) are deployed at the places of high user density, i.e., user hotspots. In order to incorporate the correlation between user and SBS locations, we model the geographical centers of user hotspots as a homogeneous Poisson point process (PPP) around which users and SBSs are clustered following two independent general distributions. The macrocell base station (BS) locations are modeled by an independent PPP. A key intermediate step of our analysis is the derivation of a new set of distance distributions, which enable the exact characterization of coverage probability and throughput. For numerical evaluation, we specialized the setup to the case where users and SBSs are clustered with two independent normal distributions. Our analysis demonstrates that as the number of SBSs reusing the same resource block increases (higher frequency reuse), coverage probability decreases whereas throughput increases. Thus the same resource block can be aggressively reused by more SBSs as long as the coverage probability remains acceptable.

We present a general mathematical framework to characterize the performance of an arbitrarily-located reference receiver in a finite wireless network. Modeling the locations of nodes as a uniform binomial point process (BPP), we derive the general k-coverage probability, which is the distribution of the signal-to-interference ratio (SIR) at the reference receiver when it connects to its k-th closest transmitting node. This k-coverage result for an arbitrarily- located reference receiver significantly generalizes existing works on finite networks, which usually assume that the reference receiver connects to a pre-selected transmitter located at a fixed distance that may not be a part of the BPP (ad hoc network setup). A particular special case of interest is that of k=1, which can be interpreted as the downlink coverage probability in a finite cellular network modeled as a BPP. To the best of our understanding, the exact characterization of this result for finite cellular networks is not known. The mathematical analysis of k-coverage probability is enabled by the derivation of joint distance distributions from interfering and serving nodes to the reference receiver. As expected, our results demonstrate that the k-coverage probability strongly depends upon the location of the reference receiver. This observation highlights the importance of location information of the reference receiver for the accurate analysis of finite wireless networks.

Modeling the locations of nodes as a uniform binomial point process, we present a generic mathematical framework to characterize the performance of an arbitrarily located reference receiver in a finite wireless network. Different from most of the prior works where the serving transmitter (TX) is located at the fixed distance from the reference receiver, we consider two general TX-selection policies: 1) uniform TX-selection: the serving node is chosen uniformly at random from amongst all transmitting nodes and 2) k-closest TX-selection: the serving node is the kth closest node (out of all transmitting nodes) to the reference receiver. The key intermediate step in our analysis is the derivation of a new set of distance distributions that lead not only to the tractable analysis of coverage probability but also enable the analysis of wide range of classical and currently trending problems in wireless networks. Using this new set of distance distributions, we further investigate the diversity loss due to SIR correlation in a finite network. We then obtain the optimal number of links that can be simultaneously activated to maximize network spectral efficiency. Finally, we evaluate optimal caching probability to maximize the total hit probability in cache-enabled finite networks.

One of the principal underlying assumptions of current approaches to the analysis of heterogeneous cellular networks (HetNets) with random spatial models is the uniform distribution of users independent of the base station (BS) locations. This assumption is not quite accurate, especially for user-centric capacity-driven small cell deployments where low-power BSs are deployed in the areas of high user density, thus inducing a natural correlation in the BS and user locations. In order to capture this correlation, we enrich the existing K-tier Poisson point process (PPP) HetNet model by considering user locations as Poisson Cluster Process with the BSs at the cluster centers. In particular, we provide the formal analysis of the downlink coverage probability in terms of a general density function describing the locations of users around the BSs. The derived results are specialized for two cases of interest: 1) Thomas cluster process, where the locations of the users around BSs are Gaussian distributed and 2) Matérn cluster process, where the users are uniformly distributed inside a disc of a given radius. Tight closed-form bounds for the coverage probability in these two cases are also derived. Our results demonstrate that the coverage probability decreases as the size of user clusters around BSs increases, ultimately collapsing to the result obtained under the assumption of PPP distribution of users independent of the BS locations when the cluster size goes to infinity. Using these results, we also handle mixed user distributions consisting of two types of users: 1) uniformly distributed and 2) clustered around certain tiers.

In this paper, we develop a comprehensive analytical framework to characterize the performance of device-centric content availability in device-to-device (D2D) networks. Modeling the locations of devices as a variant of Thomas cluster process, we derive the coverage probability of a typical device when its content of interest is available at its kth closest device within the same cluster. Using the coverage probability results, we characterize the area spectral efficiency (ASE) of the whole network. A key intermediate step in this analysis is the derivation of the distributions of distances from the typical device to both the intra- and inter-cluster devices. Our analysis reveals that an optimum number of D2D transmitters must be simultaneously activated per cluster in order to maximize ASE. This can be interpreted as the classical tradeoff between more aggressive frequency reuse and higher interference power. Our analysis also quantifies the best and worst case performance of the clustered D2D networks both in terms of coverage and ASE.

