To cope with the unprecedented ubiquity of smart applications, Machine-Type Communication (MTC), the cellular communication backbone of the Internet of Things (IoT), has become an inevitable choice. In this paper, we investigate the achievable performance of MTC in an Ultra-Dense Network (UDN). To fully utilize the available resources in 5G and beyond networks, we exploit the propagation characteristics and excess bandwidth of the Millimeter wave (mmWave) band. Using tools from stochastic geometry, we provide a mathematical framework to evaluate the achievable Signal-to-Interference plus Noise Ratio (SINR) per user and the average capacity per Small Cell (SC) while considering the severe Inter-Cell Interference (ICI) of UDNs and the blockage effect in mmWave. The accuracy of the formu-lated analytical expressions is verified through extensive Monte-Carlo simulations. The obtained results show the existence of an optimal Small Cell (SC) density that maximizes the utilization of the deployed SCs.

This paper investigates the downlink (DL) performance of cell-free (CF) massive multiple-input multiple-output (mMIMO) systems under limited-fronthaul capacity. We consider a practical fronthaul deployment where the fronthaul network is modeled as a hybrid millimeter wave (mmWave) /microwave network. In particular, we assume the presence of multiple edge-cloud processor (ECP)s to which access points (AP)s are associated in a distance-based criterion. The APs are supported by mmWave fronthaul link given that line-of-sight (LoS) links exist with their associated ECPs, otherwise, microwave fronthaul links will be used. We analyze the achievable DL data rates under distributed and centralized system operations. For the distributed system operation, APs apply local conjugate beamforming (CB) precoding along with beamforming training. On the other hand, ECPs apply zero-forcing (ZF) precoding in the centralized system operation. Results reveal that the centralized system operation remarkably outperforms the distributed counterpart under perfect fronthaul links. However, the impact of limited capacity fronthaul links is more prominent on the centralized system operation with ZF precoding. Moreover, we show that the network should be designed according to the adopted system operation and the capacities of fronthaul links.

The rising era of smart living requires unprecedented advancements in cellular networks to support the communications of the Internet of Things (IoT), referred to as machine-type communication (MTC). Hence, we consider an ultradense network (UDN) environment supported by wireless backhaul links (BHs) and investigate the achievable performance gains for MTC. By doing so, we avoid the complexity, cost, and/or infeasibility of providing fiber BHs for the massive number of small cells (SCs) found in UDNs. We utilize the millimeter wave (mmWave) band to support the communications between the IoT Devices (IoTD) and their serving SCs. By doing so, the excess available bandwidth can be used to support a massive number of IoTDs while the propagation characteristics of the mmWave signals can be exploited to mitigate the severe intercell interference (ICI) found in UDNs. In this regard, we formulate a mathematical framework using tools from stochastic geometry to derive analytical expressions for the density of supported IoTDs and the average capacities per SC on both the access link (AL) and the BH. In addition, we obtain a tight lower bound of the average capacity per SC under the considered wireless limited-capacity BHs. The obtained results show the existence of an optimal active SC density that maximizes SC utilization.

This paper investigates the downlink (DL) performance of cell-free (CF) massive multiple-input multiple-output (mMIMO) systems under a wireless mMIMO-based fronthaul network operation. Particularly, we consider multiple edge-cloud processors (ECP)s serving access points (AP)s using one of three possible fronthaul network operations, namely, microwave, millimeter wave (mmWave), or hybrid microwave/mmWave. Under each fronthaul network operation, we analyze the achievable DL data rates for two different microwave-based operations of the access link (APs-users), namely, distributed and centralized operations, while assuming APs with/without decoding capabilities. In the distributed operation, APs are responsible for performing both channel estimation and DL data precoding tasks, whereas ECPs are the responsible entities for carrying out such tasks in the centralized counterpart. Our results show that the integration between the centralized access link operation and the hybrid-based fronthaul network provides the highest DL data rates when APs are empowered with decoding capabilities. However, integrating the distributed access link operation with the microwave-based fronthaul network achieves ultimate performance when APs are not supported with decoding capabilities. Interestingly, we reveal that APs with low fronthaul capacities dominantly control the preferred network configuration in-terms of the densities and the number of deployed antennas for both APs and ECPs.

One of the major technological breakthroughs to support unprecedented demands of the future generations of wireless communication networks is cell-free (CF) massive multiple-input multiple-output (mMIMO). However, a fronthaul network with high and reliable capacity links is a prerequisite to realize the full potential of the CF mMIMO. Aiming at deploying a cost-efficient fronthaul network, this paper proposes a millimeter wave (mmWave)-based fronthaul network for the CF mMIMO system operation thanks to the broad bandwidth in the mmWave frequency band. Stochastic geometry tools have been exploited to reflect the impact of the considered fronthaul network on the uplink (UL) performance of CF mMIMO systems. Results reveal that increasing the blockage density deteriorates the average UL data rates, however, increasing the density of CPUs can limit the blockages effect on the system performance. Besides, while it is more preferable to deploy a large number of antennas per access points (AP)s under low blockage densities, having a large number of APs, provided with a small number of antennas leads to superior UL data rates at high blockage densities.

In this paper, we propose a nearest line-of-sight relay (NLR) selection technique for internet of things (IoT) devices in millimeter wave (mmWave) relaying systems. We present a tractable analytical framework to characterize the network connectivity for the proposed technique using tools from stochastic geometry. Moreover, we investigate the impact of the relay-selected region and the distance between the base station and IoT device on the network connectivity of mmWave relaying systems. The analytical results unveil a high degree of accuracy which is confirmed by extensive simulations at different relay densities, blockage densities, and signal-to-noise ratio (SNR) thresholds. Results obtained via both simulations and analyses reveal the trade-off between the network connectivity and the energy consumption of IoT devices. Results also reveal a significant impact of blockage density and controlling the relay-selected region on the network connectivity and energy consumption.

Operating beyond-5G networks at the millimeter wave (mmWave) band imposes technological challenges while offering great opportunities. The nature of millimeter waves renders the communication quality susceptible due to blockage caused by obstacles. Hence, multi-hop relaying is likely to play a significant role in improving the performance of mmWave networks. In this paper, we investigate the performance of two appropriate routing techniques for mmWave networks, namely minimum hop count (MHC) and nearest LoS relay to the destination with MHC (NLR-MHC). Analytical models are provided to evaluate the performance of the two routing techniques using tools from stochastic geometry. We model the distribution of hop count using phase-type distribution, and then we use this distribution to derive analytical results for the coverage probability and spectral efficiency. Results reveal the significant impact of densities of relays and blockages on the performance of the aforementioned routing techniques in-terms of spectral efficiency, connectivity probability, and average hop count. It is also demonstrated that NLR-MHC achieves a superior coverage probability and spectral efficiency compared to MHC. However, MHC provides better performance in-terms of connectivity probability and average hop count.

In this paper, we propose an analytical framework to characterize the hop count distribution for the minimum hop count (MHC) routing technique in mmWave networks. The hop count distribution is modelled as a phase-type distribution, and its parameters are derived using tools from stochastic geometry. Capitalizing on the hop count distribution, we investigate the impact of limiting the hop count on the connectivity of mmWave networks. We further demonstrate that the network connectivity varies according to specific system parameters, such as the densities of relays and blockages. Results obtained via both simulations and analyses reveal the trade-off between the network connectivity and the delay as a function of the hop count.