Relay system energy efficiency optimization method based on OFDM
An optimization method and relay system technology, applied in transmission systems, digital transmission systems, energy consumption reduction, etc., can solve problems such as low-complexity algorithms that do not fully consider the logarithm of system user energy efficiency and optimal real-time requirements
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Embodiment 1
[0094] An OFDM-based relay system energy efficiency optimization method, comprising
[0095] Step 1: build system model;
[0096] The present invention is aimed at a special application scene, comes from practical application, and the scene setting is meticulous and reasonable, and has practical guiding significance. like figure 1 As shown, the present invention considers a two-hop multi-relay multi-user OFDM cellular system. In this system, there is a base station located in the center of the circle, the cell radiation radius is R, K relay nodes are r (r0 . All relay nodes apply the half-duplex AF relay mode, and can obtain instantaneous channel information under different subcarriers. The communication process of the system is divided into two time slots. In the first time slot, all relay nodes receive the signal broadcast from the base station, and each pair of subcarriers can only be used by one relay; in the second time slot, All relay nodes amplify the received signa...
Embodiment 2
[0128] On the basis of the first embodiment, the Lagrangian multiplier algorithm is used, and in the process of each loop iteration, we can use the sub-gradient method, and select the gradual step, so that the optimization is more accurate. Specifically, the Lagrangian factor β in the Lagrangian form of the optimization problem P1 ρ,n ,β s ,β r,k The iterative update method of using the sub-gradient algorithm has lower complexity and more efficiency. The iterative update equation of the sub-gradient algorithm is:
[0129] β ρ , n ( τ + 1 ) = [ β ρ , n ( τ ) - δ ρ , n ...
Embodiment 3
[0136] On the basis of the first embodiment, the present invention adopts the method of dual decomposition to solve the optimization problem P1. Specifically, the solution of the optimization problem P1 in step 3 may include dual decomposition:
[0137] The classical problem of convex optimization problems with zero duality interval has been proved. That is to say, the solution of the dual problem is exactly the same as the original problem. The present invention will introduce the fractional programming Dinkelbach algorithm to transform the fractional problem into the integer problem. Therefore, construct the Lagrangian function of the objective function:
[0138] L ( p s , k n , p ...
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