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.

This paper investigates the downlink (DL) performance of cell-free (CF) massive multiple-input multiple-output (mMIMO) systems with limited capacity fronthaul links. The achievable DL rates are derived assuming two different CF mMIMO system operations, namely, distributed and centralized system operations. For the distributed system operation, access points (AP)s apply local conjugate beamforming (CB) precoding along with beamforming training (BT). On the other hand, the central processing unit (CPU) applies zero-forcing (ZF) precoding in the centralized system operation. Results revealed that the impact of limited capacity fronthaul links is more prominent on the centralized system operation. In addition, while the distributed system operation is more preferable under low capacities of fronthaul links, the centralized counterpart attains superior performance at high capacities of fronthaul links.

Cell-free (CF) massive multiple-input multiple-output (MIMO) system is currently considered as a promising network architecture to satisfy the anticipated rate requirements of beyond-5G networks. However, in practical scenarios with the presence of high-velocity users, the network experiences an inevitable performance degradation due to the Doppler shift effect. This paper analyzes the potential of frame length optimization in limiting the Doppler shift effect on the performance of time-division duplexing CF massive MIMO under different mobility conditions. In doing so, we derive novel expressions for tight lower bound of the average downlink (DL) and uplink (UL) rates. Capitalizing on the derived analytical results, we provide an analytical framework to determine the optimal frame length that limits the Doppler shift effect on DL and UL rates according to some criterion. Our results show perfect match of both analytical and simulated results under different system settings. Also, we reveal that the optimal frame lengths for maximizing the DL and UL rates are different and depend mainly on the transmission criterion and the users' velocities. Besides, our results demonstrate the high potential of adapting the frame length according to the velocity conditions in limiting the Doppler shift effect compared to applying a fixed frame length.

This paper investigates the downlink (DL) performance of cell-free (CF) massive multiple-input multiple-output (MIMO) systems in the presence of pilot spoofing attacks. Assuming no statistical information of the eavesdropper is available at the access points (AP)s while adopting non-orthogonal pilot sequences in the uplink (UL) training phase, new analytical expressions for the achievable DL rates and information leakage are derived. Besides, we propose a new DL transmission protocol in which the nearest APs to users send DL pilots so that the users can estimate the corresponding DL channel conditions and detect the intended DL transmitted symbols. The performance of the proposed technique is compared with other techniques in the literature, namely, no DL pilots and DL beamforming training. Results reveal that the proposed technique is more robust under pilot spoofing attacks as it significantly limits the information leakage to the eavesdropper and achieves superior secrecy rates.