Data transmission – MapYourTech

Hollow Core Fiber (HCF): A Game-Changer for Optical Communication

Technical 6 Mins Read

The world of optical communication is undergoing a transformation with the introduction of Hollow Core Fiber (HCF) technology. This revolutionary technology offers an alternative to traditional Single Mode Fiber (SMF) and presents exciting new possibilities for improving data transmission, reducing costs, and enhancing overall performance. In this article, we will explore the benefits, challenges, and applications of HCF, providing a clear and concise guide for optical fiber engineers.

What is Hollow Core Fiber (HCF)?

Hollow Core Fiber (HCF) is a type of optical fiber where the core, typically made of air or gas, allows light to pass through with minimal interference from the fiber material. This is different from Single Mode Fiber (SMF), where the core is made of solid silica, which can introduce problems like signal loss, dispersion, and nonlinearities.

In HCF, light travels through the hollow core rather than being confined within a solid medium. This design offers several key advantages that make it an exciting alternative for modern communication networks.

Traditional SMF vs. Hollow Core Fiber (HCF)

Single Mode Fiber (SMF) technology has dominated optical communication for decades. Its core is made of silica, which confines laser light, but this comes at a cost in terms of:

Attenuation: SMF exhibits more than 0.15 dB/km attenuation, necessitating Erbium-Doped Fiber Amplifiers (EDFA) or Raman amplifiers to extend transmission distances. However, these amplifiers add Amplified Spontaneous Emission (ASE) noise, degrading the Optical Signal-to-Noise Ratio (OSNR) and increasing both cost and power consumption.
Dispersion: SMF suffers from chromatic dispersion (CD), requiring expensive Dispersion Compensation Fibers (DCF) or power-hungry Digital Signal Processing (DSP) for compensation. This increases the size of the transceiver (XCVR) and overall system costs.
Nonlinearity: SMF’s inherent nonlinearities limit transmission power and distance, which affects overall capacity. Compensation for these nonlinearities, usually handled at the DSP level, increases the system’s complexity and power consumption.
Stimulated Raman Scattering (SRS): This restricts wideband transmission and requires compensation mechanisms at the amplifier level, further increasing cost and system complexity.

In contrast, Hollow Core Fiber (HCF) offers significant advantages:

Attenuation: Advanced HCF types, such as Nested Anti-Resonant Nodeless Fiber (NANF), achieve attenuation rates below 0.1 dB/km, especially in the O-band, matching the performance of the best SMF in the C-band.
Low Dispersion and Nonlinearity: HCF exhibits almost zero CD and nonlinearity, which eliminates the need for complex DSP systems and increases the system’s capacity for higher-order modulation schemes over long distances.
Latency: The hollow core reduces latency by approximately 33%, making it highly attractive for latency-sensitive applications like high-frequency trading and satellite communications.
Wideband Transmission: With minimal SRS, HCF allows ultra-wideband transmission across O, E, S, C, L, and U bands, making it ideal for next-generation optical systems.

Operational Challenges in Deploying HCF

Despite its impressive benefits, HCF also presents some challenges that engineers need to address when deploying this technology.

1. Splicing and Connector Challenges

Special care must be taken when connecting HCF cables. The hollow core can allow air to enter during splicing or through connectors, which increases signal loss and introduces nonlinear effects. Special connectors are required to prevent air ingress, and splicing between HCF and SMF needs careful alignment to avoid high losses. Fortunately, methods like thermally expanded core (TEC) technology have been developed to improve the efficiency of these connections.

2. Amplification Issues

Amplifying signals in HCF systems can be challenging due to air-glass reflections at the interfaces between different fiber types. Special isolators and mode field couplers are needed to ensure smooth amplification without signal loss.

3. Bend Sensitivity

HCF fibers are more sensitive to bending than traditional SMF. While this issue is being addressed with new designs, such as Photonic Crystal Fibers (PCF), engineers still need to handle HCF with care during installation.

4. Fault Management

HCF has a lower back reflection compared to SMF, which makes it harder to detect faults using traditional Optical Time Domain Reflectometry (OTDR). New low-cost OTDR systems are being developed to overcome this issue, offering better fault detection in HCF systems.

