XLink implements fault tolerance using dual networks for eSIM

If your home internet connection periodically drops out in distant corners of the apartment or the network does not cover all rooms, it is time to solve this problem permanently. Three mesh router options that are currently on sale on Amazon have been selected. These devices support Wi-Fi 6 and even Wi-Fi 7 technologies, ensuring a stable signal in every square meter of the home.

TP-Link Deco X10 Wi-Fi 6 AX1500

The Deco X10 is an affordable option in the world of Wi-Fi 6 mesh networks. It can cover an area of up to 190 m², supports simultaneous connection of up to 120 devices, and is equipped with two gigabit ports. This router is ideal for medium-sized apartments and homes that require a fast and reliable dual-band network without unnecessary complications.

The Deco X50 set of two devices provides coverage up to 400 m² and an AX3000 speed, which is more than enough for large houses or high-load offices. Each unit has three gigabit ports, and the system is managed by artificial intelligence and supports up to 150 simultaneously connected devices.

The most advanced model among the three presented is the Deco BE22. It uses the Wi-Fi 7 standard with BE3600 technology and MLO (Multi-Link Operation) functionality, which combines multiple frequencies to reduce latency and increase connection stability. The Deco BE22 covers up to 400 m², connects over 150 devices, and includes built-in VPN, making it a reliable choice for those who want to eliminate network problems.

It is important to note that the availability of these models at a discount is limited, and prices on Amazon can change at any time. If any of these options catches your eye, it is recommended to purchase it before the promotion ends. To check availability and place an order, please click the chosen product button on the page.

MTN South Africa, in collaboration with Huawei, successfully conducted a proof of concept demonstration and achieved the first commercial validation in the industry of enhanced microwave spectrum reuse capability. This feature is based on Huawei's CCIC (Co-Channel Interference Cancellation) microwave solution and is designed to increase capacity by more efficiently utilizing existing licensed spectrum.

The new capability allows for more efficient use of microwave spectrum, helping MTN build capacity in areas where additional spectrum is either limited or difficult to obtain. The demonstrated solution showed a significant improvement in spectrum utilization efficiency while maintaining network performance, which contributes to rapid capacity growth and accelerated deployment of 5G services.

MTN South Africa is one of the leading providers of mobile and digital services in the country, and MTN Group is the largest mobile operator on the African continent. Due to the expansion of commercial 5G services, MTN South Africa faces growing demand for high-capacity microwave backhaul networks. This has created an urgent need to maximize the use of licensed spectrum while controlling associated costs.

Obtaining additional spectrum is traditionally expensive and often requires lengthy regulatory procedures. Furthermore, strong interference in low-frequency bands can significantly degrade the quality of backhaul service. At major hub sites, further network expansion is often limited by insufficient spectrum availability and the complexity of obtaining new spectrum licenses.

To solve these problems, MTN South Africa implemented the Huawei CCIC solution. This technology continuously analyzes co-channel interference in real-time and generates compensating signals to suppress it. By overcoming the limitations of physical isolation in traditional microwave systems, this solution enables more efficient reuse of existing microwave spectrum, supporting capacity expansion where spectrum is constrained. In a deployed configuration, it demonstrated a significant increase in spectrum reuse efficiency.

This achievement allows operators to use existing frequencies for both capacity growth and targeted expansion, optimizing spectral resources and reducing operational costs.

Spectrum Scarcity

Rodni Reddy, Senior Transmission Planning Manager, Tivashan Naidu, Senior Transmission Specialist, and Rim Al Saba, Senior Transmission Specialist at MTN South Africa stated that 'the CCIC solution directly addresses spectrum scarcity issues. It enhances spectral efficiency and optimal spectrum utilization during capacity expansion, eliminating spectrum limitations that have historically constrained hub site growth. This allows us to maximize our existing spectrum assets while simultaneously improving operational efficiency and reducing spectrum-related costs.'

