Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: What is the capacity of the uplink of a radio network of receivers?  consider a spread spectrum model in which each user is decoded by all the receivers in the network (macrodiversity).  use a carrier-to-interference performance criterion that  derive from Shannon theory; each user must find the right transmitter por level to satisfy its carrier-to interference constraint. Satisfying this requirement for all users is equivalent to solving a fixed point problem.  use this por control problem to derive the network capacity region and find that the feasibility of a configuration of users is independent of their positions in the network; each user can be assigned a bandwidth that is independent of the user's position in the network. Our capacity region is an upper bound over all schemes that treat the interference of other users as pure noise. To show that the capacity can be realized in practice,  propose a decentralized por adaptation algorithm and prove global convergence to the fixed point via a monotonicity argument.
['Stephen V. Hanly']
I am writing a research paper on a idea Capacity and power control in spread spectrum macrodiversity radio networks
[{"from": "human", "value": "I am writing a research paper on a idea Capacity and power control in spread spectrum macrodiversity radio networks"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: What is the capacity of the uplink of a radio network of receivers?  consider a spread spectrum model in which each user is decoded by all the receivers in the network (macrodiversity).  use a carrier-to-interference performance criterion that  derive from Shannon theory; each user must find the right transmitter por level to satisfy its carrier-to interference constraint. Satisfying this requirement for all users is equivalent to solving a fixed point problem.  use this por control problem to derive the network capacity region and find that the feasibility of a configuration of users is independent of their positions in the network; each user can be assigned a bandwidth that is independent of the user's position in the network. Our capacity region is an upper bound over all schemes that treat the interference of other users as pure noise. To show that the capacity can be realized in practice,  propose a decentralized por adaptation algorithm and prove global convergence to the fixed point via a monotonicity argument."}]