{"schema_version":"1.0","canonical_url":"https://patentable.app/patents/US-9853667","patent":{"patent_number":"US-9853667","title":"Noise and interference estimation for colliding neighbor reference signals","assignee":null,"inventors":[],"filing_date":"2016-05-25T00:00:00.000Z","publication_date":"2017-12-26T00:00:00.000Z","cpc_codes":["H04B","H04B","H04B"],"num_claims":20,"abstract":"This disclosure relates to techniques for estimating noise and interference in a wireless communication system in which neighbor and serving cell reference signals are colliding. A wireless device and a base station may establish a wireless communication link such that the base station acts as a serving cell to the wireless device. It may be determined that one or more neighboring cells have colliding reference signals with the serving cell. Neighbor load conditions may be determined. A neighbor reference signal interference cancellation policy may be selected based at least in part on the determined neighbor load conditions and the one or more neighboring cells having colliding reference signals with the serving cell."},"analysis":{"summary":"The **Noise and Interference Estimation for Colliding Neighbor Reference Signals** patent (US-9853667) introduces a sophisticated method for improving wireless communication by intelligently managing signal interference. Its core innovation lies in its adaptive approach to identifying and mitigating noise when reference signals from neighboring cells collide with those of a user's serving cell.\n\nThe primary problem this patent solves is the degradation of wireless service quality and efficiency in dense network environments. In such scenarios, crucial reference signals—used by wireless devices for synchronization and channel estimation—can become corrupted by similar signals from adjacent base stations. This 'collision' leads to reduced data rates, increased latency, and a poor user experience, undermining the performance promise of advanced wireless networks like 5G.\n\nThe key technical approach involves a collaborative effort between a wireless device and its serving base station. First, the system determines if one or more neighboring cells have reference signals that are colliding with the serving cell's signals. Crucially, it then assesses the 'neighbor load conditions'—how busy or congested these interfering cells are. Based on this comprehensive understanding of both the collision presence and the neighbor's activity, the system dynamically selects and applies an optimal 'neighbor reference signal interference cancellation policy.' This intelligent adaptation ensures that the most effective strategy is used to clean up the signal.\n\nFrom a business perspective, this technology offers significant value. It enables network operators to achieve higher spectral efficiency and network capacity, especially in congested urban areas. This translates directly into improved quality of service (QoS) for subscribers, leading to greater customer satisfaction and reduced churn. The ability to provide more reliable and faster connections supports the rollout of bandwidth-intensive applications and services, driving revenue growth. For industries relying on stable, high-performance wireless connectivity, such as IoT, autonomous vehicles, and real-time enterprise applications, this patent provides a foundational technology.\n\nThe market opportunity for this invention is substantial, encompassing the entire wireless telecommunications industry. As 5G and future networks become increasingly dense and complex, the need for sophisticated interference management will only grow. This patent positions adopters to lead in network performance, offering a critical competitive advantage in a rapidly evolving global market. It's a strategic asset for any company aiming to optimize its wireless infrastructure and deliver a superior user experience.","layman_explanation":"## Decoding the Future of Wireless: Noise and Interference Estimation for Colliding Neighbor Reference Signals\n\nIn today's hyper-connected world, reliable and fast wireless communication isn't just a convenience; it's a fundamental business necessity. From enabling remote work to powering smart cities and industrial IoT, the backbone of our digital economy relies on seamless connectivity. However, as wireless networks become denser and more complex, a significant challenge emerges: signal interference. The **Noise and Interference Estimation for Colliding Neighbor Reference Signals** patent offers a sophisticated solution to this pervasive problem, promising to unlock new levels of performance and efficiency.\n\n### What Problem Does This Solve?