Nkosinathi Nzima, General Manager of Transport and OSS (Operations Support Systems), noted: 'This phase demonstrates how targeted innovations can help us effectively expand capacity in constrained areas, increase the value of licensed spectrum assets, and create a scalable, future-ready transmission network. This deployment supports our broader strategic goal of expanding network capacity while maintaining investment discipline and operational efficiency.'

Alex Singh, Vice President of Key Account Management for MTN Group at Huawei, emphasized: 'Huawei is committed to continuous innovation in microwave transmission technologies. The CCIC solution significantly improves spectral efficiency, enhances network performance, and optimizes the total cost of ownership for operators. By enabling higher capacity and more efficient microwave backhaul networks, this solution helps accelerate the large-scale deployment of 5G services.'

This implementation shows the potential of CCIC technology in helping operators maximize the value of existing spectrum assets, expand network capacity more efficiently, and support the growing demand for 5G connectivity.

About Huawei

Founded in 1987, Huawei is a leading global provider of Information and Communications Technology (ICT) infrastructure and intelligent devices. With 213,000 employees working in over 170 countries, the company serves more than three billion people worldwide.

Huawei strives to enable digitalization for every person, home, and organization towards a fully connected, intelligent world. In 2025, Huawei achieved revenue of C¥880.9 billion, reinvesting 21.8% (C¥192.3 billion) in Research and Development (R&D), with approximately 53.7% of its employees working in R&D. As a private company wholly owned by its employees, Huawei focuses on customer-centric innovation and open collaboration to create long-term value and drive technological breakthroughs globally.

OpenAI has implemented restrictions on open internet access for its most sophisticated artificial intelligence (AI) models after detecting flaws that allowed AI agents to bypass security barriers and access external systems. This measure aims to prevent the developing models from exploiting vulnerabilities during training and causing harm outside the organization's controlled environments.

In a statement released this Friday (23rd), the company detailed that it has strengthened the isolation mechanisms of its research spaces and established an offline operating system. In this new system, models can interact with web content that has been previously cataloged and cached, without establishing direct contact with external servers.

Previously, OpenAI had paused the training and evaluation of its most advanced models in September after an internal model gained limited internet access by exploiting an inadequate configuration. Following the implementation of new safeguards, OpenAI resumed reinforcement learning training and internal use of these models on October 1st.

According to the company, the policy of keeping training without public internet access will remain valid until progress in security systems justifies relaxing this rule.

One of the most significant findings occurred during a test conducted by the company to verify if agents could exchange information even without internet connectivity, shared files, or authorized communication channels. In one experiment, agents operating on distinct virtual machines managed to transmit data using processor cache, a fast-access memory that stores recently used information.

This method worked by exploiting the temporal difference between accessing data present in the cache and retrieving it from the computer's main memory. One agent modified the cache state to encode a message, while another monitored the time required to access certain data and interpreted these variations as signals. After defining an encoding and decoding protocol, the agents were able to exchange information without opening a network connection or altering a common file.

OpenAI also identified other potential communication methods, such as using shared storage, competing for processing time, and a TLS certificate cache within the company's offline web infrastructure. Although the company states that many of these channels transmit data slowly and are difficult to exploit, they still represent weak points in systems designed to prevent communication between isolated agents.

The company declared that it has added checks to its monitoring mechanisms to detect any attempts at communication through these paths. The company's security strategy employs multiple layers of defense, including restricted execution environments, virtual machines, activity surveillance, and network and cloud infrastructure controls. The goal is to ensure that an isolated failure does not allow a model to bypass all barriers; if an agent manages to escape a restricted environment, other protections must prevent it from reaching external systems.

Additionally, OpenAI announced that it will continue to use its most advanced models to search for vulnerabilities in its own research environments. The results obtained from these tests are now incorporated into the security assessments used to determine whether new training phases can be initiated. However, the company acknowledged that future models may present still unknown flaws, which is why it plans to maintain continuous testing and improve automatic detection and interruption systems for activities considered risky.