The recent widespread use of mobile internet, complemented by the advent of many smart applications, has led to an explosive growth in mobile data traffic over the last few years. This remarkably growing momentum of mobile traffic will most likely continue on a similar trajectory, mainly due to the emerging need of connecting people, machines, and applications in a ubiquitous manner through the mobile infrastructure. As a result, the current and projected dramatic growth of mobile data traffic necessitates the development of fifth-generation (5G) mobile communications technology. 5G promises a mobile broadband experience far beyond current 4G systems. The 5G vision is broad, with stringent design targets that support massive connectivity, extreme broadband, and ultra-low latency. In achieving these expectations, operators and carriers are planning to leverage small cells such as metro, pico, nano, and elastic cells to densify the network and improve the user experience and consequently improve the overall network performance. Although the small-cell concept has been articulated and studied for many years within the 4G LTE framework, the concept has yet to find widespread application mainly due to the cost of deployment. In conventional wireless networks, the cost of macro base stations has been a dominant factor. The cost of a small-cell, on the other hand, is much lower in comparison to that of a macro base station; but efficient and satisfactory operation of all these densely deployed small-cells hinges on smart, economical, and ubiquitous backhaul/fronthaul networks provisioning ultra-low latency, high data rate, and high reliability to meet the global information and communication requirements of future smart and resilient cities and provide ubiquitous connectivity. Hence, there is considerable market interest for the development of innovative and smart backhaul and fronthaul solutions for ultra-dense heterogeneous networks.
It is envisioned that 5G networks will mostly be deployed for data-centric applications. Therefore, one of the main considerations that operators are facing today is how to migrate existing backhaul/fronthaul infrastructure toward Internet Protocol (IP)-based solutions for hyper dense small-cell deployment. Moreover, the data rates of 5G networks will demand an optical backhaul/fronthaul such as fiber. However, it's unlikely that fiber will be economical for all installation sites. Operators will also face deployment restrictions for laying the fiber in many developed areas. Millimeter-wave backhaul/fronthaul is an attractive option, but technological and regulatory challenges are yet to be addressed. Another possible emergent solution is to exploit the interworking and joint design of open-access and backhaul/fronthaul network architecture for hyper dense small-cells based on cloud networks. This requires adaptive and smart backhauling/fronthauling solutions that optimize their operations jointly with the access network optimization. The availability, convergence, and economics of smart backhauling/fronthauling systems are the most important factors in selecting the appropriate backhaul/fronthaul technologies. Hence, it is imperative to analyze the variety of end-to-end backhaul and fronthaul solutions for 5G and Beyond 5G (B5G) networks. The Best Readings list is expected to provide several archival papers and special issues on the backhaul/fronthaul and related networking, communication, and signal processing issues that are currently available.
Issued February 2019
Contributors
Muhammad Zeeshan Shakir
Assistant Professor
School of Computing, Engineering and Physical Sciences
University of the West of Scotland
Paisley, United Kingdom
Walid Saad
Associate Professor
Bradley Department of Electrical and Computer Engineering
Virginia Tech
Blacksburg, Virginia, USA
Muhammad Ali Imran
Professor
School of Engineering
University of Glasgow
Glasgow, United Kingdom
Editorial Staff
Matthew C. Valenti
Editor-in-Chief, ComSoc Best Readings
West Virginia University
Morgantown, WV, USA
- Books
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M. A. Imran, S. A. R. Zaidi, and M. Z. Shakir, Access, Fronthaul and Backhaul Networks for 5G & Beyond, IET Press, 2017.
This book provides a comprehensive overview of latest technologies in radio access, fronthaul, and backhaul sections of the network. It covers the concepts behind emerging technologies as well as results from trials in the field.K. M. Saidul Huq and J. Rodriguez, Backhauling / Fronthauling for Future Wireless Systems, Wiley-Blackwell, 2016.
This book covers recent contributions on backhaul/fronthaul technologies from both academic and industrial perspectives. Topics range from fundamentals, new technologies, and standards.V. Camarchia, M. Pirola, and R. Quaglia, Electronics for Microwave Backhaul, Artech House, 2016.
