On the Transport Capability of LAN Cables in All-Analog MIMO-RoC Fronthaul

Centralized Radio Access Network (C-RAN) architecture is the only viable solution to handle the complex interference scenario generated by massive antennas and small cells deployment as required by next generation (5G) mobile networks. In conventional C-RAN, the fronthaul links used to exchange the signal between Base Band Units (BBUs) and Remote Antenna Units (RAUs) are based on digital baseband (BB) signals over optical fibers due to the huge bandwidth required. In this paper we evaluate the transport capability of copper-based all-analog fronthaul architecture called Radio over Copper (RoC) that leverages on the pre-existing LAN cables that are already deployed in buildings and enterprises. In particular, the main contribution of the paper is to evaluate the number of independent BB signals for multiple antennas system that can be transported over multi-pair Cat-5/6/7 cables under a predefined fronthauling transparency condition in terms of maximum BB signal degradation. The MIMO-RoC proves to be a complementary solution to optical fiber for the last 200m toward the RAUs, mostly to reuse the existing LAN cables and to power-supply the RAUs over the same cable

Sparse Beamforming for Real-Time Resource Management and Energy Trading in Green C-RAN

This paper considers cloud radio access network with simultaneous wireless information and power transfer and finite capacity fronthaul, where the remote radio heads are equipped with renewable energy resources and can trade energy with the grid. Due to uneven distribution of mobile radio traffic and inherent intermittent nature of renewable energy resources, the remote radio heads may need real-time energy provisioning to meet the users' demands. Given the amount of available energy resources at remote radio heads, this paper introduces two provisioning strategies to strike an optimum balance among the total power consumption in the fronthaul, through adjusting the degree of partial cooperation among the remote radio heads, the total transmit power and the maximum or the overall real-time energy demand. More specifically, this paper formulates two sparse optimization problems and applies reweighted ℓ 1 -norm approximation for ℓ 0 -norm and semidefinite relaxation to develop two iterative algorithms for the proposed strategies. Simulation results confirm that both of the proposed strategies outperform two other recently proposed schemes in terms of improving energy efficiency and reducing overall energy cost of the network

Tutorial on LTE/LTE-A Cellular Network Dimensioning Using Iterative Statistical Analysis

LTE is the fastest growing cellular technology and is expected to increase its footprint in the coming years, as well as progress toward LTE-A. The race among operators to deliver the expected quality of experience to their users is tight and demands sophisticated skills in network planning. Radio network dimensioning (RND) is an essential step in the process of network planning and has been used as a fast, but indicative, approximation of radio site count. RND is a prerequisite to the lengthy process of thorough planning. Moreover, results from RND are used by players in the industry to estimate preplanning costs of deploying and running a network; thus, RND is, as well, a key tool in cellular business modelling. In this work, we present a tutorial on radio network dimensioning, focused on LTE/LTE-A, using an iterative approach to find a balanced design that mediates among the three design requirements: coverage, capacity, and quality. This approach uses a statistical link budget analysis methodology, which jointly accounts for small and large scale fading in the channel, as well as loading due to traffic demand, in the interference calculation. A complete RND manual is thus presented, which is of key importance to operators deploying or upgrading LTE/LTE-A networks for two reasons. It is purely analytical, hence it enables fast results, a prime factor in the race undertaken. Moreover, it captures essential variables affecting network dimensions and manages conflicting targets to ensure user quality of experience, another major criterion in the competition. The described approach is compared to the traditional RND using a commercial LTE network planning tool. The outcome further dismisses the traditional RND for LTE due to unjustified increase in number of radio sites and related cost, and motivates further research in developing more effective and novel RND procedures

Centralized and partial decentralized design for the Fog Radio Access Network

Fog Radio Access Network (F-RAN) has been shown to be a promising network architecture for the 5G network. With F-RAN, certain amount of signal processing functionalities are pushed from the Base Station (BS) on the network edge to the BaseBand Units (BBU) pool located remotely in the cloud. Hence, partially centralized network operation and management can be achieved, which can greatly improve the energy and spectral efficiency of the network, in order to meet the requirements of 5G. In this work, the optimal design for both uplink and downlink of F-RAN are intensively investigated

Joint Fronthaul Load Balancing and Computation Resource Allocation in Cell-Free User-Centric Massive MIMO Networks

We consider scalable cell-free massive multiple-input multiple-output networks under an open radio access network paradigm comprising user equipments (UEs), radio units (RUs), and decentralized processing units (DUs). UEs are served by dynamically allocated user-centric clusters of RUs. The corresponding cluster processors (implementing the physical layer for each user) are hosted by the DUs as software-defined virtual network functions. Unlike the current literature, mainly focused on the characterization of the user rates under unrestricted fronthaul communication and computation, in this work we explicitly take into account the fronthaul topology, the limited fronthaul communication capacity, and computation constraints at the DUs. In particular, we systematically address the new problem of joint fronthaul load balancing and allocation of the computation resource. As a consequence of our new optimization framework, we present representative numerical results highlighting the existence of an optimal number of quantization bits in the analog-to-digital conversion at the RUs.Comment: 13 pages, 5 figures, submitted to IEEE Transactions on Wireless Communication