Passive optical network range applicable to cost-effective mobile fronthaul

The time-division multiplexed-passive optical network (TDM-PON) architecture can efficiently accommodate densely deployed small cells in a centralized radio access network (C-RAN)-based future radio access (FRA). C-RAN is a type of mobile front-haul network, which connects multiple remote radio heads to a baseband unit pool by optical links. The required optical bandwidth in the mobile front-haul of FRA is very large, so it is necessary to efficiently use the optical bandwidth by using in-phase and quadrature-phase (IQ) data compression techniques. This paper proposes an IQ data compression technique that dynamically reduces the required optical bandwidth based on wireless resource allocation, and provides TDM-PON with statistical multiplexing gain. Simulation results showed the achievable compression ratio of the proposed IQ data compression technique. The feasibility of our technique was confirmed by experiments. The reduction in the average TDM-PON bandwidth was 50% when there were 60 mobile terminals, all of which required 0.18 Mbps bandwidth.

Grant management procedure for energy saving TDM-PONs

One of the major shortcomings of Centralized Radio Access Networks (C-RAN) is that the large capacity is required for fronthaul network between Remote Radio Heads (RRHs) and central office with baseband unit (BBU) pool. Possible solutions are to introduce lower-cost networking technology for fronthaul network, such as Time and Wavelength Division Multiplexing Passive Optical Network (TWDM-PON), and to introduce functional split, that moves some baseband processing functions to cell site to decrease the utilization of the fronthaul network. In this paper, we construct the mathematical model for selecting function split options of baseband processing to minimize the power consumption of TWDM-PON based fronthaul network. In detail, we formulate the optimization problem for minimizing the total power consumption of fronthaul network in terms of the capacity of TWDM-PON, the number of RRHs in each cell site, server resources, latency constraints, the amount of traffic from each RRH, physical/virtual server power consumption characteristics. Numerical examples are shown for confirming the correctness of the proposed model and for presenting the effect of resource enhancement methods on the capacity and energy efficiency of the system.

Time Division Multiplexing Passive Optical Networks (TDM-PONs) serve as a key enabler for the evolution of broadband access network infrastructure. As TDM-PONs adapt to support 6G networks, reducing energy consumption becomes increasingly critical. Sleep modes have been widely adopted as an effective energy-saving solution. However, their use can introduce delays that compromise performance. This issue becomes especially problematic in 6G PONs, where ultra-low latency and stringent service requirements leave minimal tolerance for delay-related inefficiencies. In this paper, we propose a novel sleep synchronization mechanism for both single and multiple TDM-PONs, allowing Optical Network Units (ONUs) to join one or more sleep/wake-up groups based on the service type and delay tolerance. Our practical design framework incorporates delay-based grouping and existing sleep modes to address the operational complexities of multi-PON systems while remaining fully compatible with current PON standards. The simulation results show that our approach satisfies the requirements of delay-sensitive traffic and achieves up to 37% energy savings. Compared to baseline methods such as adaptive scheduling and fixed-interval cyclic sleep, it offers a 15–20% improvement in the energy–delay trade-off. These results demonstrate the potential for near-term deployment of 6G PONs and lay the foundation for more advanced, delay-aware energy management strategies in next-generation optical access networks.

Cloud radio access networks (C-RAN) is a potential solution to meet the traffic demand of the future network, which migrates the baseband units (BBU) to the BBU pool in the cloud. The connection between BBU and remote radio head (RRH) can be dynamically changed and the resources can be allocated more flexible according to some factor, e.g., traffic demand of RRHs. Therefore, the resource allocation scheme in C-RAN is redefined, which regards the BBUs as a sharing resource. Existing studies execute the mapping scheme with the consideration of the single BBU but not the whole network, e.g., the BBU with high utilization switches the supported RRH to other BBU to reduce the resource usage. To achieve this goal, this paper makes use of the concept of cloud resources and centralized management to fully utilize the resources and allocate the resources more centralized. The main contribution of this paper is to propose a dynamic BBU–RRH mapping scheme using a borrow-and-lend approach to dynamically allocate the resources to RRHs in a clever and efficient way. With the centralized management, the max busy group borrows the resource for RRH switching, whereas the min helper group lends the resource to handle the switching RRHs. Finally, simulation results illustrate the proposed mechanism in C-RAN significantly reduces the waste of the resource usage and improves the throughput.