(a) Schematics of a 3×4-slot mating sleeve and two CTF connectors; (b) principle of lateral offset reduction by using a multi-slot mating sleeve; (c) Measured ILs (at 1550 nm) of a CTF/CTF interconnection versus the relative rotation angle; (d) Minimum ILs of 10 plugging trials.

Applications of Hollow Core Fiber

HCF is already being used in several high-demand applications, and its potential continues to grow.

1. Financial Trading Networks

HCF’s low-latency properties make it ideal for high-frequency trading (HFT) systems, where reducing transmission delay can provide a competitive edge. The London Stock Exchange has implemented HCF to speed up transactions, and this use case is expanding across financial hubs globally.

2. Data Centers

The increasing demand for fast, high-capacity data transfer in data centers makes HCF an attractive solution. Anti-resonant HCF designs are being tested for 800G applications, which significantly reduce the need for frequent signal amplification, lowering both cost and energy consumption.

3. Submarine Communication Systems

Submarine cables, which carry the majority of international internet traffic, benefit from HCF’s low attenuation and high power transmission capabilities. HCF can transmit kilowatt-level power over long distances, making it more efficient than traditional fiber in submarine communication networks.

4. 5G Networks and Remote Radio Access

As 5G networks expand, Remote Radio Units (RRUs) are increasingly connected to central offices through HCF. HCF’s ability to cover larger geographic areas with low latency helps 5G providers increase their coverage while reducing costs. This technology also allows networks to remain resilient, even during outages, by quickly switching between units.

Future Directions for HCF Technology

HCF is poised to shift the focus of optical transmission from the C-band to the O-band, thanks to its ability to maintain low chromatic dispersion and attenuation in this frequency range. This shift could reduce costs for long-distance communication by simplifying the required amplification and signal processing systems.

In addition, research into high-power transmission through HCF is opening up new opportunities for applications that require the delivery of kilowatts of power over several kilometers. This is especially important for data centers and other critical infrastructures that need reliable power transmission to operate smoothly during grid failures.

Hollow Core Fiber (HCF) represents a leap forward in optical communication technology. With its ability to reduce latency, minimize signal loss, and support high-capacity transmission over long distances, HCF is set to revolutionize industries from financial trading to data centers and submarine networks.

While challenges such as splicing, amplification, and bend sensitivity remain, the ongoing development of new tools and techniques is making HCF more accessible and affordable. For optical fiber engineers, understanding and mastering this technology will be key to designing the next generation of communication networks.

As HCF technology continues to advance, it offers exciting potential for building faster, more efficient, and more reliable optical networks that meet the growing demands of our connected world.

References/Credit :

Image https://www.holightoptic.com/what-is-hollow-core-fiber-hcf%EF%BC%9F/
https://www.mdpi.com/2076-3417/13/19/10699
https://opg.optica.org/oe/fulltext.cfm?uri=oe-30-9-15149&id=471571
https://www.ofsoptics.com/a-hollow-core-fiber-cable-for-low-latency-transmission-when-microseconds-count/

Basics of 5G Transport Network Architecture

Standards 3 Mins Read

The advent of 5G technology is set to revolutionise the way we connect, and at its core lies a sophisticated transport network architecture. This architecture is designed to support the varied requirements of 5G’s advanced services and applications.

As we migrate from the legacy 4G to the versatile 5G, the transport network must evolve to accommodate new deployment strategies influenced by the functional split options specified by 3GPP and the drift of the Next Generation Core (NGC) network towards cloud-edge deployment.

**Deployment location of core network in 5G network**

The Four Pillars of 5G Transport Network

1. Fronthaul: This segment of the network deals with the connection between the high PHY and low PHY layers. It requires a high bandwidth, about 25 Gbit/s for a single UNI interface, escalating to 75 or 150 Gbit/s for an NNI interface in pure 5G networks. In hybrid 4G and 5G networks, this bandwidth further increases. The fronthaul’s stringent latency requirements (<100 microseconds) necessitate point-to-point (P2P) deployment to ensure rapid and efficient data transfer.

2. Midhaul: Positioned between the Packet Data Convergence Protocol (PDCP) and Radio Link Control (RLC), the midhaul section plays a pivotal role in data aggregation. Its bandwidth demands are slightly less than that of the fronthaul, with UNI interfaces handling 10 or 25 Gbit/s and NNI interfaces scaling according to the DU’s aggregation capabilities. The midhaul network typically adopts tree or ring modes to efficiently connect multiple Distributed Units (DUs) to a centralized Control Unit (CU).