\n\nImagine trying to hold a critical business call in a bustling convention center. Everyone around you is talking loudly, and several different conversations are bleeding into your ear. This is akin to what happens in a congested wireless environment. Your phone's main connection (the 'serving cell') needs to communicate clearly, but signals from other nearby cell towers (the 'neighboring cells') can often overlap and interfere with its crucial 'reference signals.' These reference signals are like the foundational instructions your phone needs to synchronize and understand the network. When they collide, it's like static on your call – data slows down, calls drop, and overall service quality plummets. Existing solutions often employ generic, static methods to filter this noise, which are simply not smart enough to handle the dynamic and complex nature of modern wireless interference. This leads to frustrated customers, inefficient network resource utilization, and ultimately, missed business opportunities.\n\n### How Does It Work?\n\nThis innovative patent introduces an intelligent, adaptive approach. Think of it as giving your wireless network a highly sophisticated 'ear' and a 'brain' to make real-time decisions. Here’s a conceptual breakdown:\n\n1.  **Smart Collision Detection:** The system first identifies precisely *when* and *where* signals from neighboring towers are interfering with your main connection's reference signals. It's not just a vague sense of 'noise'; it pinpointed the exact source of the disruption.\n2.  **Assessing Neighbor 'Busyness':** This is where the innovation truly shines. The system doesn't just know *that* a neighbor is interfering; it also determines *how busy* that interfering neighbor tower is. Is that neighboring tower handling a massive data surge, making its interference a significant and persistent problem? Or is it relatively quiet, meaning its interference is minor? This 'load condition' assessment is crucial.\n3.  **Dynamic Policy Selection:** Armed with both pieces of information – the fact of collision and the 'busyness' of the interferer – the system's 'brain' then selects the *most effective* strategy to cancel out the interference. Instead of a one-size-fits-all filter, it might choose an aggressive cancellation technique if the interfering neighbor is very busy, or a more subtle adjustment if the interference is light. This adaptive policy ensures that the network is always applying the optimal solution for the specific situation.\n\nIt's like having a personalized noise-canceling headset that not only identifies different types of noise but also understands the source's intensity, then applies the perfect filter to give you crystal-clear audio, adapting in real-time.\n\n### Why Does This Matter?\n\nFor businesses and consumers alike, the implications are substantial:\n\n*   **Enhanced User Experience:** For consumers, this means consistently faster data speeds, fewer dropped calls, and more reliable streaming, even in crowded environments. This directly translates to higher customer satisfaction and loyalty.\n*   **Increased Network Capacity & Efficiency:** For network operators, the ability to intelligently manage interference means more efficient use of precious spectrum. This boosts network capacity without necessarily requiring expensive new infrastructure, leading to significant cost savings and better return on investment (ROI) on existing assets.\n*   **Enabling Future Technologies:** Reliable, high-performance wireless connectivity is the bedrock for emerging technologies like autonomous vehicles, advanced IoT deployments, augmented reality, and real-time industrial applications. This patent helps ensure the underlying network infrastructure can support these demanding, high-value services.\n*   **Competitive Advantage:** Operators and equipment manufacturers that implement this technology can differentiate themselves by offering superior network quality, attracting and retaining lucrative business clients and high-value consumers. It's a strategic move in a fiercely competitive market.\n\n### What's Next?\n\nThis technology is poised to become a foundational component of advanced 5G and future 6G networks. Its principles could be extended to more complex scenarios, such as dynamic spectrum sharing and cognitive radio deployments, where networks autonomously adapt to their environment. As the demand for wireless connectivity continues to explode, innovations like Noise and Interference Estimation for Colliding Neighbor Reference Signals will be crucial for maintaining quality, driving efficiency, and unlocking the full potential of our digital future. Investing in or leveraging such intelligent interference management solutions will be key for any business aiming to stay ahead in the evolving wireless landscape.","technical_analysis":"The patent **Noise and Interference Estimation for Colliding Neighbor Reference Signals** (US-9853667) details a crucial advancement in wireless communication, specifically addressing the complex challenge of interference management in heterogeneous network environments. This technical analysis will dissect the underlying architecture, implementation specifics, and algorithmic considerations that define this innovation.