Picocellular architectures are essential for providing the spatial reuse required to satisfy the ever-increasing demand for mobile data. A key deployment challenge is to provide backhaul connections with sufficiently high data rate. Providing wired support (e.g., using optical fiber) to pico base stations deployed opportunistically on lampposts and rooftops is impractical, hence wireless backhaul becomes an attractive approach. A multihop mesh network comprised of directional millimeter wave links is considered here for this purpose. The backhaul design problem is formulated as one of joint routing and resource allocation, accounting for mutual interference across simultaneously active links. A computationally tractable formulation is developed by leveraging the localized nature of interference and the provable existence of a sparse optimal allocation. Numerical results are provided for millimeter (mm) wave mesh networks, which are well suited for scaling backhaul data rates due to abundance of spectrum, and the ability to form highly directional, electronically steerable beams.
Millimeter wave (mm-wave) frequencies provide orders of magnitude larger spectrum than current cellular allocations and allow usage of high dimensional antenna arrays for exploiting beamforming and spatial multiplexing. This paper addresses the problem of joint scheduling and radio resource allocation optimization in mm-wave heterogeneous networks where mm-wave small cells are densely deployed underlying the conventional homogeneous macro cells. Furthermore, mm-wave small cells operate in time division duplexing mode and share the same spectrum and air-interface for backhaul and access links. The scheme proposed in this paper can significantly enhance network throughput by exploiting space-division multiple access, i.e., allowing non-conflicting flows to be transmitted simultaneously. The optimization problem of maximizing network throughput is formulated as a mixed integer nonlinear programming problem. To find a practical solution, this is decomposed into three steps: concurrent transmission scheduling, time resource allocation, and power allocation. A maximum independent set based algorithm is developed for concurrent transmission scheduling to improve resource utilization efficiency with low computational complexity. Through extensive simulations, we demonstrate that the proposed algorithm achieves significant gain over benchmark schemes in terms of user throughput.  Millimeter wave (mmWave) cellular systems will require high-gain directional antennas and dense base station (BS) deployments to overcome a high near-field path loss and poor diffraction. As a desirable side effect, high-gain antennas offer interference isolation, providing an opportunity to incorporate self-backhauling , i.e., BSs backhauling among themselves in a mesh architecture without significant loss in the throughput, to enable the requisite large BS densities. The use of directional antennas and resource sharing between access and backhaul links leads to coverage and rate trends that significantly differ from conventional UHF cellular systems. In this paper, we propose a general and tractable mmWave cellular model capturing these key trends and characterize the associated rate distribution. The developed model and analysis are validated using actual building locations from dense urban settings and empirically derived path loss models. The analysis shows that, in sharp contrast to the interference-limited nature of UHF cellular networks, the spectral efficiency of mmWave networks (besides the total rate) also increases with the BS density, particularly at the cell edge. Increasing the system bandwidth does not significantly influence the cell edge rate, although it boosts the median and peak rates. With self-backhauling, different combinations of the wired backhaul fraction (i.e., the fraction of BSs with a wired connection) and the BS density are shown to guarantee the same median rate (QoS). Delivering Gbps high user rate over long distances ( 1 km) is challenging, and the abundant spectrum available in millimeter wave band cannot solve the challenge by its own due to the severe path loss and other limitations. Since it is economically challenging to deploy wired backhaul every few hundred meters, relays (e.g., wireless access points) have been proposed to extend the coverage of a base station, which has wired connection to the core network. These relays, deployed every few hundred meters, serve the users in their vicinity and are backhauled to the base station through wireless connections. In this paper, the wireless-relayed backhaul design has been formulated as a topology-bandwidth-power joint optimization problem, and the influence of path loss, angular spread, array size, and RF power limitation on the user rate has been evaluated. It has been shown that for a linear network deployed along the street at 28 GHz, when high joint directional gain (50 dBi) is available, 1 Gb s user rate within cell range of 1 km can be delivered using 1.5 GHz of bandwidth (using single polarization antennas). The user rates drop precipitously when joint directional gain is reduced, or when the path loss is much more severe. When the number of RF chains is limited, the benefit of larger arrays will eventually be surpassed by the increased channel estimation penalty as the effective beamforming gain saturates owing to the channel angular spread. Massive Multiple-Input Multiple-Output (MIMO) systems, dense Small-Cells (SCs), and full duplexing are three candidates for next-generation wireless systems. The cooperation of the three techniques could offer more benefits, e.g., SC in-band wireless backhaul in massive MIMO systems. In this paper, three strategies of SC in-band wireless backhaul in massive MIMO systems are introduced and compared. Simulation results show that SC in-band wireless backhaul has the potential to improve the throughput for massive MIMO systems, and applying full-duplexing techniques at SCs could provide greater gain. While small cells (SCs) are an important feature of emerging network architectures, providing backhaul to SCs is a challenging problem. Non-line-of-sight (NLOS) wireless backhaul networks provide a cost effective approach in urban areas where providing a wired- or fiber-based backhaul is difficult. An important problem in designing such networks is to optimize the position of backhaul hubs in a way that all SCs are properly serviced. However, this is a NP-complete problem requiring suboptimal, but effective, solutions. In this work, we will propose a novel suboptimal algorithm, based on dynamic programming, to solve the NP-hard problem of hub placement in backhaul networks. We will further consider an extended problem of optimizing both the placement of hubs and the orientation of the hub antennas. Our design methodology is backed up with numerical examples using deterministic channel prediction tools which leads to a robust and smart design of the backhaul network.