3. Backhaul: Above the Radio Resource Control (RRC), the backhaul shares similar bandwidth needs with the midhaul. It handles both horizontal traffic, coordinating services between base stations, and vertical traffic, funneling various services like Vehicle to Everything (V2X), enhanced Mobile BroadBand (eMBB), and Internet of Things (IoT) from base stations to the 5G core.

4. NGC Interconnection: This crucial juncture interconnects nodes post-deployment in the cloud edge, demanding bandwidths equal to or in excess of 100 Gbit/s. The architecture aims to minimize bandwidth wastage, which is often a consequence of multi-hop connections, by promoting single hop connections.

The Impact of Deployment Locations

The transport network’s deployment locations—fronthaul, midhaul, backhaul, and NGC interconnection—each serve unique functions tailored to the specific demands of 5G services. From ensuring ultra-low latency in fronthaul to managing service diversity in backhaul, and finally facilitating high-capacity connectivity in NGC interconnections, the transport network is the backbone that supports the high-speed, high-reliability promise of 5G.

As we move forward into the 5G era, understanding and optimizing these transport network segments will be crucial for service providers to deliver on the potential of this transformative technology.

Reference

https://www.itu.int/rec/T-REC-G.Sup67-201907-I/en

Noise Concatenation in Optical Amplifier Chains

Standards 4 Mins Read

Optical networks are the backbone of the internet, carrying vast amounts of data over great distances at the speed of light. However, maintaining signal quality over long fiber runs is a challenge due to a phenomenon known as noise concatenation. Let’s delve into how amplified spontaneous emission (ASE) noise affects Optical Signal-to-Noise Ratio (OSNR) and the performance of optical amplifier chains.

The Challenge of ASE Noise

ASE noise is an inherent byproduct of optical amplification, generated by the spontaneous emission of photons within an optical amplifier. As an optical signal traverses through a chain of amplifiers, ASE noise accumulates, degrading the OSNR with each subsequent amplifier in the chain. This degradation is a crucial consideration in designing long-haul optical transmission systems.

Understanding OSNR

OSNR measures the ratio of signal power to ASE noise power and is a critical parameter for assessing the performance of optical amplifiers. A high OSNR indicates a clean signal with low noise levels, which is vital for ensuring data integrity.

Reference System for OSNR Estimation

As depicted in Figure below), a typical multichannel N span system includes a booster amplifier, N−1 line amplifiers, and a preamplifier. To simplify the estimation of OSNR at the receiver’s input, we make a few assumptions:

Representation of optical line system interfaces (a multichannel N-span system)

All optical amplifiers, including the booster and preamplifier, have the same noise figure.
The losses of all spans are equal, and thus, the gain of the line amplifiers compensates exactly for the loss.
The output powers of the booster and line amplifiers are identical.

Estimating OSNR in a Cascaded System

E1: Master Equation For OSNR

P_out is the output power (per channel) of the booster and line amplifiers in dBm, L is the span loss in dB (which is assumed to be equal to the gain of the line amplifiers), G_BA is the gain of the optical booster amplifier in dB, NFis the signal-spontaneous noise figure of the optical amplifier in dB, h is Planck’s constant (in mJ·s to be consistent with P_out in dBm), ν is the optical frequency in Hz, ν_r is the reference bandwidth in Hz (corresponding to c/Br ), N–1 is the total number of line amplifiers.

The OSNR at the receivers can be approximated by considering the output power of the amplifiers, the span loss, the gain of the optical booster amplifier, and the noise figure of the amplifiers. Using constants such as Planck’s constant and the optical frequency, we can derive an equation that sums the ASE noise contributions from all N+1 amplifiers in the chain.

Simplifying the Equation

Under certain conditions, the OSNR equation can be simplified. If the booster amplifier’s gain is similar to that of the line amplifiers, or if the span loss greatly exceeds the booster gain, the equation can be modified to reflect these scenarios. These simplifications help network designers estimate OSNR without complex calculations.

