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A method of noise plus interference estimation for communication systems

IP.com Disclosure Number: IPCOM000241056D
Publication Date: 2015-Mar-23
Document File: 6 page(s) / 199K

Publishing Venue

The IP.com Prior Art Database

Abstract

Noise plus interference computation is key for any wireline/wireless communication system. With evolving standards such as LTE/LTE-A and others, there is a prominent need to correctly compute noise plus interference across multiple data and control channels. Noise plus interference is eventually used to compute Signal to Noise plus Interference Ratio (SINR), which is an essential part of any communication receiver. This paper describes an accurate and reliable method to compute noise plus interference under different multiplexing schemes such as Code Division Multiplexing (CDM), Frequency Division Multiplexing (FDM) and/or both CDM and FDM based users. A system level sensing is applied to obtain the details of resource allocation in time, frequency and code division that helps to identify used and unused allocations. This paper is not limited to estimate noise plus interference from unused time and/or frequency resources, but also considers scenarios where none of unused resources are available in time and frequency domain. The proposed method doesn’t put any constraint on higher layers for reserving any time and/or frequency resources and hence applicable for fully loaded system without compromising any system requirements such as capacity and throughput.

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A method of noise plus interference estimation for communication systems

1.  Abstract

Noise plus interference computation is key for any wireline/wireless communication system. With evolving standards such as LTE/LTE-A and others, there is a prominent need to correctly compute noise plus interference across multiple data and control channels. Noise plus interference is eventually used to compute Signal to Noise plus Interference Ratio (SINR), which is an essential part of any communication receiver. This paper describes an accurate and reliable method to compute noise plus interference under different multiplexing schemes such as Code Division Multiplexing (CDM), Frequency Division Multiplexing (FDM) and/or both CDM and FDM based users. A system level sensing is applied to obtain the details of resource allocation in time, frequency and code division that helps to identify used and unused allocations. This paper is not limited to estimate noise plus interference from unused time and/or frequency resources, but also considers scenarios where none of unused resources are available in time and frequency domain. The proposed method doesn’t put any constraint on higher layers for reserving any time and/or frequency resources and hence applicable for fully loaded system without compromising any system requirements such as capacity and throughput.

2. Overview of the proposed method

In communication system, it is required to estimate signal to noise plus interference ratio (SINR) mainly because of following reasons:

 Modulation and coding scheme selection for an optimum link performance

 Sound the channel and channel gain across the system bandwidth

 A reliable and optimum functionality of close loop power control 

 Efficient Interference management to enable cooperative networking

 Efficient and effective beam forming

At the receiver, there are multiple ways to estimate SINR and that varies based on the standards and their applications. For example, a single carrier based standard will estimate SINR differently compared to a multi-carrier system. Similarly, a code division multiplexed signal will experience a different SINR compared to an orthogonal-frequency-division multiplexed signal due to coding gain at receiver. Additionally, in a given standard, channels responsible to carry data, control, sounding-reference-signal and synchronization signals vary in the way signal is modulated. For an example, in LTE/LTE-A standard, a random-access channel is time domain multiplexed but in sounding reference signal it is multiplexed in both the domains i.e., time and frequency. For a solution provider, it is required to design and maintain SINR estimation schemes for each channel for an efficient functionality of the link. To address above issues, there are following challenges and requirements:

 an optimum scheme to meet the algorithmic performance and implementation complexity requirements

 there is a need of a scalable solution wh...