What is 5G Mobile Edge Computing (MEC)?

As Open RAN, beamforming, and Massive MIMO transform the mobile network landscape, the real time intelligence needed for dynamic spectrum allocation, beam management, and service assurance continues to move closer to the edge of the network. With an unmatched portfolio of network monitoring, fiber certification, 5G RAN optimization, and access testing solutions, VIAVI is uniquely qualified to support the expansion of mobile edge computing that comes with 5G adoption.

VIAVI maintains a dedication to testing and assurance throughout the network lifecycle. Advanced emulation and certification tools for the lab expedite and optimize edge data center performance in the field. Cloud-enabled fiber and application test solutions with automated workflows simplify deployment while remote 24/7 monitoring capabilities enable efficient and reliable “lights out” edge data center operation.

  • By migrating computing infrastructure closer to the radio access network (RAN) and end user, increased user density, high-speed transmission, and ultra-low latency requirements introduced by 5G use cases become achievable. Shifting the computing burden to the network edge reduces traffic congestion and improves overall quality of experience (QoE). 5G Distributed Architecture divides the functionality of a traditional base station between a Radio Unit (RU), Distributed Unit (DU) and Centralized Unit (CU). A DU situated at the edge of the network supports lower levels of the protocol stack for a variety of mobility scenarios. To facilitate 5G edge densification, many distributed units can be connected through a single centralized unit closer to the Core network.
  • Massive MIMO (multiple-input, multiple-output) technology utilizes large antenna arrays to improve spectral efficiency and coverage. “Super-massive” MIMO connects multiple arrays together. Steerable antennas within these arrays require precise alignment and real time synchronization that can only be attained through 5G edge computing.
  • The European Telecommunications Standards Institute (ETSI) has established the MEC industry specification group (ISG) to develop a unified standard for edge computing that ensures interoperability for all stakeholders. This standardization brings the telco and cloud ecosystems into alignment and allows third parties to deploy mobile applications more easily.

Multi access edge computing increases flexibility for all access technologies by shifting intelligence, applications, and decisions further from centralized data centers and closer to the user and/or IoT application. Latency reduction and efficiency are enhanced with 5G and edge computing working in tandem, along with QoS and reliability.

  • 5G/6G Performance: As 5G networks are deployed worldwide, tentative steps toward the 6th generation of wireless technology are already underway. The FCC has opened terahertz wave spectrum (95GHz to 3THz) and 3GPP release dates for 6G standards are being set. Exponential speed and bandwidth increases will soon be coupled with nearly imperceptible latency. With range limitations inherent to higher frequencies and IoT use cases multiplying, the demand for MEC deployments will continue to rise.   
  • RAN Intelligent Controller (RIC): As a fundamental component of Open RAN architecture, the software-defined RIC performs essential, time-sensitive functions including load balancing, handover, and interference detection. The RIC automates RAN performance and improves interoperability and agility. The rapid decision-making required by the RIC will add more emphasis on enhanced MEC capabilities. MEC .
  • Beamforming: Along with massive steerable antenna arrays, beamforming technology narrowly focuses 5G signals toward specific user equipment (UE). 5G MEC supports complex beam handover and reconfiguration functions. With communication networks of the future expected to place any application with 1 hub of the user, intelligent software at the edge is essential for beam management. 

5G MEC Use Cases

Bringing the network closer to the user pushes performance to unprecedented levels. Although multi access edge computing enhances broadband delivery, interactive gaming, and Software-as-a-Service (SaaS) applications, the most remarkable edge computing use cases harness the power of 5G and the IoT to transform everyday experiences.

