Next-generation Wireless Access Networks Research Articles

Wireless Caching: Making Radio Access Networks More than Bit-Pipelines

Caching has attracted much attention recently because it holds the promise of scaling the service capability of radio access networks (RANs). We envision that caching will ultimately make next-generation RANs more than bit-pipelines and emerge as a multi-disciplinary area via the union with communications, pricing, recommendation, compression, and computation units. By summarizing cutting-edge caching policies, we trace a common root of their gains to the prolonged transmission time, which is then traded for higher spectral or energy efficiency. To realize caching, the physical layer and higher layers have to function together, with the aid of prediction and memory units, which substantially broadens the concept of cross-layer design to a multi-unit collaboration methodology. We revisit caching from a generalized cross-layer perspective, with a focus on its emerging opportunities, challenges, and theoretical performance limits. To motivate the application and evolution of caching, we conceive a hierarchical pricing infrastructure that provides incentives to network operators and users. To make RANs even more proactive, we design caching and recommendation jointly, showing a user what it might be interested in and what has been done for it. Furthermore, the user-specific demand prediction motivates edge compression and proactive MEC as new applications. The beyond-bit-pipeline RAN is a paradigm shift that brings with it many cross-disciplinary research opportunities.

Dual-mode index modulation based OFDM system over NOMA networks

Non-orthogonal multiple access (NOMA) scheme is strongly recommended due to its ability to serve multiple users sharing the same frequency and time resources for next-generation radio access networks. Index modulation (IM) over the orthogonal frequency division multiplexing (OFDM) system creates a new dimension for data transmission in terms of subcarrier indices selection bits to enhance the spectral efficiency (SE) through selection diversity gain. By combining IM and conventional OFDM with NOMA, multiple users reap the aforesaid benefits with the variation of power allocation factors and subcarrier indices pattern. Inspired by OFDM-IM NOMA, a dual-mode OFDM-IM technique with NOMA (DM-OFDM-IM NOMA) users is proposed in this paper. The proposed method increases the SE using indices selection bits and data transmission through all the OFDM subcarriers employing different constellation sets. The error performance of the proposed method is evaluated using the maximum-likelihood (ML) and log-likelihood ratio (LLR) detection techniques. The simulation results for the proposed method validates the improvement in SE compared to conventional method over different modulation order. Also, the computational complexity is presented for proposed and existing OFDM-IM NOMA technique using both ML and LLR detectors.

Content Pushing Over Idle Timeslots: Performance Analysis and Caching Gains

Caching holds the promise of scaling the service capability of next-generation radio access networks (RANs), thereby attracting much recent attention in the era of 6G research. To enable caching, popular content items should be proactively pushed to the user ends (UEs) in the placement phase. In practice, most content placement is only allowed to exploit idle spectrum or timeslot that is not occupied by any on-demand transmissions. In this case, however, the performance analysis and optimizations of practical caching gains remain open. In this paper, we are interested in how pushing, as a secondary service, improves the overall performance in terms of energy efficiency and latency reduction. To this end, we formulate a Markovian queueing model, the caching gains of which are optimized via linear programming (LP) with acceptable computational complexity. Our work demonstrates that the peak traffic load due to burst on-demand transmissions, as primary services, can be effectively offloaded by pushing over idle timeslots, leading to substantially reduced power consumption and queueing delay.

A Formally Verified Security Scheme for Inter-gNB-DU Handover in 5G Vehicle-to-Everything