This book provides an overview of the electronics that enable mobile network backhaul networks. The building blocks of specific backhaul features are covered. - Overviews and Tutorials
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I. A. Alimi, A. L. Teixeira, and P. P. Monteiro, “Toward an Efficient C-RAN Optical Fronthaul for the Future Networks: A Tutorial on Technologies, Requirements, Challenges, and Solutions,” IEEE Communications Surveys & Tutorials, vol. 20, no. 1, pp. 708-769, First Quarter 2018.
M. Jaber, M. A. Imran, R. Tafazolli, and A. Tukmanov, “5G Backhaul Challenges and Emerging Research Directions: A Survey,” IEEE Access, vol. 4, pp. 1743-1766, 2016.
M. Peng, C. Wang, V. Lau, and H. V. Poor, “Fronthaul-Constrained Cloud Radio Access Networks: Insights and Challenges,” IEEE Wireless Communications, vol. 22, no. 2, pp. 152-160, April 2015.
U. Siddique, H. Tabassum, E. Hossain, and D. I. Kim, “Wireless Backhauling of 5G Small Cells: Challenges and Solution Approaches,” IEEE Wireless Communications, vol. 22, no. 5, pp. 22-31, October 2015.
J. Bartelt, P. Rost, D. Wubben, J. Lessmann, B. Melis, and G. Fettweis, “Fronthaul and Backhaul Requirements of Flexibly Centralized Radio Access Networks,” IEEE Wireless Communications, vol. 22, no. 5, pp. 105-111, October 2015.
X. Ge, H. Cheng, M. Guizani, and T. Han, “5G Wireless Backhaul Networks: Challenges and Research Advances,” IEEE Network, vol. 28, no. 6, pp. 6-11, November-December 2014.
A. Aijaz, H. Aghvami, and M. Amani, “A Survey on Mobile Data Offloading: Technical and Business Perspectives,” IEEE Wireless Communications, vol. 20, no. 2, pp. 104-112, April 2013.
O. Tipmongkolsilp, S. Zaghloul, and A. Jukan, “The Evolution of Cellular Backhaul Technologies: Current Issues and Future Trends,” IEEE Communications Surveys & Tutorials, vol. 13, no. 1, pp. 97-113, First Quarter 2011.
Z. Gao, L. Dai, X. Gao, M. Z. Shakir, and Z. Wang, “Fronthaul Design for mmWave Massive MIMO,” Chapter 12 of mmWave Massive MIMO: A Paradigm for 5G, Academic Press, 2017, pp. 289-312.
- Special Issues
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“Smart Backhauling and Fronthauling for 5G Networks: From Precoding to Network Architecture,” IEEE Wireless Communications, vol. 22, no. 5, pp. 10-111, October 2015.
“Mobile Backhaul for Small Cells,” IEEE Communications Magazine, vol. 51, no. 9, pp. 60-107, September 2013.
“Emerging Technologies in Tactile Internet and Backhaul/Fronthaul Networks,” IEEE Journal on Selected Areas in Communications, vol. 36, no. 11, pp. 2387-2590, November 2018.
- Standards-Related Articles
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N. Eiselt et al., “Performance Comparison of 112-Gb/s DMT, Nyquist PAM4, and Partial-Response PAM4 for Future 5G Ethernet-Based Fronthaul Architecture,” Journal of Lightwave Technology, vol. 36, no. 10, pp. 1807-1814, May 15, 2018.
G. Talli et al., “SDN Enabled Dynamically Reconfigurable High Capacity Optical Access Architecture for Converged Services,” Journal of Lightwave Technology, vol. 35, no. 3, pp. 550-560, February 1, 2017.
R. Zhang et al., “Connecting a City by Wireless Backhaul: 3D Spatial Channel Characterization and Modeling Perspectives,” IEEE Communications Magazine, vol. 55, no. 5, pp. 62-69, May 2017.
“IEEE Standard for Radio Over Ethernet Encapsulations and Mappings,” IEEE 1914.3-2018, October 2018.
