Water injection algorithm

The iterative water injection algorithm is proposed by Wei Yu. It is a multi-user power allocation algorithm. This is a selfish algorithm. When the receiver and the sender do not share channel information, it is very simple to implement and has low complexity. However, when there is shared information on the channel and the channel needs to be shared, this will cause a near-far effect on the network topology. This creates an unbalanced state, causing signal interference between users and reducing the efficiency of information transmission.

Table Comparison of Multi-user OFDM Power Allocation Algorithm Tables

algorithm

Performance characteristics

Greedy algorithm

Using the multi-user water injection algorithm principle, the complexity is low, the implementation is simple, and the performance is poor

Transceivers do not need to share information when they are simple to implement. When they are needed, they can cause user interference and result in decreased channel throughput.

Ideal optimization algorithm

Excellent performance, computational complexity, difficulty in implementation

By optimizing the sum of formaldehyde rates, consider the interference between each user's transmit power to other users in the system, and reasonably allocate carrier resources and transmit power, so that the overall OFDM system has the best transmission performance.

The iterative water injection algorithm aims at maximizing user throughput. The iterative water injection algorithm formula list is as follows:

Then find the Lagrange function:

To:

At this point, we use the iterative algorithm to obtain a water injection level β, and then we can obtain the optimal power allocation. This algorithm is what we call the iterative water injection algorithm.

An important step in the iterative water injection algorithm is to determine the value of the water injection level β. So, how to quickly determine the value of the water level β, also to some extent determine the merits of the water injection algorithm. Here, we provide a beta value algorithm for your reference.

Where 0<β<1.

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