Cellular technology has evolved over the decades for mobile network operators to accommodate the ever-growing demands of services for connecting Vehicle-to-Everything (V2X). The 5G infrastructure facilitates V2X communications, where a small-cell base station operating at ultra-high radio frequency with limited coverage becomes pervasive. These small-cell base stations in 5G-V2X must be strategically deployed near the consumers to realize several use cases. More recently, the architectural split solutions in Next Generation Radio Access Network (NG-RAN) are introduced, in which the gNB is divided into the distributed unit (gNB-DU) and control unit (gNB-CU). This functional split intends to improve scalability, performance, and network orchestration optimization. In this case, frequent user equipment (UE) handover between gNB-DUs is inevitable. However, the current 5G standard did not consider securing the path between these two entities. Hence, the NG-RAN could likely experience various security threats if the current handover procedure standard is employed without changes. Consequently, this paper introduces potential threats like resource depletion at NG-RAN caused by the useless execution of resource-demanding procedures to complete the transfer of attachment of UE to target gNB-DU. Another is UE being denied from accessing services caused by unsuccessful uplink and downlink synchronization during random access procedure execution, requiring establishing security and mutual authentication between the entities. Motivated by this, we proposed a security protocol composed of two phases, namely initial and handover. While the former phase assists in mutual authentication and key agreement between UE and serving gNB-DU, the latter secures UE’s mobility in inter-gNB-DU handover. This protocol aims to preserve the existing quality of service and support essential security requirements, including confidentiality, integrity, mutual authentication, secure key exchange, and perfect forward secrecy. The security requirements are formally verified using BAN logic and Scyther, and the proposed protocol demonstrated lower handover latency than EAP-AKA’, AKA, EAP-TLS, and EAP-IKEv2.

Planning mm-Wave Access Networks Under Obstacle Blockages: A Reliability-Aware Approach

Millimeter-wave (mm-wave) technologies are the main driver to deliver the multiple-Gbps promise in next-generation wireless access networks. However, the GHz-bandwidth potential must coexist with a harsh propagation environment. While strong attenuations can be compensated by directional antenna arrays, the severe impact of obstacle blockages can only be mitigated by smart resource allocation techniques. Multi-connectivity, as multiple mm-wave links from a mobile device to different base stations, is one of them. However, the higher reliability provided by several access alternatives can be fully exploited only if uncorrelated link statuses are guaranteed. Therefore, spatial diversity must be enforced. Moreover, since interposing obstacles can block a link, short access links allow reducing the link unavailability probability. Smart base-station selections can be made once the network is deployed, however, our results show that much better results are achievable if spatial diversity and link-length aspects are directly included in the network planning phase. In this article, we propose an mm-wave access network planning framework that considers base-station spatial diversity, link lengths, and achievable user throughput, according to channel conditions and network congestion. The comparison against traditional k-coverage approaches shows that our approach can obtain much better access reliability, thus providing higher robustness to random obstacles and self-blockage phenomena.

Cooperative Autonomous Driving Oriented MEC-Aided 5G-V2X: Prototype System Design, Field Tests and AI-Based Optimization Tools

Vehicle-to-Everything (V2X) requirements from cooperative autonomous driving can be characterized as ultra-reliable, low latency, high traffic, and high mobility. These requirements introduce great challenges in the air interface and protocol stack design, resource allocation, network deployment, and all the way up to mobile (or multi-access) edge computing (MEC), cloud and application layer. In this paper, we present a cooperative autonomous driving oriented MEC-aided 5G-V2X prototype system design and the rationale behind the design choices. The prototype system is developed based on a next-generation radio access network (NG-RAN) experimental platform, a cooperative driving vehicle platoon, and an MEC server providing high definition (HD) 3D dynamic map service. Field tests are conducted and the results demonstrate that the combination of 5G-V2X, MEC and cooperative autonomous driving can be pretty powerful. Considering the remaining challenges in the commercial deployment of 5G-V2X networks and future researches, we propose two artificial intelligence (AI) based optimization tools. The first is a deep-learning-based tool called deep spatio-temporal residual networks with a permutation operator (PST-ResNet). By providing city-wide user and network traffic prediction, PST-ResNet can help to reduce the capital expense (CAPEX) and operating expense (OPEX) costs of commercial 5G-V2X networks. The second is a swarm intelligence based optimization tool called subpopulation collaboration based dynamic self-adaption cuckoo Search (SC-DSCS), which can be widely used to solve complex optimization problems in future researches. The effectiveness of proposed optimization tools is verified by real-world data and benchmark functions.