\n\n**Technical Architecture and System Overview:**\nAt its core, this invention describes a distributed intelligence system involving a wireless device (User Equipment, UE) and a base station (e.g., gNB in 5G, eNB in LTE) acting as the serving cell. The architecture is designed to enable dynamic, context-aware interference mitigation. The primary components and their interactions are:\n1.  **Wireless Device (UE):** Responsible for receiving reference signals from both the serving cell and neighboring cells, performing initial signal processing, and potentially assisting in the determination of collision events and neighbor load. The UE's physical layer (PHY) capabilities for channel estimation and interference measurement are critical here.\n2.  **Base Station (Serving Cell):** Orchestrates the overall interference management process. It communicates with the UE, potentially exchanges information with neighboring base stations (via inter-base station interfaces like X2/Xn), processes data, and ultimately selects and signals the interference cancellation policy to the UE.\n3.  **Neighboring Cells:** These are other base stations whose reference signals may collide with the serving cell's signals. Their load conditions are a key input to the system.\n\n**Implementation Details and Algorithm Specifics:**\n1.  **Collision Detection:** The patent implies a mechanism for determining that 'one or more neighboring cells have colliding reference signals with the serving cell.' This can be implemented through several technical approaches:\n    *   **Resource Element (RE) Overlap:** Reference signals (e.g., Cell-specific Reference Signals (CRS) in LTE, Demodulation Reference Signals (DMRS) in 5G NR) are transmitted on specific time-frequency REs. The serving cell and UE can identify if the REs used by known or detected neighbor cells overlap with the serving cell's RS REs. This requires knowledge of neighbor cell IDs, their cyclic prefixes, and timing offsets.\n    *   **Signal Strength Analysis:** If a UE detects strong signals from a neighbor cell on REs designated for the serving cell's RS, it indicates a collision. Advanced receivers can attempt to decode or estimate the interfering signal's characteristics.\n    *   **Inter-Base Station Coordination:** The serving base station might receive information from neighboring base stations (e.g., via X2/Xn interfaces) about their RS configurations and power levels, allowing it to predict potential collisions.\n\n2.  **Neighbor Load Conditions Determination:** This is a crucial differentiator from simpler interference management. Knowing the neighbor's load allows for a more intelligent decision on mitigation. Methods include:\n    *   **X2/Xn Interface Signaling:** The most direct method is for neighboring base stations to report their current load (e.g., Physical Resource Block (PRB) utilization, active user count, buffer status) to the serving base station. This real-time information is essential.\n    *   **UE Measurement Reports:** UEs can be configured to report measurements of neighboring cells, including Reference Signal Received Power (RSRP), Reference Signal Received Quality (RSRQ), and Signal-to-Interference-plus-Noise Ratio (SINR). Statistical analysis of these reports over time can infer load, especially if combined with knowledge of neighbor transmit power.\n    *   **Machine Learning/Pattern Recognition:** Over time, the network could learn correlations between observed interference patterns (from UE measurements) and actual neighbor load (from signaling), enabling predictive load estimation.\n\n3.  **Neighbor Reference Signal Interference Cancellation Policy Selection:** This is the adaptive decision-making stage. Based on the collision detection and neighbor load determination, the serving base station selects an optimal policy. This policy could involve:\n    *   **Successive Interference Cancellation (SIC):** If a strong interfering neighbor RS is detected from a highly loaded cell, the UE might be instructed to first decode and cancel that strong interference before attempting to decode its serving cell's RS. The order of cancellation can be dynamically adjusted based on estimated signal strengths and loads.\n    *   **Advanced Receiver Algorithms:** The UE's receiver might employ more sophisticated algorithms like Minimum Mean Square Error (MMSE) interference rejection combining, with parameters dynamically adjusted based on the estimated interference characteristics and load.\n    *   **Resource Management:** The serving cell might instruct the UE to ignore certain heavily interfered REs or adjust its Modulation and Coding Scheme (MCS) to be more robust to residual interference.\n    *   **Coordinated Multipoint (CoMP) Enhancements:** While not explicitly stated, the principles could inform CoMP operations, where multiple cells coordinate to manage interference or even cooperatively transmit/receive.