To maintain tractability, interference field is often modeled as a homogeneous Poisson Point Process (PPP) in the analysis of wireless networks. While it provides meaningful first-order results, it falls short in modeling the effect of interference management techniques, which typically introduce some form of spatial interaction among transmitters. In some applications, such as cognitive radio and device-to-device networks, this interaction results in the formation of holes in an otherwise homogeneous interference field. The resulting interference field can be accurately modeled as a Poisson Hole Process (PHP). Despite the importance of PHP in modeling wireless networks, exact characterization of the interference experienced by a typical node in a PHP is an open problem. In this paper, we introduce a new approach to modeling the PHP, in which we dissolve the holes in such a way that it results in an equivalent non-homogeneous PPP, which is much more amenable to shot-noise analysis. Using this approach, we derive new lower and upper bounds on the Laplace transform of interference in a PHP. The new bounds are compared numerically to the known approaches and are shown to be very tight under various operational regimes.

This paper develops a comprehensive analytical framework with foundations in stochastic geometry to characterize the performance of cluster-centric content placement in a cache-enabled device-to-device (D2D) network. Different from device-centric content placement, cluster-centric placement focuses on placing content in each cluster, such that the collective performance of all the devices in each cluster is optimized. Modeling the locations of the devices by a Poisson cluster process, we define and analyze the performance for three general cases: 1) k-Tx case: the receiver of interest is chosen uniformly at random in a cluster and its content of interest is available at the kth closest device to the cluster center; 2) 1-Rx case: the receiver of interest is the Ith closest device to the cluster center and its content of interest is available at a device chosen uniformly at random from the same cluster; and 3) baseline case: the receiver of interest is chosen uniformly at random in a cluster and its content of interest is available at a device chosen independently and uniformly at random from the same cluster. Easy-to-use expressions for the key performance metrics, such as coverage probability and area spectral efficiency of the whole network, are derived for all three cases. Our analysis concretely demonstrates significant improvement in the network performance when the device on which content is cached or device requesting content from cache is biased to lie closer to the cluster center compared with the baseline case. Based on this insight, we develop and analyze a new generative model for cluster-centric D2D networks that allows to study the effect of intra-cluster interfering devices that are more likely to lie closer to the cluster center.

Device-to-device (D2D) communication enables direct communication between proximate devices thereby improving the overall spectrum utilization and off-loading traffic from cellular networks. This paper develops a new spatial model for D2D networks in which the device locations are modeled as a Poisson cluster process. Using this model, we study the performance of a typical D2D receiver in terms of coverage probability under two realistic content availability setups: 1) content of interest for a typical device is available at a device chosen uniformly at random from the same cluster, which we term uniform content availability, and 2) content of interest is available at the kthclosest device from the typical device inside the same cluster, which we term k-closest content availability. Using these coverage probability results, we also characterize the area spectral efficiency (ASE) of the whole network for the two setups. A key intermediate step in this analysis is the derivation of the distributions of distances from a typical device to both the intra-and inter-cluster devices. Our analysis reveals that an optimum number of D2D transmitters must be simultaneously activated per cluster in order to maximize ASE. This can be interpreted as the classical tradeoff between more aggressive frequency reuse and higher interference power. The optimum number of simultaneously transmitting devices and the resulting ASE increase as the content is made available closer to the receivers. Our analysis also quantifies the best and worst case performance of clustered D2D networks both in terms of coverage and ASE.

Interference field in wireless networks is often modeled by a homogeneous Poisson point process (PPP). While it is realistic in modeling the inherent node irregularity and provides meaningful first-order results, it falls short in modeling the effect of interference management techniques, which typically introduces some form of spatial interaction among active transmitters. In some applications, such as cognitive radio and device-to-device networks, this interaction may result in the formation of holes in an otherwise homogeneous interference field. The resulting interference field can be accurately modeled as a Poisson hole process (PHP). Despite the importance of the PHP in many applications, the exact characterization of interference experienced by a typical node in the PHP is not known. In this paper, we derive several tight upper and lower bounds on the Laplace transform of this interference. Numerical comparisons reveal that the new bounds outperform all known bounds and approximations, and are remarkably tight in all operational regimes of interest. The key in deriving these tight and yet simple bounds is to capture the local neighborhood around the typical node accurately while simplifying the far field to attain tractability. Ideas for tightening these bounds further by incorporating the effect of overlaps in the holes are also discussed. These results immediately lead to an accurate characterization of the coverage probability of the typical node in the PHP under Rayleigh fading.

This paper develops a new spatial model for device-to-device (D2D) networks in which the device locations are modeled as a Thomas cluster process. The devices inside a given cluster form D2D links amongst themselves and the direct communication across clusters is not required. This model captures the fact that the devices engaged in D2D communications need to be in close proximity of each other. For this model, we derive easy-to-use expressions for both coverage probability and area spectral efficiency (ASE) assuming that the content of interest is available at a device chosen uniformly at random from the same cluster. One of the important consequences of this analysis is that there exists an optimal number of simultaneously active D2D-Txs that maximizes the ASE. This can be interpreted as the classical tradeoff between more aggressive frequency reuse and higher interference power. Our analysis also provides insights into the effect of scattering variance of each cluster and the density of cluster centers on coverage probability and ASE.

We propose a dynamic interference mitigation technique by incorporating cognitive capability and cooperative mechanism in two tier heterogeneous network (HetNet) with open access femtocells. To further enhance protection of victim user that is subject to interference, a cooperative mechanism is designed based on received power of user. We exploit stochastic geometry for modelling and analysing the effect of our interference mitigation mechanism in two-tier HetNet by considering Rayleigh fading environment. Results show significant improvement on the coverage probability.