1) If the gain of the booster amplifier is approximately the same as that of the line amplifiers, i.e., G_BA » L, above Equation E1 can be simplified to:

E1-1

2) The ASE noise from the booster amplifier can be ignored only if the span loss L (resp. the gain of the line amplifier) is much greater than the booster gain G_BA. In this case Equation E1-1 can be simplified to:

E1-2

3) Equation E1-1 is also valid in the case of a single span with only a booster amplifier, e.g., short‑haul multichannel IrDI in Figure 5-5 of [ITU-T G.959.1], in which case it can be modified to:

E1-3

4) In case of a single span with only a preamplifier, Equation E1 can be modified to:

Practical Implications for Network Design

Understanding the accumulation of ASE noise and its impact on OSNR is crucial for designing reliable optical networks. It informs decisions on amplifier placement, the necessity of signal regeneration, and the overall system architecture. For instance, in a system where the span loss is significantly high, the impact of the booster amplifier on ASE noise may be negligible, allowing for a different design approach.

Conclusion

Noise concatenation is a critical factor in the design and operation of optical networks. By accurately estimating and managing OSNR, network operators can ensure signal quality, minimize error rates, and extend the reach of their optical networks.

In a landscape where data demands are ever-increasing, mastering the intricacies of noise concatenation and OSNR is essential for anyone involved in the design and deployment of optical communication systems.

References

https://www.itu.int/rec/T-REC-G/e

BER and FEC in Optical Network Performance

Standards 3 Mins Read

Forward Error Correction (FEC) has become an indispensable tool in modern optical communication, enhancing signal integrity and extending transmission distances. ITU-T recommendations, such as G.693, G.959.1, and G.698.1, define application codes for optical interfaces that incorporate FEC as specified in ITU-T G.709. In this blog, we discuss the significance of Bit Error Ratio (BER) in FEC-enabled applications and how it influences optical transmitter and receiver performance.

The Basics of FEC in Optical Communications

FEC is a method of error control for data transmission, where the sender adds redundant data to its messages. This allows the receiver to detect and correct errors without the need for retransmission. In the context of optical networks, FEC is particularly valuable because it can significantly lower the BER after decoding, thus ensuring the accuracy and reliability of data across vast distances.

BER Requirements in FEC-Enabled Applications

For certain optical transport unit rates (OTUk), the system BER is mandated to meet specific standards only after FEC correction has been applied. The optical parameters, in these scenarios, are designed to achieve a BER no worse than 10⁻¹² at the FEC decoder’s output. This benchmark ensures that the data, once processed by the FEC decoder, maintains an extremely high level of accuracy, which is crucial for high-performance networks.

Practical Implications for Network Hardware

When it comes to testing and verifying the performance of optical hardware components intended for FEC-enabled applications, achieving a BER of 10⁻¹² at the decoder’s output is often sufficient. Attempting to test components at 10⁻¹² at the receiver output, prior to FEC decoding, can lead to unnecessarily stringent criteria that may not reflect the operational requirements of the application.

Adopting Appropriate BER Values for Testing

The selection of an appropriate BER for testing components depends on the specific application. Theoretical calculations suggest a BER of 1.8×10⁻⁴at the receiver output (Point A) to achieve a BER of 10⁻¹² at the FEC decoder output (Point B). However, due to variations in error statistics, the average BER at Point A may need to be lower than the theoretical value to ensure the desired BER at Point B. In practice, a BER range of 10⁻⁵ to 10⁻⁶ is considered suitable for most applications.

Conservative Estimation for Receiver Sensitivity

By using a BER of 10⁻⁶ for component verification, the measurements of receiver sensitivity and optical path penalty at Point A will be conservative estimates of the values after FEC correction. This approach provides a practical and cost-effective method for ensuring component performance aligns with the rigorous demands of FEC-enabled systems.

Conclusion

FEC is a powerful mechanism that significantly improves the error tolerance of optical communication systems. By understanding and implementing appropriate BER testing methodologies, network operators can ensure their components are up to the task, ultimately leading to more reliable and efficient networks.

As the demands for data grow, the reliance on sophisticated FEC techniques will only increase, cementing BER as a fundamental metric in the design and evaluation of optical communication systems.

References

https://www.itu.int/rec/T-REC-G/e

BER and Q Factor

Standards 3 Mins Read

Signal integrity is the cornerstone of effective fiber optic communication. In this sphere, two metrics stand paramount: Bit Error Ratio (BER) and Q factor. These indicators help engineers assess the performance of optical networks and ensure the fidelity of data transmission. But what do these terms mean, and how are they calculated?

What is BER?