Increasing the serial bitrate beyond 10 Gb/s in time division multiplexed passive optical network (TDM-PON) is difficult. The reduced chromatic dispersion tolerance and the reduced signal-to-noise ratio's at higher rates make it much more challenging to achieve the needed optical power budget, especially in a cost-effective way. To combat these challenges, we investigated and demonstrated a 25-Gb/s TDM-PON, with optical amplification at the optical line termination (OLT), based on PAM-4 modulation in the downstream and Duobinary modulation in the upstream. Described in this paper is a first demonstration of a symmetrical 25-Gb/s TDM-PON with 31.5-dB class N2 power budget over 0–20 km at 1556 nm using only cost-effective off-the-shelf 10-Gb/s optical components at the ONU and OLT side. We used small form factor erbium doped fiber amplifiers as booster and preamplifier at the OLT. We also applied low-cost dispersion compensating schemes to increase chromatic dispersion tolerance, a simple predistortion scheme based on optimization of electroabsorption modulated laser bias voltage and a simple fiber dispersion supported transmission scheme. We obtained a power budget of 31.5 dB with 0–20 km of standard single mode fiber, which we doubled to 0–40 km using dispersion compensating fiber at 1556 nm (BER = 10 −3).

In this paper we consider a cloud radio access network (C-RAN) where the remote radio heads (RRHs) are separated from the baseband signal processing servers, named baseband units (BBUs). The latter forms a centralized pool of high-performance data center resources. To benefit from network function virtualization, we consider virtualized BBU (V-BBU) resources where the BBU functionality and services have been virtualized in the form of virtual network functions. All RRHs in the C-RAN form a single cluster. Each RRH of such a cluster may accommodate random or quasi-random traffic. That means that new calls in a RRH can be generated by an infinite number of mobile users (random traffic) or by a finite number of mobile users (quasi-random traffic). An arriving call requires a radio resource unit from the serving RRH and a computational resource unit from the V-BBU. If these resource units are available, then the call is accepted and remains in the system for a generally distributed service time. Otherwise, the call is blocked and lost. In order to analyze this C-RAN we model it as a loss system and study two cases: (i) all RRHs accommodate quasi-random traffic and (ii) some RRHs accommodate random traffic and the rest accommodate quasi-random traffic. In both cases, we show that the steady state probabilities have a product form solution and propose convolution algorithms for the accurate determination of the main teletraffic performance measure which is congestion probability. The accuracy of these algorithms is verified via simulation.

A cost-effective and smooth evolution scheme from a time-division multiplexing–passive optical network (TDM-PON) to a WDM-overlaid PON that can provide high-speed fiber-to-the-home service to a wide area with a high population density is proposed. Existing optical transmitters of TDM-PON optical network units (ONUs) are reusable by employing a wavelength-conversion node at the ONU site, which transforms the wavelength of each ONU to a predefined WDM wavelength. A specially designed optical router is needed at a remote node site; it should broadcast downstream signals to each ONU, routing upstream ONU signals to a wavelength-conversion node and passing the wavelength-converted signal to an optical line terminal. A simple but efficient remote node structure is proposed. A wavelength conversion node should be designed carefully since it repeats burst-mode signals from multiple ONUs. A 2R repeater-based wavelength conversion node is suggested. Performance of various schemes is analyzed and their measurement results are provided.

To meet the 5G requirements in terms of high capacity and enhanced quality of service, the Cloud Radio Access Network (C-RAN) relies on the network densification and coordination. The main idea behind the C- RAN is to split the base station into two parts: the first component is the Remote Radio Head (RRH) which will be responsible for all Radio transmissions and the second one is the Base Band Unit (BBU) which will be responsible for the processing and control. Only the RRH will be densified to offer more capacity. The processing resources will be pooled and clustered so that many RRHs will be managed by one BBU pool which will reduce the related CAPEX and OPEX of the network's deployment, operation and maintenance. The main goal of this paper is to propose an optimized clustering algorithm able to improve interference management between BBU clusters and decrease the network mobility signaling cost. In this work, we will be interested by the implementation and optimization of local search algorithm (Tabu Search) and evolution algorithm (Genetic Algorithm) as well as the combination of both methods in order to enhance the convergent solution.

