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In this paper, we analyze a hybrid Heterogeneous Cellular Network (HCNet) framework by deploying millimeter Wave (mmWave) small cells with coexisting traditional sub-6GHz macro cells to achieve improved coverage and high data rate. We consider randomly-deployed macro base stations throughout the network whereas mmWave Small Base Stations (SBSs) are deployed in the areas with high User Equipment (UE) density. Such user centric deployment of mmWave SBSs inevitably incurs correlation between UE and SBSs. For a realistic scenario where the UEs are distributed according to Poisson cluster process and directional beamforming with line-of-sight and non-line-of-sight transmissions is adopted for mmWave communication. By using tools from stochastic geometry, we develop an analytical framework to analyze various performance metrics in the downlink hybrid HCNets under biased received power association. For UE clustering we considered Thomas cluster process and derive expressions for the association probability, coverage probability, area spectral efficiency, and energy efficiency. We also provide Monte Carlo simulation results to validate the accuracy of the derived expressions. Furthermore, we analyze the impact of mmWave operating frequency, antenna gain, small cell biasing, and BSs density to get useful engineering insights into the performance of hybrid mmWave HCNets. Our results show that network performance is significantly improved by deploying millimeter wave SBS instead of microwave BS in hot spots.

Unmanned aerial vehicle (UAV) assisted wireless communication has been recently proposed as an effective solution to provide wireless connectivity to ground users which can improve the network coverage area and spectral efficiency. In this paper, we consider the post‐disaster network scenario where users are isolated from the network infrastructure. We investigate the best positioning of the UAV in terms of the optimal trajectory as well as UAV vertical location to cover as many ground users as possible to improve the spectral efficiency. When the trajectory is optimized, the optimal transmit power within the available power budget is then obtained. The simulation results demonstrate that the proposed UAV‐enabled wireless communication technique improves the overall spectral and energy efficiency. [ABSTRACT FROM AUTHOR]

The Terahertz (THz) band (0.1–10 THz) contains abundant spectrum resources that can offer ultra-high data rates. Despite these potential benefits, the adoption of THz communication has been stagnant until very recently due to the poor penetrability and limited coverage of the THz links. To overcome the aforementioned obstacles and take full advantage of the THz band, we introduced a hybrid network consisting of THz and millimeter-wave (mmWave) nodes deployed within a finite area. Furthermore, the mmWave nodes are spatially distributed by a Poisson Point Process (PPP), whereas the THz nodes are clustered around the mmWave nodes, forming a Poisson Cluster Process (PCP) with the parent process of mmWave tier. We derive the Laplace transform of the interference in a closed form and evaluate the coverage probability (CP) based on the maximum biased power (Max-BRP) association strategy. The proposed framework provides insights into how the spatial dependence between THz and mmWave tier and clustering setting affects network performance. We quantitatively reveal its impact on the network performance. It is revealed that this inter-tier spatial dependence introduces the flexibility of nodes deployment by tuning the scattering variance and the number of nodes per cluster. Furthermore, we use numerical simulation to demonstrate the significant impact of bias ratio, density, and blockage on the CP, indicating the importance of choosing the optimal combination of the parameters.

This paper develops a new approach to the modeling and analysis of device-to-device (D2D) underlaying multi-tier cellular network for dense hotspot communications, which consists of macro base stations (MBSs), pico BSs (PBSs), femto BSs (FBSs). A typicl user equipment (UE) can work either in D2D mode or cellular mode. Considering the dense hotspot communications, this work employs Poisson point process (PPP) to model the locations of MBSs and PBSs, and uses Poisson cluster process (PCP) to model the ones of UEs and FBSs. The locations of PBSs are also modeled as the centers of hotspots, referred to as the centers of PCPs. UEs and FBSs cluster around the common parent process PBSs. To guard the cluster-edge UEs, the clustered-UE classification and modified fractional frequency reuse (FFR) are jointly used, by which both the UEs and FBSs are classified two sets, cluster-center UEs and cluster-edge UEs, cluster-center FBSs and cluster-edge FBSs, respectively. The total frequency band is divided into two orthogonal segments, one of which is shared by D2D devices, cluster-edge FBSs, and PBSs, and the other segment of which is shared by cluster-center FBSs and MBSs. For such clustered multi-tier network, by using the methods from PPP, PCP, and PHP, this paper presents a tractable approach for modeling and analyzing the performance of cellular and D2D networks and gives the statistical descriptions of the experienced interferences at a typical D2D or cellular receiver by using the approximated Poisson hole processes (PHP) theory. This yields the derivations of the coverage probabilities of both the D2D receivers and cellular destinations. In additon, during the analysis of cellular UEs, to derive the coverage probabilities, this paper specially constructs one UE association criterion as well as the derivations of both the association probabilities and the statistical descriptions of association distances for cluster-center and cluster-edge UEs. The simulations results exploit the effect of various network parameters on the network performance and give the insights in terms of the proposed schemes as well as the comparison between cluster-center and cluster-edge UEs. [ABSTRACT FROM AUTHOR]

