Abstract: In order to overcome the severe Inter-Symbol Interference (ISI) effect generated by digital baseband signals passing through UTP-CAT5, adaptive equalization technology is widely used to reduce the Inter-Symbol Interference, which greatly reduces the bit error rate of the received signal. The Least Mean Square (LMS) algorithm can effectively reduce Inter-Symbol Interference, but requires training sequences, which affects transmission efficiency. The Decision-Directed LMS (DDLMS) algorithm does not require training sequences, but when the eye diagram is not open, misjudgment may occur and even cause false convergence. The Constant Modulus Algorithm (CMA) has better blind equalization characteristics than the DDLMS algorithm, but the residual error is large. A novel joint blind equalization algorithm is proposed, which optimizes the existing CMA algorithm, and forms a new joint blind equalization algorithm with the DDLMS algorithm, and uses the Mean Square Error (MSE) to control the weights of the two algorithms. MATLAB modeling and simulation results show that the new joint blind equalization algorithm overcomes the shortcomings of the large residual error of the CMA algorithm and the false convergence of the DDLMS algorithm, and can effectively equalize the digital signals transmitted in the UTP-CAT5.

Key words: digital baseband signal, Inter-Symbol Interference (ISI), Least Mean Square (LMS) algorithm, decision-directed, Constant Modulus Algorithm (CMA), blind equalization