It is well known that optical access networks are able to provide high data rates over long distances and to a reasonable number of users. Security and privacy are always a challenge for public accessible network infrastructures. Especially in time-division multiplexing passive optical networks (TDM-PONs), in which the downstream signal is broadcasted to all users connected via the same wavelength channel in a shared fiber link, privacy can be a critical concern. Although encryption at the application layer can provide a high level of security, this can be achieved only if the encryption key distribution is perfectly save. On the other hand, encryption on the physical layer such as quantum cryptography or, more precisely, quantum key distribution (QKD) is a very promising approach to achieve secure communication. However, there remain several issues that have to be solved before the quantum cryptography reaches the maturity level needed for a cost effective implementation in practical networks. In this paper, we address quantum key distribution (QKD) over passive optical access networks, which is an enabling technology required to cost efficiently deploy practical quantum encrypted data communication in the access area. We study different methods to integrate QKD systems in conventional optical access networks and quantitatively evaluate their suitability for a potential implementation.

This study describes resilient access network structures in time-division multiplexing passive optical networks (TDM-PONs) and wave-division multiplexing (WDM)/ TDM-PONs, and compares their network unavailability versus outage scale. In addition, this study discusses the unavailability for media networks with simple ladder and more realistic ring-to-tree topologies for cases with simplex and full/partial duplex configurations between drop points and central offices. In large-scale networks, the unavailability in duplex networks is drastically improved by 4-5 orders of magnitude compared with that in simplex networks for large outage scales. Cable failure significantly affects the unavailability, especially in feeder sections, whereas failures due to optical fiber or optical add-drop multiplexers are mostly masked by cable failure in WDM/TDM-PONs. Consequently, there is little difference in the unavailability of the two PON schemes, except for the difference due to PON splitters. A comparison of the unavailability for fully and partially duplicated networks shows that the latter with a ring-to-tree topology has the advantage of lower unavailability in large-scale regions. These results imply that a realistic duplication scheme successfully enhances the network reliability regardless of imperfect duplex structure.

In recent years, the Cloud Radio Access Network (CRAN) has become a promising solution for increasing network capacity in terms of high data rates and low latencies for fifth-generation (5G) cellular networks. In CRAN, the traditional base stations (BSs) are decoupled into remote radio heads (RRHs) and base band units (BBUs) that are respectively responsible for radio and baseband functionalities. The RRHs are geographically proximated whereas the the BBUs are pooled in a centralized cloud named BBU pool. This virtualized architecture facilitates the system to offer high computation and communication loads from the impetuous rise of mobile devices and applications. Heterogeneous service requests from the devices to different RRHs are now sent to the BBUs to process centrally. Meeting the baseband processing of heterogeneous requests while keeping their Quality-of-Service (QoS) requirements with the limited computational resources as well as enhancing service provider profit is a challenging multi-constraint problem. In this work, a multi-objective non-linear programming solution to the Quality-of-Experience (QoE) and Profit-aware Resource Allocation problem is developed which makes a trade-off in between the two. Two computationally viable scheduling algorithms, named First Fit Satisfaction and First Fit Profit algorithms, are developed to focus on maximization of user QoE and profit, respectively, while keeping the minimum requirement level for the other one. The simulation environment is built on a relevant simulation toolkit. The experimental results demonstrate that the proposed system outperforms state-of-the-art works well across the requests QoS, average waiting time, user QoE, and service provider profit.