BER represents the fraction of bits that have errors relative to the total number of bits sent in a transmission. It’s a direct indicator of the health of a communication link. The lower the BER, the more accurate and reliable the system.

ITU-T Standards Define BER Objectives

The ITU-T has set forth recommendations such as G.691, G.692, and G.959.1, which outline design objectives for optical systems, aiming for a BER no worse than 10⁻¹² at the end of a system’s life. This is a rigorous standard that guarantees high reliability, crucial for SDH and OTN applications.

Measuring BER

Measuring BER, especially as low as 10⁻¹², can be daunting due to the sheer volume of bits required to be tested. For instance, to confirm with 95% confidence that a system meets a BER of 10⁻¹², one would need to test 3×10¹² bits without encountering an error — a process that could take a prohibitively long time at lower transmission rates.

The Q Factor

The Q factor measures the signal-to-noise ratio at the decision point in a receiver’s circuitry. A higher Q factor translates to better signal quality. For a BER of 10⁻¹², a Q factor of approximately 7.03 is needed. The relationship between Q factor and BER, when the threshold is optimally set, is given by the following equations:

The general formula relating Q to BER is:

A common approximation for high Q values is:

For a more accurate calculation across the entire range of Q, the formula is:

Practical Example: Calculating BER from Q Factor

Let’s consider a practical example. If a system’s Q factor is measured at 7, what would be the approximate BER?

Using the approximation formula, we plug in the Q factor:

This would give us an approximate BER that’s indicative of a highly reliable system. For exact calculations, one would integrate the Gaussian error function as described in the more detailed equations.

Graphical Representation

The graph typically illustrates these relationships, providing a visual representation of how the BER changes as the Q factor increases. This allows engineers to quickly assess the signal quality without long, drawn-out error measurements.

Concluding Thoughts

Understanding and applying BER and Q factor calculations is crucial for designing and maintaining robust optical communication systems. These concepts are not just academic; they directly impact the efficiency and reliability of the networks that underpin our modern digital world.

References

https://www.itu.int/rec/T-REC-G/e

Spectral Grids and WDM Techniques for Fiber Optic Capacity

Technical 2 Mins Read

Introduction

The telecommunications industry constantly strives to maximize the use of fiber optic capacity. Despite the broad spectral width of the conventional C-band, which offers over 40 THz, the limited use of optical channels at 10 or 40 Gbit/s results in substantial under utilization. The solution lies in Wavelength Division Multiplexing (WDM), a technique that can significantly increase the capacity of optical fibers.

Understanding Spectral Grids

WDM employs multiple optical carriers, each on a different wavelength, to transmit data simultaneously over a single fiber. This method vastly improves the efficiency of data transmission, as outlined in ITU-T Recommendations that define the spectral grids for WDM applications.

The Evolution of Channel Spacing

Historically, WDM systems have evolved to support an array of channel spacings. Initially, a 100 GHz grid was established, which was then subdivided by factors of two to create a variety of frequency grids, including:

12.5 GHz spacing
25 GHz spacing
50 GHz spacing
100 GHz spacing

All four frequency grids incorporate 193.1 THz and are not limited by frequency boundaries. Additionally, wider spacing grids can be achieved by using multiples of 100 GHz, such as 200 GHz, 300 GHz, and so on.

ITU-T Recommendations for DWDM

ITU-T Recommendations such as ITU-T G.692 and G.698 series outline applications utilizing these DWDM frequency grids. The recent addition of a flexible DWDM grid, as per Recommendation ITU-T G.694.1, allows for variable bit rates and modulation formats, optimizing the allocation of frequency slots to match specific bandwidth requirements.

Flexible DWDM Grid in Practice

The flexible grid is particularly innovative, with nominal central frequencies at intervals of 6.25 GHz from 193.1 THz and slot widths based on 12.5 GHz increments. This flexibility ensures that the grid can adapt to a variety of transmission needs without overlap, as depicted in Figure above.

CWDM Wavelength Grid and Applications

Recommendation ITU-T G.694.2 defines the CWDM wavelength grid to support applications requiring simultaneous transmission of several wavelengths. The 20 nm channel spacing is a result of manufacturing tolerances, temperature variations, and the need for a guardband to use cost-effective filter technologies. These CWDM grids are further detailed in ITU-T G.695.