\n\n**Integration Patterns:**\nThis technology would primarily integrate into the PHY and MAC layers of the wireless protocol stack. It requires tight coordination between the UE's receiver capabilities and the base station's scheduler and resource management functions. Data exchange between base stations (X2/Xn) is also a critical integration point for real-time neighbor load information. Software Defined Networking (SDN) and Network Function Virtualization (NFV) architectures could facilitate more flexible and dynamic deployment of these intelligent interference management functionalities.\n\n**Performance Characteristics:**\nSuccessful implementation of this patent would yield several performance benefits:\n*   **Improved SINR:** More accurate estimation and cancellation of interference directly leads to higher SINR at the UE receiver.\n*   **Increased Throughput:** Better SINR enables higher order modulation and coding, translating to higher data rates.\n*   **Reduced Latency:** More reliable channel estimation and fewer retransmissions contribute to lower latency.\n*   **Enhanced Spectral Efficiency:** The network can utilize its spectrum more effectively, especially in high-density deployments.\n*   **Better Handover Performance:** More accurate channel conditions lead to smoother and more robust handovers.\n*   **Optimized Resource Utilization:** By adapting cancellation policies, computational resources are used more efficiently, avoiding unnecessary processing when interference is low.\n\nIn essence, this patent provides a robust framework for cognitive interference management, moving beyond static solutions to an adaptive, context-aware system that is vital for the performance and scalability of future wireless networks.","business_analysis":"The **Noise and Interference Estimation for Colliding Neighbor Reference Signals** patent (US-9853667) represents a significant business opportunity and a strategic imperative for players across the wireless telecommunications ecosystem. Its core value proposition lies in its ability to enhance network performance and spectral efficiency, directly addressing critical pain points for operators and unlocking new revenue streams.\n\n**Market Opportunity Size:**\nThe global wireless infrastructure market is valued in the hundreds of billions of dollars, with significant ongoing investment in 5G rollouts and future network generations. Interference management is a universal and persistent challenge in all wireless networks, especially as cell density increases. This patent targets a fundamental aspect of network optimization, making its addressable market vast. Every operator deploying 5G, particularly in dense urban areas, stadiums, or enterprise campuses, will benefit from improved interference mitigation. The market for advanced network optimization software and intellectual property related to 5G performance is growing rapidly, positioning this invention at the heart of that expansion.\n\n**Competitive Advantages:**\nCompanies that license or implement this technology can gain substantial competitive advantages:\n1.  **Superior Network Performance:** Offering demonstrably faster and more reliable connections, especially in congested areas, directly translates to higher customer satisfaction, reduced churn, and the ability to attract new subscribers.\n2.  **Enhanced Spectral Efficiency:** Spectrum is a finite and incredibly expensive resource. By intelligently mitigating interference, this technology allows operators to extract more capacity and throughput from their existing spectrum allocations, deferring costly spectrum acquisition or infrastructure upgrades.\n3.  **Reduced Operational Costs:** Fewer dropped calls, better data speeds, and more stable connections lead to fewer customer support tickets related to network quality, lowering operational expenditures.\n4.  **Future-Proofing Infrastructure:** As networks evolve towards 6G and beyond, with even denser deployments and new frequency bands (e.g., millimeter-wave), adaptive interference management will be non-negotiable. Adopting this technology now positions companies ahead of the curve.\n5.  **Enabling New Services:** Reliable, high-performance wireless is crucial for emerging high-value applications like industrial IoT, autonomous vehicles, augmented/virtual reality, and smart cities. This patent helps ensure the underlying network can support these demanding services, opening up new B2B revenue opportunities.\n\n**Revenue Potential and Business Models:**\nFor the patent holder, revenue potential could come from licensing to major network equipment vendors (e.g., Ericsson, Nokia, Huawei, Samsung) and directly to mobile network operators (MNOs). Potential business models include:\n*   **Per-device or Per-base station licensing:** A fee for each piece of equipment incorporating the technology.\n*   **Subscription-based software licensing:** For network optimization software that includes this capability.\n*   **Royalty agreements:** Based on the revenue generated by improved network performance or associated services.