- Topic: Fronthaul and Backhaul Architecture
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A. D. La Oliva et al., “Xhaul: Toward an Integrated Fronthaul/Backhaul Architecture in 5G Networks,” IEEE Wireless Communications, vol. 22, no. 5, pp. 32-40, October 2015.
This article focuses on developing a 5G integrated backhaul and fronthaul transport network enabling flexible and software-defined reconfiguration of all networking elements in a multi-tenant and service-oriented unified management environment. Key challenges are identified for the proposed architecture including new technologies for ultra-capacity, unified data and control plane designs, and context-aware resource orchestration for joint optimization.A. Pizzinat, P. Chanclou, F. Saliou, and T. Diallo, “Things You Should Know About Fronthaul,” Journal of Lightwave Technology, vol. 33, no. 5, pp. 1077-1083, March 2015.
This paper presents a detailed review of a new fronthaul network segment that appears in centralized radio access network (C-RAN) architecture. Additionally, the paper discusses key requirements of various fronthaul architecture and solutions pertaining to 5G and beyond networks.N. J. Gomes et al., “Boosting 5G Through Ethernet: How Evolved Fronthaul Can Take Next-Generation Mobile to the Next Level,” IEEE Vehicular Technology Magazine, vol. 13, no. 1, pp. 74-84, March 2018.
This paper studies Ethernet as a new transport protocol for the fronthaul architecture that allows statistical multiplexing and enables convergence between fixed and mobile services. Ethernet is proposed as a transport protocol in terms of cost, standardized network control and management functions, software-defined networking, and extending existing means of network monitoring and tools for optimization.X. Costa-Perez et al., “5G-Crosshaul: An SDN/NFV Integrated Fronthaul/Backhaul Transport Network Architecture,” IEEE Wireless Communications, vol. 24, no. 1, pp. 38-45, February 2017.
This article presents an innovative architecture design for a 5G transport solution (dubbed 5G-Crosshaul) integrating existing and new fronthaul and backhaul technologies and interfaces. Some of the key features of the design include an SDN/NFV-based management and orchestration entity and an Ethernet-based packet forwarding entity supporting various fronthaul and backhaul traffic QoS profiles. The proposed design supports the concept of network slicing for realizing a truly flexible, sharable, and cost-effective future 5G system.X. Li et al., “5G-Crosshaul Network Slicing: Enabling Multi-Tenancy in Mobile Transport Networks,” IEEE Communications Magazine, vol. 55, no. 8, pp. 128-137, August 2017.
This article presents the 5G transport network architecture designed in the 5G-Crosshaul project. An SDN/NFV-based control plane has been designed that enables multi-tenancy through network slicing. The proposed solution allows for flexible and efficient allocation of transport network resources (networking and computing) to multiple tenants by leveraging widespread architectural frameworks for NFV (ETSI NFV) and SDN (e.g., Open Daylight and ONOS).N. J. Gomes, P. Chanclou, P. Turnbull, A. Magee, and V. Jungnickel, “Fronthaul Evolution: From CPRI to Ethernet,” Optical Fiber Technology, vol. 26, Part A, pp. 50-58, December 2015.
This paper proposes a new fronthaul functional division that can alleviate the most demanding bit-rate requirements by transport of baseband signals instead of sampled radio waveforms and can enable statistical multiplexing gains. Such a fronthaul can also make use of Ethernet switches and networking statistical multiplexing gains, as it transports relatively bursty data instead of continuous radio waveforms.A. Checko, A. P. Avramova, M. S. Berger, and H. L. Christiansen, “Evaluating C-RAN Fronthaul Functional Splits in Terms of Network Level Energy and Cost Savings,” Journal of Communications and Networks, vol. 18, no. 2, pp. 162-172, April 2016.
This paper proposes a mathematical model that quantifies the multiplexing gains and the trade-offs between centralization and decentralization with respect to the cost of the pool, fronthaul network capacity, and resource utilization. A new principle for fronthaul dimensioning based on the traffic profile is presented. The principle allows for radio access networks with efficient multiplexing gains that simultaneously achieve the expected quality of service.M. Jaber, M. A. Imran, R. Tafazolli, and A. Tukmanov, “A Distributed SON-Based User-Centric Backhaul Provisioning Scheme,” IEEE Access, vol. 4, pp. 2314-2330, 2016.