The work reports the developed planning algorithms for optimum resource allocation over a dynamic 5G infrastructure, addressing all involved types of system resources, from the radio access domain to the MEC domain through the Optical Distribution Network (ODN). A modular modelling design is adopted considering these three domains. In that manner, allocation is composed of three optimization phases, which are executed sequentially and ensure optimal end-to-end allocation of resources. The first allocation phase focuses on the over-the-air resources, which are directly assigned to the 5G mobile users. The key entities for radio access are the Remote Radio Heads (RRHs), which are placed at the edge of the network fronthaul and provide wireless communication slots to the User Equipment (UE). Beamforming capabilities are also assumed allowing each RRH to support simultaneous and independent transmission of multiple directed beams to provide high quality targeted coverage. The resource allocation scheme is responsible for assigning subchannels within specific beams to address the bandwidth requirements of the requested services. The translation from the requested data-rate and the allocated bandwidth is based on the characteristics of 3GPP New Radio (NR) standard. Furthermore, the radio resource allocation process is responsible for assigning different bands for optimal frequency reuse within the available spectrum and avoids interference. The formulated ILP optimization problem, which is solvable in close to real-time due to its low computational complexity, allows dynamic adaptation to requests and resources, with a target to minimize energy consumption. The latter is achievable through the aggregation of wireless resources into individual beams and RRHs. In order to further enhance this process, an RRH prioritization algorithm is introduced for weighting the candidate allocations. With the completion of the first allocation phase, the optical resource allocation phase is initiated. The considered architecture follows that of the EU funded blueSPACE project and consists of a fully flexible ODN exploiting the cutting-edge capabilities of Spectrally Spatially Flexible Optical Networks (SS-FONs). In this context, the allocator considers the spectral and/or spatial multiplexing features of the optical nodes for performing elastic switching. The aim is to establish complete optical routes (lightpaths) from the radio access domain to the Central Office (CO). In particular, the output of this allocation phase is utilized to determine end-to-end fiber-based connections between BBUs and beams. The formulated optimization problem (a low complexity ILP) is able to model any type of network topology and provide optimal paths to dynamic demands according to the available optical domain resources. Power saving is achieved by minimizing the number of the optical elements used for building the required lightpaths. The last allocation phase assigns MEC resources within the blueSPACE virtual Content Delivery Network (vCDN) and Evolved Packet Core (vEPC). The services request MEC resources to offload computationally demanding tasks (such as real-time multimedia processing) and the allocator is responsible to make optimal decisions for the hosting of the required VM instances. The formulated ILP problem provides such a fast decision-making mechanism, while averting the scattering of allocated resources to numerous physical servers in order to conserve energy. With the termination of this third phase, all required network and computing resources are fully allocated for serving dedicated enhanced Mobile Broadband (eMBB) slices. The aforementioned resource allocation algorithms are implemented and simulated in MATLAB. For the evaluation process, two real-world simulation scenarios are considered to assess the allocation effectiveness and energy conservation capabilities for changing traffic requests. One scenario simulates a 5G deployment over a football stadium and the second scenario a deployment over a city park. Due to their coverage requirements the two scenarios lead to different RRH location and connectivity properties. Results show that in the “Stadium” scenario we achieve 50% savings in the number of activated RRHs and beams, while in the “City Park” scenario this metric reaches 67%. With respect to the allocation of optical networking resources, our optimization approach achieves conservation of up to 11% of optical ports and 14% of optical cores for the stadium scenario, while the corresponding results for the “City Park” scenario are 9% and 16%, respectively. Lastly, regarding the MEC resource allocation, the conducted simulations in the context of the “Stadium” scenario have shown 22% average reduction of the activated physical MEC servers (reaching up to 38%), while in the “City Park” scenario these savings average even higher to 68% (reaching up to 91%).

With the advent of Cloud Radio Access Networks (C-RAN) where base band units (BBU) have the ability to dynamically support the bandwidth allocation and centrally manage the bearers transmitted from the remote radio heads (RRH), bandwidth adaptation (BA) mechanism emerges as a promising solution to provide the required resources for C-RAN to provide resources to the bearers during congestion. Existing studies use BA mechanism on congestion management only for LTE system but rarely for C-RAN. To achieve this goal, this paper takes the advantage of dual connectivity with the ability of bearer split to cooperatively provide resources by the serving RRHs, at the same time the mobility robustness and the throughput performance can be improved. The main contribution of this work is to propose an improved BA mechanism for C-RAN with dual connectivity in a centralized concept. More specifically, this work designs a “downgrading index” includes two additional centralized contribution attribute to decide the proportional resource contribution of the bearers which are transmitted by the chosen RRHs and are grouped to assist the serving RRHs. Finally, simulation results illustrate the proposed BA mechanism for C-RAN with dual connectivity significantly reduces the probabilities of the handoff bearer dropping and the bearer blocking.

A deep learning based dynamic bandwidth allocation method for XG-PON based mobile fronthaul for CRAN