  • Coverage Optimization: The millimeter wave (mmWave) frequencies employed by 5G are limited to a few hundred meters in range and are subject to high path and penetration loss. Although steerable antennas and beamforming technology overcome these obstacles and improve coverage, transmission quality is still highly susceptible to environmental conditions and user mobility. 5G beam measurement and reporting techniques used to optimize handovers and coverage rely on the real-time intelligence delivered through 5G MEC.
  • Public Safety: Improved public safety practices are an undeniable byproduct of 5G and IoT adoption. Enhanced speed and bandwidth support rich media streaming and information access for first responders while reduced latency enables the use of autonomous vehicles in dangerous conditions. With IoT applications expanding to further the use of body-worn cameras and smart city sensors, 5G MEC plays a pivotal role in sustaining public safety evolution.
  • Advanced Driver-Assistance Systems (ADAS): Driverless cars, “vehicle to everything” communication, and breakthroughs in transportation safety, security, and infotainment rely on well-orchestrated network slices and artificial intelligence (AI) to decipher complex mobility scenarios. The autonomous edge supports low latency (1-2ms) ADAS requirements and seamless handovers as vehicle positions rapidly change.
  • Connected Health: A new and improved healthcare ecosystem where technology compliments personalized care will encompass virtual consultations, AV/AR-enabled medical training, and improved access to treatment and diagnostics in rural areas. Next generation connected health applications including remote surgical procedures and wearable IoT devices raise the bar by placing life-or-death importance on 5G edge artificial intelligence and ultra-low latency performance.

Advantages of Mobile Edge Computing

5G MEC safeguards the performance and latency of IoT use cases while providing a higher level of end-to-end visibility. Intelligence at the edge is leveraged to deploy the automation, infrastructure, and analytics that define 5G QoS and reliability.    

  • Automation and Zero-touch operation: 5G, network slicing, beamforming, and the IoT bring dramatic changes to wireless network management and orchestration. Fully automated, “zero-touch” networks capable of self-monitoring and self-healing reduce operational expenses and mean-time-to-repair (MTTR). The visibility needed to implement zero-touch 5G automation cannot be established without end-to-end intelligence deployed from RAN to Core.
  • Spectrum Management: Edge computing 5G intelligence allows the available spectrum to be utilized more efficiently. Dynamic spectrum allocation techniques use real-time feedback from UEs to instantaneously optimize transmission frequencies. Dynamic spectrum sharing (DSS) allows 5G and LTE signals to occupy the same frequency band, instantaneously dividing the available bandwidth based on the traffic demands.
  • Service Optimization: Data and analytics managed closer to the edge provide local visibility into user preferences and traffic patterns to endow differentiated levels of service. Bandwidth availability, power consumption, and application performance are continually optimized, and applications are deployed more efficiently.

Challenges of Mobile Edge Computing

As 5G rollout continues, the challenges and limitations of distributed edge computing continue to be revealed. Many of the breakthrough innovations enabling 5G technology can also be used to address these challenges proactively.

  • Power consumption is an ongoing concern with hardware deployed at thousands of individual tower sites and each 5G base station consuming over twice the energy of its 4G predecessor. Although dual power feeds to improve resiliency are often included in larger data centers, the size and location of 5G edge deployments make this less practical. Lights out (unmanned) edge locations with self-healing capabilities help to lessen 5G MEC energy utilization.  
  • Distribution of intelligence from Core to edge optimizes performance from the user perspective but also introduces a heightened level of system complexity that must be managed. Artificial intelligence and machine learning are among the evolving technologies used to detect and resolve 5G and edge computing issues in real time.
  • Densification is an inevitable result of 5G adoption. The impact of higher device and IoT sensor counts is magnified by the sheer volume of RAN hardware required for short-range mmWave transmission. Densification has driven intelligence and flexibility into distributed networks so that time division duplex (TDD) with efficient uplink and downlink transmission over the same frequency and dynamic network slicing processes can be optimized.

5G edge computing architecture combines elements of cloud computing and virtualized RAN to create a working foundation for 5G operation at the edge of the wireless network.

  • The 3GPP has recognized MEC as a central element of 5G architecture since its inception. Edge computing for 5G mobile networks is defined by 3GPP Technical Specification TS 23.501. Modular, service-based 5G architecture at the edge allows mobile operators to scale their offerings more efficiently.
  • The ETSI MEC guidelines describe MEC software architecture for either 4G or 5G networks and standard APIs. ETSI reference architecture includes a mobile edge host to supply storage, computing, and networking resources and a mobile edge platform for application assistance, authentication, and state change notifications.