Apt-RAN: A Flexible Split-Based 5G RAN to Minimize Energy Consumption and Handovers

The recent adoption of virtualized technologies in Next Generation Radio Access Network (NG-RAN) has driven a significant impact on energy consumption by subsequently decreasing the number of active base stations. The base station (gNodeB) of 5G is segregated into cost-efficient Central Units (CU) hosted on virtual platforms and cheaper & smaller Distributed Units (DU) present at the cell sites. Multiple CUs are pooled together in a single powerful central cloud, known as CU pool. The logical connection between DU and CU can be dynamically adjusted and can potentially affect the energy consumption of the CU pool. The deployment of NG-RAN imposes strict latency requirements on the fronthaul link that connects DUs to CU. To relax these strict latency requirements, various alternate architectures such as Flexible RAN Functional Splits have been proposed by 3GPP. In this paper, we first evaluate the energy consumption of DU and CU for various functional split options using OpenAirInterface (OAI), a real-time open source software radio solution. We find that lower layer splits have high energy consumption at CU as compared to higher layer split options. We also observe the variation in energy consumption due to traffic heterogeneity. Motivated by the above study, we formulate an optimization model, Apt-RAN, that optimizes the energy consumption of the CU pool and the number of handovers, considering different functional splits. To address the computational complexity of solving the optimization model, a lightweight polynomial time heuristic algorithm is proposed. Simulation results demonstrate that our proposed model outperforms existing state-of-art schemes.

On the automation of RAN slicing provisioning: solution framework and applicability examples

Network slicing is a fundamental feature of 5G systems that allows the partitioning of a single network into a number of segregated logical networks, each optimized for a particular type of service, or dedicated to a particular customer or application. While support for network slicing (e.g. identifiers, functions, signalling) is already defined in the latest 3GPP Release 15 specifications, solutions for efficient automated management of network slicing (e.g. automatic provisioning of slices) are still at a much more incipient stage, especially for what concerns the next-generation Radio Access Network (NG-RAN). In this context, and consistently with the new service-based management architecture defined by 3GPP for 5G systems, this paper presents a functional framework for the management of network slicing in a NG-RAN infrastructure, delineating the interfaces and information models necessary to support the dynamic and automatic deployment of RAN slices. A discussion on the complexity of such automation follows together with an illustrative description of the applicability of the overall framework and information models in the context of a neutral host provider scenario that offers RAN slices to third party service providers.

Impact of Virtualization Technologies on Virtualized RAN Midhaul Latency Budget: A Quantitative Experimental Evaluation

In the next-generation radio access network (NG-RAN) defined by 3GPP for the fifth-generation mobile communications, the next-generation NodeB is split into a radio unit (RU), a distributed unit (DU), and a central unit (CU). The RU, DU, and CU are connected through the fronthaul (RU-DU) and midhaul (DU-CU) segments. If the RAN is also a virtualized RAN (VRAN), DU and CU are deployed in virtual machines or containers. Different latency and jitter requirements are demanded on the midhaul according to the distribution of the protocol functions between the DU and CU. This letter shows that in VRAN, the virtualization technologies, the functional split option, and the number of elements deployed in the same computational resource affect the latency budget available for the midhaul. Moreover, it provides an expression for the midhaul allowable latency as a function of the aforementioned parameters. Finally, it shows that the virtualized DUs featuring a lower layer split option shall be deployed not in the same computational resources, where other vDUs are deployed.

Integrated resource optimization with WDM-based fronthaul for multicast-service beam-forming in massive MIMO-enabled 5G networks

Massive MIMO (mMIMO) is a technology with high potential in future 5G radio access networks (RAN). As a crucial feature in mMIMO, beam-forming provides a remarkable enhancement for the wireless transmission. However, beam-forming introduces extra wireless resource and fronthaul bandwidth consumption for utilizing multiple antennas to transmit the same data. Moreover, this problem will be highlighted in the multicast-service beam-forming because more identical data will be transmitted in networks. In this paper, we focus on the entire resource consumption of a single cell for the multicast-service beam-forming in next-generation RAN and propose a flexible wavelength-division-multiplexing-based fronthaul to support the high-capacity and resilient transport. A mixed-integer nonlinear programming formulation and two heuristic algorithms are developed to minimize the utilized optical bandwidth, radio resource blocks and antennas. Simulation comparisons are performed among different resource allocation strategies. Numerical results demonstrate that our strategies can efficiently reduce the total resource consumption.