This article proposes a novel, distributed, self-optimized, end-to-end user-cell-backhaul association scheme that intelligently associates users with candidate cells based on corresponding dynamic radio and backhaul conditions while abiding the users' requirements. The paper presents a proof-of-concept through a case study simulating a simplified version of the user-centric backhaul and demonstrates that the presented approach improves the users’ QoE by 55% relative to throughput and 11% relative to latency while maintaining total system throughput comparable to the maximum throughput approach.T. Ding, X. Yuan, and S. C. Liew, “Network-Coded Fronthaul Transmission for Cache-Aided C-RAN,” in Proc. IEEE International Symposium on Information Theory (ISIT), Aachen, Germany, June 2017.
This article studies the cache-aided cloud radio access network (C-RAN) with wireless fronthaul, where multiple cache-enabled users are served by multiple cache-enabled transmitters that are connected to a cloud processor through a wireless fronthaul link. An achievable normalized delivery time (NDT) is derived with respect to the cache sizes and the fronthaul capacity. - Topic: Smart City
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F. Tonini, M. Fiorani, M. Furdek, C. Raffaelli, L. Wosinska, and P. Monti, “Radio and Transport Planning of Centralized Radio Architectures in 5G Indoor Scenarios,” IEEE Journal on Selected Areas in Communications, vol. 35, no. 8, pp. 1837-1848, August 2017.
This paper proposes different deployment strategies to minimize the centralized radio architecture (CRA) deployment cost. An optimization problem is formulated and solved heuristically to minimize (1) the number of active sites in a residential area that host remote radio units (RRUs) and (2) the total number of deployed RRUs. The proposed strategies are able to achieve almost a 60% cost savings with respect to a conventional approach based on radio over fiber.M. Alzenad, M. Z. Shakir, H. Yanikomeroglu, and M. S. Alouini, “FSO-Based Vertical Backhaul/Fronthaul Framework for 5G+ Wireless Networks,” IEEE Communications Magazine, vol. 56, no. 1, pp. 218-224, January 2018.
This article studies the feasibility of a novel vertical backhaul/fronthaul framework where networked-flying platforms (NFPs) transport the backhaul/fronthaul traffic between the access and core networks via point-to-point FSO links. The efficacy of the proposed system is investigated in terms of link budget and achievable data rate. Simulations show that the key challenge is the high path loss under some weather conditions. However, performance can be improved significantly and rates on the order of multi Gb/s can be achieved by reducing the divergence angle. An economic study shows that the vertical network has a high total cost of ownership compared to terrestrial backhaul/fronthaul networks. - Topic: Performance of Backhaul and Fronthaul Networks
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D. Chitimalla, K. Kondepu, L. Valcarenghi, M. Tornatore, and B. Mukherjee, “5G Fronthaul-Latency and Jitter Studies of CPRI over Ethernet,” IEEE/OSA Journal of Optical Communications and Networking, vol. 9, no. 2, pp. 172-182, February 2017.
By reporting on FPGA-based Verilog experiments and simulations, this paper investigates whether CPRI over Ethernet (CoE) can meet delay and jitter requirements. The paper shows that the proposed scheduling policy of CoE flows on Ethernet can reduce jitter when redundant Ethernet capacity is provided.S. H. Park, O. Simeone, and S. Shamai (Shitz), “Joint Optimization of Cloud and Edge Processing for Fog Radio Access Networks,” IEEE Transactions on Wireless Communications, vol. 15, no. 11, pp. 7621-7632, November 2016.
This paper studies the joint design of cloud and edge processing for the downlink of a fog radio access network (F-RAN) where each edge node is equipped with not only the functionalities of standard C-RAN remote radio heads (RRHs), but also with local cache and baseband processing capabilities. Two basic fronthauling modes are proposed: hard- and soft-transfer fronthauling, as well as a hybrid mode. Specifically, with the hard-transfer mode, the fronthaul links transport the requested files that are not in the local caches. Numerical results show that the soft-transfer mode provides a more effective way to use fronthaul resources than the hard-transfer mode in most operating regimes except for regimes with very low SNR and/or moderate fronthaul capacity. - Topic: Millimeter-wave Based Backhaul
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S. Singh, M. N. Kulkarni, A. Ghosh, and J. G. Andrews, “Tractable Model for Rate in Self-Backhauled Millimeter Wave Cellular Networks,” IEEE Journal on Selected Areas in Communications, vol. 33, no. 10, pp. 2196-2211, October 2015.