\n*   **Strategic partnerships:** Collaborating with industry leaders to integrate this into their next-generation products.\n\nFor MNOs, the revenue impact is indirect but significant: increased average revenue per user (ARPU) through premium service tiers, reduced churn, and the ability to charge for enhanced enterprise solutions.\n\n**Strategic Positioning:**\nThis patent strategically positions its owner as a leader in advanced wireless interference management and a key enabler for high-performance 5G and future networks. It moves beyond generic interference cancellation to a nuanced, intelligent approach that considers real-time network conditions. This expertise is highly valued in an industry where network quality is a primary differentiator.\n\n**ROI Projections:**\nWhile specific ROI will vary, the benefits are clear. For MNOs, even a modest improvement in spectral efficiency (e.g., 5-10%) across their network can translate into billions of dollars in saved capital expenditure (by delaying the need for new cell sites or spectrum) and increased operational revenue (from higher throughput and customer satisfaction). Reduced churn rates, even by a small percentage, have a substantial impact on long-term customer value. For equipment vendors, incorporating this patented technology into their products provides a competitive edge, allowing them to capture larger market shares and offer more compelling solutions to operators.\n\nIn conclusion, the **Noise and Interference Estimation for Colliding Neighbor Reference Signals** patent addresses a critical and growing technical challenge with a solution that delivers clear, quantifiable business benefits. It is a strategic asset that promises substantial returns for innovators and early adopters, solidifying their position in the vanguard of wireless technology.","faqs":[{"answer":"The **Noise and Interference Estimation for Colliding Neighbor Reference Signals** patent (US-9853667) describes an advanced technique designed to significantly improve wireless communication performance. It focuses on intelligently identifying and mitigating unwanted 'noise' or 'interference' that occurs when signals from different cell towers overlap, specifically targeting crucial 'reference signals'. These reference signals are essential for a wireless device (like your smartphone) to establish and maintain a stable, high-quality connection with its serving cell tower. Without clear reference signals, your device struggles to understand the network, leading to poor performance.\n\nThis invention introduces a dynamic approach, moving beyond static solutions that treat all interference generically. Instead, it enables the wireless system to adapt its interference cancellation strategy based on real-time conditions. This makes it a crucial development for modern wireless networks, especially 5G and beyond, where signal congestion is a growing challenge.\n\nThe core idea is to make the network smarter and more responsive to its environment, ensuring that your device always receives the clearest possible signal. This leads directly to faster speeds, more reliable connections, and an overall better user experience in various wireless environments.","question":"What is Noise and Interference Estimation for Colliding Neighbor Reference Signals?"},{"answer":"The **Noise and Interference Estimation for Colliding Neighbor Reference Signals** patent works through a sophisticated, multi-step process involving collaboration between your wireless device and its serving base station. First, the system identifies instances where reference signals from neighboring cells are directly overlapping and interfering with the reference signals from your serving cell. This detection is crucial for pinpointing the exact source of disruption.\n\nNext, and critically, the system determines the 'load conditions' of those identified interfering neighboring cells. This means it assesses how busy or congested those adjacent towers are. For example, is a neighboring tower currently handling a large volume of data traffic, indicating a strong and persistent source of interference? Or is it relatively quiet, meaning its interference is minor or sporadic? This contextual information is a key differentiator of this technology.\n\nFinally, based on both the precise detection of colliding signals and the real-time understanding of the neighbor's load, the system dynamically selects and applies an optimal 'neighbor reference signal interference cancellation policy.' This adaptive policy ensures that the most effective and efficient strategy is used to mitigate the interference, rather than a generic, one-size-fits-all approach. By tailoring the cancellation method to the specific interference scenario, this innovation significantly enhances signal quality and network efficiency.","question":"How does Noise and Interference Estimation for Colliding Neighbor Reference Signals work?"