Semidefinite Relaxation-Based PAPR-Aware Precoding for Massive MIMO-OFDM Systems

Massive MIMO requires a large number of antennas and the same amount of power amplifiers (PAs), one per antenna. As opposed to 4G base stations, which could afford highly linear PAs, next-generation base stations will need to use inexpensive PAs, which have a limited region of linear amplification. One of the research challenges is effectively handling signals which have high peak-to-average power ratios (PAPRs), such as orthogonal frequency division multiplexing (OFDM). This paper introduces a PAPR-aware precoding scheme that exploits the excessive spatial degrees-of-freedom of large scale multiple-input multipleoutput (MIMO) antenna systems. This typically requires finding a solution to a nonconvex optimization problem. Instead of relaxing the problem to minimize the peak power, we introduce a practical semidefinite relaxation (SDR) framework that enables accurately and efficiently approximating the theoretical PAPR-aware precoding performance for OFDM-based massive MIMO systems. The framework allows incorporating channel uncertainties and intercell coordination. Numerical results show that several orders of magnitude improvements can be achieved w.r.t. state of the art techniques, such as instantaneous power consumption reduction and multiuser interference cancellation. The proposed PAPRaware precoding can be effectively handled along with the multicell signal processing by the centralized baseband processing platforms of next-generation radio access networks. Performance can be traded for the computing efficiency for other platforms

Orchestrating Lightpath Recovery and Flexible Functional Split to Preserve Virtualized RAN Connectivity

In the next-generation radio access network (NG RAN), the next-generation evolved NodeBs (gNBs) will be, likely, split into virtualized central units (CUs) and distributed units (DUs) interconnected by a fronthaul network. Because of fronthaul latency and capacity requirements, optical metro-ring networks are among the main candidates for supporting converged 5G and non-5G services. In this scenario, a degradation in the quality of transmission of the lightpaths connecting DU and CU can be revealed (or anticipated) based on monitoring techniques. Thus, the lightpath transmission parameters can be adapted to maintain the required bit error rate (BER). However, in specific cases, the original requested capacity between DU and CU could be not guaranteed, thus impacting the service. In this case, another DU-CU connectivity should be considered, relying on a change of the so-called functional split. This study proposes a two-step recovery scheme orchestrating lightpath transmission adaptation and functional split reconfiguration to guarantee the requested connectivity in a virtualized RAN fronthaul. Results show that, for the connections that cannot be transported by the original lightpath, a graceful degradation followed by a recovery is possible within tens of seconds.

Game-Assisted Distributed Decision Making to Build Virtual TDM-PONs in C-RANs Adaptively

Although a promising solution for next-generation radio access networks (RANs), cloud RAN (C-RAN) still faces technical challenges due to the separate locations of the cloud-based baseband unit (BBU) pool and remote radio heads (RRHs). Fortunately, time- and wavelength-division multiplexing passive optical networks (TWDM-PONs) can efficiently bridge the communications between the BBU pool and RRHs. In this work, we address the problem of formulating virtual time division multiplexing PONs (vTDM-PONs) adaptively in a TWDM-PON-based C-RAN. However, instead of relying on a centralized approach, we develop algorithms that can work in a distributed manner. Specifically, we consider a scenario in which the optical network unit (ONU) of each RRH has the initiative to choose a proper vTDM-PON to register to based on its knowledge on the C-RAN. We formulate game theoretic models for the vTDM-PON formation for both static and dynamic operation of a C-RAN, then transform the games into weighted potential games and therefore prove the existence of Nash equilibrium (NE) points in the games. Moreover, we propose a distributed algorithm that can converge to the NE point(s) to enable each ONU to choose its vTDM-PON intelligently. As a comparison, we formulate a centralized mixed-integer linear programming model to provide the optimum vTDM-PON formation solution. Simulation results confirm the effectiveness of the design of the proposed game models and distributed algorithm.