By using stochastic geometry, this paper develops a tractable model that characterizes the rate distribution of self-backhauled mmWave networks. The key results show that the rate and spectral efficiency of mmWave networks increase with BS density, particularly at the cell edge. While increasing the system bandwidth improves boost peak rates, it has no influence on cell edge rate.S.Hur, T. Kim, D. J. Love, J. V. Krogmeier, T. A. Thomas, and A. Ghosh, “Millimeter Wave Beamforming for Wireless Backhaul and Access in Small Cell Networks,” IEEE Transactions on Communications, vol. 61, no. 10, pp. 4391-4403, October 2013.
This paper shows how to leverage outdoor mmWave links to enable backhauling between cells and mobile access in a multi-tier cellular network. The key is to use beamforming techniques to overcome the challenges of mmWave propagation. The results reveal the tradeoff between array size and wind-induced movement and its impact on beam alignment.Z. Gao, L. Dai, D. Mi, Z. Wang, M. A. Imran, and M. Z. Shakir, “MmWave Massive-MIMO-Based Wireless Backhaul for the 5G Ultra-Dense Network,” IEEE Wireless Communications, vol. 22, no. 5, pp. 13-21, October 2015.
This paper advocates the integration of massive MIMO with mmWave communications to facilitate high rate wireless backhauling. Various design aspects, such as precoding and architecture, for integrated massive MIMO-mmWave backhauls are outlined and analyzed.R. Taori and A. Sridharan, “Point-to-Multipoint In-Band mmWave Backhaul for 5G Networks,” IEEE Communications Magazine, vol. 53, no. 1, pp. 195-201, January 2015.
This paper primarily focuses on the feasibility and challenges of in-band backhauling in mmWave networks. The results show performance under different deployment and scheduling schemes.O. Semiari, W. Saad, M. Bennis, and Z. Dawy, “Inter-Operator Resource Management for Millimeter Wave, Multi-Hop Backhaul Networks,” IEEE Transactions on Wireless Communications, vol. 16, no. 8, pp. 5258-5272, August 2017.
This paper studies how multi-hop mmWave backhaul networks can be dynamically formed to service the access traffic, while taking into account environmental characteristics. The network formation process is coupled with an economic incentive solution that sheds light on how operators can share their backhaul resources to meet their load requirements.Y. Li, E. Pateromichelakis, N. Vucic, J. Luo, W. Xu, and G. Caire, “Radio Resource Management Considerations for 5G Millimeter Wave Backhaul and Access Networks,” IEEE Communications Magazine, vol. 55, no. 6, pp. 86-92, June 2017.
This paper first uncovers the key challenges and architecture design choices for radio resource management in 5G millimeter wave backhaul networks. Then, it introduces a framework that allows joint backhaul and access operation for 5G mmWave radio access networks. - Topic: Resource Allocation
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M. Chen, M. Mozaffari, W. Saad, C. Yin, M. Debbah, and C. S. Hong, “Caching in the Sky: Proactive Deployment of Cache-Enabled Unmanned Aerial Vehicles for Optimized Quality-of-Experience,” IEEE Journal on Selected Areas in Communications (JSAC), vol. 35, no. 5, pp. 1046-1061, May 2017.
This paper studies resource management for CRAN systems that use fronthauling via unmanned aerial vehicles and in presence of caching. The paper leverages tools from machine learning to predict user content requests and their mobility, so as to solve joint resource management and cell association problems in networks whose fronthaul serves both regular RRHs as well as cache-enabled flying drones.A. Delmade et al., “Performance Analysis of Analog IF over Fiber Fronthaul Link with 4G and 5G Coexistence,” IEEE/OSA Journal of Optical Communications and Networking, vol. 10, no. 3, pp. 174-182, March 2018.