},{"answer":"The **Noise and Interference Estimation for Colliding Neighbor Reference Signals** patent primarily solves the problem of degraded wireless communication performance caused by signal interference in dense network environments. In today's crowded wireless landscapes, especially in urban areas or at large events, signals from multiple cell towers can overlap. When the vital 'reference signals' (which devices use for synchronization and channel estimation) from a user's serving cell collide with similar signals from neighboring cells, they become corrupted.\n\nThis corruption leads to several significant issues: reduced data speeds, increased latency, dropped calls, and generally unstable connections. Existing interference management techniques often fall short because they are either static (not adapting to changing conditions) or too generic, failing to intelligently differentiate between various types and sources of interference. This results in inefficient use of spectrum and a poor user experience, hindering the full potential of advanced wireless networks like 5G.\n\nBy providing a smart, adaptive mechanism to identify and mitigate this specific type of interference, this technology ensures clearer signals, more efficient spectrum utilization, and ultimately, a much more reliable and high-performing wireless experience for everyone.","question":"What problem does Noise and Interference Estimation for Colliding Neighbor Reference Signals solve?"},{"answer":"The patent **Noise and Interference Estimation for Colliding Neighbor Reference Signals** (US-9853667) was filed by an assignee, and the inventors are associated with this entity. While the specific inventors' names and assignee details are not provided in the abstract, the innovation represents a collective effort within the telecommunications research and development community to address fundamental challenges in wireless network performance. Patents are often the result of extensive research and engineering work conducted by teams within leading technology companies or research institutions.\n\nThis particular patent contributes to the broader field of wireless communication, focusing on advanced interference management techniques crucial for the evolution of cellular networks. The development of such sophisticated algorithms and systems requires deep expertise in signal processing, network architecture, and radio resource management. The invention reflects the ongoing commitment of innovators to push the boundaries of what's possible in wireless connectivity, ensuring that future networks can meet ever-increasing demands for speed, reliability, and capacity. For full details on the inventors and assignee, one would typically consult the full patent document available through official patent databases.","question":"Who invented Noise and Interference Estimation for Colliding Neighbor Reference Signals?"},{"answer":"The **Noise and Interference Estimation for Colliding Neighbor Reference Signals** patent delivers a range of significant benefits for both wireless network operators and end-users.\n\nFor **users**, the primary benefits include: 1) **Faster and More Reliable Connections:** By effectively clearing up signal interference, users experience consistently higher data speeds, reduced latency, and fewer dropped calls, especially in congested areas. 2) **Improved User Experience:** The overall quality of service (QoS) is enhanced, leading to smoother streaming, more responsive online gaming, and better performance for real-time applications. 3) **Extended Battery Life:** More efficient signal processing can lead to less power consumption for devices trying to decode corrupted signals.\n\nFor **network operators**, the key advantages are: 1) **Increased Spectral Efficiency:** The ability to extract more capacity and throughput from existing spectrum assets, deferring costly new spectrum acquisitions or infrastructure upgrades. 2) **Enhanced Network Capacity:** Supports higher user density and traffic volumes without compromising performance. 3) **Reduced Operational Costs:** Fewer customer complaints related to network quality translate into lower customer support expenses and network troubleshooting efforts. 4) **Future-Proofing Infrastructure:** The adaptive and intelligent nature of this technology positions networks to better handle the complexities of 5G, 6G, and beyond, supporting emerging high-value applications like autonomous vehicles and industrial IoT. These benefits collectively drive greater customer satisfaction, operational efficiency, and competitive advantage in the telecommunications market.","question":"What are the key benefits of Noise and Interference Estimation for Colliding Neighbor Reference Signals?"},{"answer":"The **Noise and Interference Estimation for Colliding Neighbor Reference Signals** patent distinguishes itself from prior art by offering a significantly more intelligent and adaptive approach to interference management. Traditional interference mitigation techniques, such as static frequency planning, basic power control, or general interference averaging, often rely on fixed rules or reactive measures that struggle with the dynamic nature of modern wireless networks. They typically treat all interference generically, without detailed understanding of its source or characteristics.