Wireless networks in next generation will provide users ubiquitous computing services with low delay by devices at the network edge, namely mobile edge computing (MEC). The intensive computation tasks can be partially offloaded to the MEC server via the wireless link and then processed through the MEC computation resources to cater for the delay demand. A parallel computation process is formed in the MEC network consists of local computation at MEC users (MUs) and MEC computation at MEC servers. However, the fluctuating wireless channel environment, changeable spatial distribution of MUs and the randomness of MEC servers’ locations make it hard to characterize and guarantee the end-to-end quality of service requirements. In this work, we are devoted to analyze and optimize the overall delay bound for MEC networks under two orthogonal frequency division multiple access (OFDMA) strategies via stochastic network calculus (SNC). Specifically, Poisson cluster process is utilized to capture the randomness of MEC servers’ and users’ spatial locations and to derive the Laplace transform of interference suffered by an MU of interest. The upper bounds for the delay violation probability of two OFDMA strategies are established by exploiting SNC with the Mellin transform of signal-to-interference ratio. Furthermore, we propose an optimal task offloading scheme by minimizing the overall delay, which balances the local computation delay and MEC delay. [ABSTRACT FROM AUTHOR]

This paper provides an analytical framework for the coexistence of uplink cellular network and D2D network in the same frequency band. D2D devices are assumed to be distributed according to a Poisson Cluster Process (PCP), while the locations of the cellular users and macro BSs are modeled as an independent Poisson Point Process (PPP) respectively. We study the performance of the uplink in cellular network with power control and the performance of this D2D network for two content availability cases: (1) Uniform content availability, which means content of interest to a typical device is available on devices selected randomly and uniformly from the same cluster, and (2) Closest content availability, which means content of interest is available on the closest devices to a typical device in the same cluster. Using this model, the distribution of the Signal to Interference Ratios (SIR) of a typical receiving node (tagged BS or D2D Rx) can be obtained. We derive the coverage probability, area spectrum efficiency (ASE) and average rate for both cellular and D2D links to analyze the performance of the whole network, and our analysis shows that an optimal number of D2D links must be simultaneously activated per cluster in order to maximize ASE. [ABSTRACT FROM AUTHOR]

Full duplex (FD) in cloud radio access networks (C-RAN) has improved the overall system throughput at most to double the half duplex (HD) counterpart. Although there is an overall improvement in the throughput, it is mainly due to the downlink (DL) rate, while the uplink (UL) rate is highly degraded due to the substantial DL interference. In this paper, we showed how by employing a downlink power control (DLPC), the overall capacity could be improved along with UL rate improvement. In DL, we could achieve 2.9 times the HD rate and 1.5 times that of FD without DLPC. In UL, 1.6 times the HD rate and the improvement up to 3.49 bps/Hz from rates of the order 1 0 − 4 bps/Hz of FD without DLPC. We have also shown how by appropriately selecting DL and UL power control parameters, we can reduce the cluster size requirement in the FD C-RAN system and the fronthaul capacity requirements. We use Matern Cluster Process (MCP) to model the network. We provide coverage and rate as integral expressions in terms of special functions and algebraic terms. We also derive closed-form approximations for asymptotic rates and reflect few insights into the system design. [ABSTRACT FROM AUTHOR]