This work demonstrates the spectral containment of fourth generation (4G) Long-Term Evolution (LTE) signals and 5G candidate waveforms-generalized frequency division multiplexing and universally filtered orthogonal frequency division multiplexing (UF-OFDM) through a directly modulated link. The paper demonstrates the fronthaul network for providing simultaneous 4G and 5G services by propagating LTE signals in coexistence with UF-OFDM.D. W. K. Ng, E. S. Lo, and R. Schober, “Energy-Efficient Resource Allocation in Multi-Cell OFDMA Systems with Limited Backhaul Capacity,” IEEE Transactions on Wireless Communications, vol. 11, no. 10, pp. 3618-3631, October 2012.
This paper studies the impact of a capacity-limited backhaul on resource management in an OFDMA system. Using an iterative scheduling scheme, the paper unveils key tradeoffs between energy efficiency, network capacity, and backhaul capacity.Y. Niu, C. Gao, Y. Li, L. Su, D. Jin, and A. V. Vasilakos, “Exploiting Device-to-Device Communications in Joint Scheduling of Access and Backhaul for mmWave Small Cells,” IEEE Journal on Selected Areas in Communications, vol. 33, no. 10, pp. 2052-2069, October 2015.
This paper investigates a joint backhaul and radio access resource management approach at mmWave bands, in presence of D2D links. The work introduces a concurrent transmission scheduling algorithm to fully exploit spatial reuse in mmWave networks and then shows improvements in delay and throughput.B. Li, D. Zhu, and P. Liang, “Small Cell In-Band Wireless Backhaul in Massive MIMO Systems: A Cooperation of Next-Generation Techniques,” IEEE Transactions on Wireless Communications, vol. 14, no. 12, pp. 7057-7069, December 2015.
The goal of this work is to study in-band backhauling in a massive MIMO network with full-duplex capabilities, while taking into account self-interference cancellation techniques. Complete time-division duplex (CTDD), zero-division duplex (ZDD), and ZDD with interference rejection (ZDD-IR), techniques are proposed and contrasted.L. Sanguinetti, A. L. Moustakas, and M. Debbah, “Interference Management in 5G Reverse TDD HetNets with Wireless Backhaul: A Large System Analysis,” IEEE Journal on Selected Areas in Communications, vol. 33, no. 6, pp. 1187-1200, June 2015.
The goal of this paper is to study interference management for a network having a microcell base station with a large number of antennas that uses a wireless backhaul to connect to small cell base stations. Under a TDD protocol, the paper analyzes the asymptotic regime where the number of BS antennas and the network size (MUEs and SCAs) grow large with fixed ratios while deriving UL and DL transmit powers and precoding vectors so as to understand how the system can better manage its interference. - Topic: Fronthaul and Backhaul Signal Processing
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S. H. Park, O. Simeone, O. Sahin, and S. Shamai (Shitz), “Fronthaul Compression for Cloud Radio Access Networks: Signal Processing Advances Inspired by Network Information Theory,” IEEE Signal Processing Magazine, vol. 31, no. 6, pp. 69-79, November 2014.
This article provides a survey of work on fronthaul compression with an emphasis on advanced signal processing solutions based on network information theoretic concepts. The performance of conventional point-to-point compression strategies can be substantially improved by leveraging techniques inspired by network information theory.T. X. Vu, H. D. Nguyen, and T. Q. S. Quek, “Adaptive Compression and Joint Detection for Fronthaul Uplinks in Cloud Radio Access Networks,” IEEE Transactions on Communications, vol. 63, no. 11, pp. 4565-4575, November 2015.
This paper provides a thorough study of compression on fronthaul uplinks and proposes a joint decompression algorithm at the BBU. A joint decompression and detection (JDD) algorithm is proposed and evaluated in terms of its block error rate (BLER). The proposed adaptive compression schemes can achieve a compression ratio of 300% in experimental setups.X. Rao and V. K. N. Lau, “Distributed Fronthaul Compression and Joint Signal Recovery in Cloud-RAN,” IEEE Transactions on Signal Processing, vol. 63, no. 4, pp. 1056-1065, February 15, 2015.