\n\nThis invention, however, introduces two crucial advancements: 1) It not only detects *that* crucial reference signals are colliding but also precisely identifies the *source* of that collision. 2) More importantly, it determines the 'load conditions' (i.e., how busy) of the interfering neighboring cells. This context-aware understanding allows the system to differentiate between a minor, sporadic interference source and a major, persistent one. Based on this granular insight, it then dynamically selects the *most optimal* interference cancellation policy, rather than applying a generic fix. This shift from a one-size-fits-all, reactive approach to a context-aware, proactive, and adaptive strategy is what sets **Noise and Interference Estimation for Colliding Neighbor Reference Signals** apart, leading to far more efficient and effective interference resolution in complex wireless environments.","question":"How is Noise and Interference Estimation for Colliding Neighbor Reference Signals different from prior art?"},{"answer":"The **Noise and Interference Estimation for Colliding Neighbor Reference Signals** patent has the potential to significantly impact a wide array of industries that rely heavily on robust and high-performance wireless connectivity. Primarily, the **Telecommunications Industry** itself will see a transformative effect, as mobile network operators and equipment vendors can deliver superior 5G and future network services, optimize infrastructure, and reduce operational costs. This innovation is crucial for MNOs to meet the increasing demand for data and support new revenue streams.\n\nBeyond telecom, industries such as **Automotive** (especially for autonomous vehicles requiring ultra-reliable, low-latency communication), **Manufacturing** (for industrial IoT and private 5G networks enabling smart factories and automation), and **Logistics** (for real-time tracking, fleet management, and smart warehousing) will benefit from the enhanced network reliability. The **Healthcare Sector** could leverage more stable connections for telemedicine and remote patient monitoring, while **Smart City Initiatives** will see improved performance for connected sensors, traffic management, and public safety systems. Finally, the **Entertainment and Gaming Industry** will benefit from the lower latency and higher bandwidth, enabling more immersive cloud gaming and AR/VR experiences. Essentially, any sector where consistent, high-quality wireless connectivity is critical for operations, innovation, or user experience stands to gain from this technology.","question":"What industries will Noise and Interference Estimation for Colliding Neighbor Reference Signals impact?"},{"answer":"The patent for **Noise and Interference Estimation for Colliding Neighbor Reference Signals**, identified as US-9853667, was **filed on May 25, 2016**. It was subsequently **published and granted on December 26, 2017**. These dates mark key milestones in the intellectual property lifecycle of this innovative wireless technology.\n\nThe filing date signifies when the patent application was initially submitted to the patent office, establishing the priority date for the invention. The publication date, typically occurring a certain period after filing, makes the details of the invention publicly accessible, allowing others in the field to review and understand the proposed solution. The grant date indicates that the patent office has examined the application and determined that the invention meets the criteria for patentability, officially awarding the patent to the applicant. This grants the patent holder exclusive rights to the invention for a specified period.\n\nThe timeline reflects the process of bringing a novel solution from conception and development through the formal legal protection required to commercialize and leverage such a significant advancement in wireless interference management.","question":"When was Noise and Interference Estimation for Colliding Neighbor Reference Signals filed/granted?"},{"answer":"The **Noise and Interference Estimation for Colliding Neighbor Reference Signals** patent has broad commercial applications, primarily centered around enhancing the performance and efficiency of wireless networks. For **Mobile Network Operators (MNOs)**, it means they can offer superior 5G services with consistently higher speeds and lower latency, even in densely populated areas. This directly translates to increased customer satisfaction, reduced churn, and the ability to attract new, high-value subscribers. Operators can also optimize their capital expenditure by maximizing the capacity of existing infrastructure rather than constantly needing to build more cell sites or acquire additional spectrum.