An Efficient Resource Allocation Mechanism for LTE–GEPON Converged Networks

Optical–wireless convergence is becoming popular as one of the most efficient access network designs that provides quality of service (QoS) guaranteed, uninterrupted, and ubiquitous access to end users. The integration of passive optical networks (PONs) with next-generation wireless access networks is not only a promising integration option but also a cost-effective way of backhauling the next generation wireless access networks. The QoS performance of the PON–wireless converged network can be improved by taking the advantages of the features in both network segments for bandwidth resources management. In this paper, we propose a novel resource allocation mechanism for long term evolution–Gigabit Ethernet PON (LTE–GEPON) converged networks that improves the QoS performance of the converged network. The proposed resource allocation mechanism takes the advantage of the ability to forecast near future packet arrivals in the converged networks. Moreover, it also strategically leverages the inherited features and the frame structures of both the LTE network and GEPON, to manage the available bandwidth resources more efficiently. Using extensive simulations, we show that our proposed resource allocation mechanism improves the delay and jitter performance in the converged network while guarantying the QoS for various next generation broadband services provisioned for both wireless and wired end users. Moreover, we also analyze the dependency between different parameters and the performance of our proposed resource allocations scheme.

차세대 이동통신 네트워크를 위한 무선 액세스 망 구조 및 가상화 시나리오

차세대 모바일 인터넷의 진화에 따라 2G, 3G, 4G, B4G 이동통신 무선접속네트워크가 공존하게 되며, 기존의 통신 서비스 제공자들은 통합 서비스 제공자로 융합되고, 다수의 가상 서비스 제공자들이 발생하게 될 것으로 예상된다. 이러한 복잡한 미래의 융합 서비스를 제공하기 위해서 미래 인터넷에서는 무선 액세스 네트워크가 융합되고 다양한 서비스 제공자들에 의해 공유되는 무선 네트워크 가상화가 필수적이다. 따라서 본 논문에서는 미래 무선 액세스 네트워크 상에서 여러 서비스 제공자들의 다양한 무선 액세스 기술들이 유연하게 통합 운영될 수 있는 무선 액세스 네트워크 가상화를 위한 망 구조와 가상화 시나리오에 대해서 고찰한다. 본 논문에서 도출된 차세대 이동통신 네트워크를 위한 무선 액세스 망 구조 및 가상화 시나리오는 앞으로 무선 액세스 네트워크 가상화 알고리즘 개발을 위한 기틀 역할을 할 수 있을 것으로 기대된다. In accordance with evolution of next-generation mobile Internet, 2G, 3G, 4G, and B4G mobile communication wireless access networks will be co-existed and service providers will be merged as an integrated service provider. In addition, multiple virtual service operators will appear. In order to provide complicated unified-services, in the future Internet, wireless network virtualization where network resource is shared by various service operators is necessary. Therefore, in this paper, we investigate network architectures and virtualization scenarios for wireless access network virtualization where various wireless access technologies are flexibly operated by multiple service providers over next-generation wireless access networks. We expect that the virtualization scenario and network architecture yielded from this study can play a role as a basis for development of wireless access network virtualization algorithms.

Multi-hop relay for next-generation wireless access networks

Multi-hop relay for next-generation wireless access networks

What a mesh! An architecture for next-generation radio access networks

With fourth-generation wireless technologies envisioned to provide high bandwidth for content-rich multimedia applications, next-generation mobile communication systems are well poised to lead the technology march. Incumbent with the new technology is the challenge of providing flexible, reconfigurable architectures capable of catering to the dynamics of the network, while providing cost-effective solutions for service providers. In this article we focus on IP-based radio access network architectures for next-generation mobile systems. We provide an insight into wireless mesh-based connectivity for the RAN network elements - using short high-bandwidth links to interconnect the network entities in a multihop mesh network for backhauling traffic to the core. A generic self-similar fractal topology, using optical wireless transmission technology, is described. We study the performance of the architecture and conclude that mesh-based architectures are well suited to provide highly scalable, dynamic radio access networks with carrier-class features at significantly low system costs.