Conclusion

The strategic use of DWDM and CWDM grids, as defined by ITU-T Recommendations, is key to maximizing the capacity of fiber optic transmissions. With the introduction of flexible grids and ongoing advancements, we are witnessing a transformative period in fiber optic technology.

Anatomy of Outdoor and Indoor Optical Fiber Cables

Standards 3 Mins Read

The world of optical communication is intricate, with different cable types designed for specific environments and applications. Today, we’re diving into the structure of two common types of optical fiber cables, as depicted in Figure below, and summarising the findings from an appendix that examined their performance.

Figure

Cable A: The Stranded Loose Tube Outdoor Cable

Cable A represents a quintessential outdoor cable, built to withstand the elements and the rigors of outdoor installation. The cross-section of this cable reveals a complex structure designed for durability and performance:

Central Strength Member: At its core, the cable has a central strength member that provides mechanical stability and ensures the cable can endure the tensions of installation.
Tube Filling Gel: Surrounding the central strength member are buffer tubes secured with a tube filling gel, which protects the fibers from moisture and physical stress.
Loose Tubes: These tubes hold the optical fibers loosely, allowing for expansion and contraction due to temperature changes without stressing the fibers themselves.
Fibers: Each tube houses six fibers, comprising various types specified by the ITU-T, including G.652.D, G.654.E, G.655.D, G.657.A1, G.657.A2, and G.657.B3. This array of fibers ensures compatibility with different transmission standards and conditions.
Aluminium Tape and PE Sheath: The aluminum tape provides a barrier against electromagnetic interference, while the polyethylene (PE) sheath offers physical protection and resistance to environmental factors.

The stranded loose tube design is particularly suited for long-distance outdoor applications, providing a robust solution for optical networks that span vast geographical areas.

Cable B: The Tight Buffered Indoor Cable

Switching our focus to indoor applications, Cable B is engineered for the unique demands of indoor environments:

Tight Buffered Fibers: Unlike Cable A, this indoor cable features four tight buffered fibers, which are more protected from physical damage and easier to handle during installation.
Aramid Yarn: Known for its strength and resistance to heat, aramid yarn is used to reinforce the cable, providing additional protection and tensile strength.
PE Sheath: Similar to Cable A, a PE sheath encloses the structure, offering a layer of defense against indoor environmental factors.

Cable B contains two ITU-T G.652.D fibers and two ITU-T G.657.B3 fibers, allowing for a blend of standard single-mode performance with the high bend-resistance characteristic of G.657.B3 fibers, making it ideal for complex indoor routing.

Conclusion

The intricate designs of optical fiber cables are tailored to their application environments. Cable A is optimized for outdoor use with a structure that guards against environmental challenges and mechanical stresses, while Cable B is designed for indoor use, where flexibility and ease of handling are paramount. By understanding the components and capabilities of these cables, network designers and installers can make informed decisions to ensure reliable and efficient optical communication systems.

Reference

https://www.itu.int/rec/T-REC-G.Sup40-201810-I/en

HD-FEC & SD-FEC differences

Technical 1 Min Read

Items	HD-FEC	SD-FEC
Definition	Decoding based on hard-bits(the output is quantized only to two levels) is called the “HD(hard-decision) decoding”, where each bit is considered definitely one or zero.	Decoding based on soft-bits(the output is quantized to more than two levels) is called the “SD(soft-decision) decoding”, where not only one or zero decision but also confidence information for the decision are provided.
Application	Generally for non-coherent detection optical systems, e.g., 10 Gbit/s, 40 Gbit/s, also for some coherent detection optical systems with higher OSNR	coherent detection optical systems, e.g., 100 Gbit/s,400 Gbit/s.
Electronics Requirement	ADC(Analogue-to-Digital Converter) is not necessary in the receiver.	ADC is required in the receiver to provide soft information, e.g., coherent detection optical systems.
specification	general FEC per [ITU-T G.975];super FEC per [ITU-T G.975.1].	vendor specific
typical scheme	Concatenated RS/BCH	LDPC(Low density parity check),TPC(Turbo product code)
complexity	medium	high
redundancy ratio	generally 7%	around 20%
NCG	about 5.6 dB for general FEC;>8.0 dB for super FEC.	>10.0 dB
Example(If you asked your friend about traffic jam status on roads and he replies)	maybe fully jammed or free	50-50 but I found othe way free or less traffic