This paper proposes a distributed fronthaul compression scheme at distributed RRHs and a joint recovery algorithm at the BBUs by using distributed compressive sensing (CS). The proposed algorithm incorporates multiple-access fading in C-RAN system into the CS formulation and then conducts an end-to-end recovery of the transmitted signals from the users. A detailed analysis shows the probability of correct active user detection and quantifies the tradeoff rbetween the uplink capacity and the distributed fronthaul loading in C-RANs.L. Liu and R. Zhang, “Optimized Uplink Transmission in Multi-Antenna C-RAN with Spatial Compression and Forward,” IEEE Transactions on Signal Processing, vol. 63, no. 19, pp. 5083-5095, October 1, 2015.
This paper proposes a new “spatial-compression-and-forward (SCF)” scheme for efficient and low-complexity processing at each RRH in the uplink multiuser communication by exploiting joint optimization across the wireless transmission, fronthaul quantization, and decoding at the BBU. It has been shown that a scheme with joint resource allocation achieves significant performance gains over the conventional “quantize-and-forward” based single-antenna C-RAN as well as massive MIMO. - Topic: Optical Transport Networks
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A. Delmade et al., “Performance Analysis of Analog IF over Fiber Fronthaul Link with 4G and 5G Coexistence,” IEEE/OSA Journal of Optical Communications and Networking, vol. 10, no. 3, pp. 174-182, March 2018.
This paper experimentally demonstrates the direct modulation-based spectral containment of GFDM and UF-OFDM using the analog intermediate frequency signal over fiber (AIFoF) fronthauling scheme. The effect on the performance of LTE in coexistence with UF-OFDM for transmission through the same fronthaul link is demonstrated. Results show that the EVM of LTE and UF-OFDM bands are well below the FEC limit, allowing successful delivery of different wireless services with different baseband sample rates through the same fronthaul networks.F. Lu et al., “Efficient Mobile Fronthaul Incorporating VLC Links for Coordinated Densified Cells,” IEEE Photonics Technology Letters, vol. 29, no. 13, pp. 1059-1062, July 1, 2017.
This paper proposes a novel hybrid mobile fronthaul (MFH) architecture combining spectral efficient fiber MFH and low-cost VLC links to support cell coordination in a spatial densified network. The MFH network is capable of delivering eight independent streams serving one master RRH and six slave RRHs with eight CA or 8×8 network MIMO (with additional processing). The system with either distributed or centralized pre-equalization has a good performance suitable for 64-QAM modulation with a received optical power (ROP) of −9.3-dBm or −5.7-dBm. - Topic: Green Backhaul/Fronthaul
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A. Bisognin et al., “Ball Grid Array Module with Integrated Shaped Lens for 5G Backhaul/Fronthaul Communications in F-Band,” IEEE Transactions on Antennas and Propagation, vol. 65, no. 12, pp. 6380-6394, December 2017.
This paper proposes a ball grid array (BGA) module with an integrated 3-D-printed plastic lens antenna for application in a dedicated 130 GHz OOK transceiver that targets the area of 5G backhaul/fronthaul systems. Data rates higher than 12 Gbps with a BER less than 10−6 at nearly 5 m can be achieved with the proposed architecture. These results are promising, and the performance achieved represents a contribution to cost-effective, energy-efficient backhaul/fronthaul systems for 5G.L. Liu, S. Bi and R. Zhang, “Joint Power Control and Fronthaul Rate Allocation for Throughput Maximization in OFDMA-Based Cloud Radio Access Network,” IEEE Transactions on Communications, vol. 63, no. 11, pp. 4097-4110, November 2015.
This paper studies joint wireless power control and fronthaul quantization design over the sub-carriers to maximize the system throughput. The fronthaul capacity constraints have significant impact on the optimal wireless power control policy. Throughput performance of the proposed simple uniform scalar quantization is very close to the performance upper (cut-set) bound. This confirms that high throughput performance could be practically achieved with C-RAN using simple fronthaul signal quantization methods. - On the Web