\n\n**Network Equipment Vendors** (e.g., manufacturers of base stations, small cells, and user equipment chipsets) can integrate this patented technology into their products, providing a significant competitive advantage. Their offerings will deliver better performance, making them more attractive to MNOs globally. This innovation supports the development of more robust **Private 5G Networks** for enterprises, enabling critical applications in manufacturing, logistics, and smart campuses where reliable, interference-free communication is paramount.\n\nFurthermore, the technology underpins the reliable deployment of **Emerging Technologies** such as autonomous vehicles, advanced IoT solutions, and augmented/virtual reality applications, all of which require unwavering high-quality wireless connectivity. By solving a fundamental interference problem, this patent enables the commercial viability and widespread adoption of these next-generation services, opening up new revenue streams and market opportunities across various industries.","question":"What are the commercial applications of Noise and Interference Estimation for Colliding Neighbor Reference Signals?"},{"answer":"Future developments for the principles outlined in the **Noise and Interference Estimation for Colliding Neighbor Reference Signals** patent are expected to drive the evolution of wireless networks towards even greater intelligence and autonomy. One major area of development is the deeper integration with **Artificial Intelligence and Machine Learning (AI/ML)**. This would involve training AI models to autonomously learn optimal interference cancellation policies based on vast amounts of real-time network data, environmental conditions, and user behavior, moving beyond pre-programmed rules.\n\nAnother key development lies in its role within **Self-Organizing Networks (SON)**. The adaptive interference management capabilities could become a core component of SON functionalities, allowing networks to self-configure, self-optimize, and self-heal in dynamic environments without human intervention. This would lead to significant operational efficiencies and improved network resilience.\n\nFurthermore, as networks evolve towards **6G and beyond**, integrating sensing capabilities with communication (known as Integrated Sensing and Communication, or ISAC) will become crucial. The precise interference estimation techniques from this patent could be leveraged to build real-time, highly accurate maps of the radio environment, informing both communication and sensing functions. This will enable more flexible and efficient **Dynamic Spectrum Sharing (DSS)**, allowing various services and users to coexist harmoniously on the same spectrum. Ultimately, the trajectory is towards fully cognitive wireless networks that can autonomously adapt to any challenge, ensuring ubiquitous, high-performance connectivity for an increasingly complex digital world.","question":"What are the future developments expected for Noise and Interference Estimation for Colliding Neighbor Reference Signals?"}],"topics":["Noise and Interference Estimation for Colliding Neighbor Reference Signals","wireless interference management","5G network optimization","reference signal collision","signal cancellation policy","technical","adaptive","mechanisms"],"tech_cluster":null},"seo":{"title":"Noise and Interference Estimation for Colliding Neighbor Reference Signals - US-9853667","description":"Discover the Noise and Interference Estimation for Colliding Neighbor Reference Signals patent. Learn how it intelligently manages wireless interference for faster, more reliable 5G.","keywords":["Noise and Interference Estimation for Colliding Neighbor Reference Signals","wireless interference management","5G network optimization","reference signal collision","signal cancellation policy","telecom innovation","spectral efficiency","patent US-9853667","wireless communication","neighbor load conditions","interference estimation","network performance","cellular technology","patent analysis"]},"attribution":{"source":"Patentable","source_url":"https://patentable.app","canonical_url":"https://patentable.app/patents/US-9853667","license":"CC-BY-4.0-like","license_terms":"AI-generated analysis on this page (summary, layman_explanation, technical_analysis, business_analysis, faqs) may be reused with attribution and a visible link back to the canonical URL above. Patent abstracts, claims, and bibliographic data are USPTO public domain.","required_link":"https://patentable.app/patents/US-9853667","citation_suggestion":"Patentable. \"Noise and interference estimation for colliding neighbor reference signals\" (US-9853667). https://patentable.app/patents/US-9853667","copyright_holder":"Nomic Interactive Technology LLC"},"links":{"html":"https://patentable.app/patents/US-9853667","json":"https://patentable.app/api/llm-context/US-9853667","site":"https://patentable.app","llms_txt":"https://patentable.app/llms.txt"},"generated_at":"2026-06-06T18:29:14.711Z"}