Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: ,  focus on the use capillary M2M (Machine-to-Machine) networks for the estimation of spatial random fields. The observations (samples) collected by the sensors are spatially correlated and, for this reason,  propose a distributed pre-coding scheme based on the Karhunen-Loeve (KL) transform. This allows us to obtain an over-the-air compressed representation of such set of observations.  assume that sensors operate with (independent) duty-cycles and  derive a closed-form expression of the optimal por allocation strategy which minimizes the estimation error for a given por constraint. For benchmarking purposes,  also assess the performance of another scheme based on a particularization of the partial KL transform.
['Javier Matamoros', 'Carles Anton-Haro']
I am writing a research paper on a idea On the impact of duty cycle on the estimation of spatial fields with compressed observations in M2M capillary networks
[{"from": "human", "value": "I am writing a research paper on a idea On the impact of duty cycle on the estimation of spatial fields with compressed observations in M2M capillary networks"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: ,  focus on the use capillary M2M (Machine-to-Machine) networks for the estimation of spatial random fields. The observations (samples) collected by the sensors are spatially correlated and, for this reason,  propose a distributed pre-coding scheme based on the Karhunen-Loeve (KL) transform. This allows us to obtain an over-the-air compressed representation of such set of observations.  assume that sensors operate with (independent) duty-cycles and  derive a closed-form expression of the optimal por allocation strategy which minimizes the estimation error for a given por constraint. For benchmarking purposes,  also assess the performance of another scheme based on a particularization of the partial KL transform."}]