Parallel Blind Adaptive Equalization of Improved Block Constant Modulus Algorithm With Decision-Directed Mode

Abstract

To eliminate inter-symbol interferences (ISI) caused by nonlinear group delay effect in high-speed broadband satellite sensor networks, an efficient parallel adaptive blind equalization of improved block constant modulus algorithm (IBCMA) with decision-directed (DD) mode (IBCMA-DD) is proposed with block minimum mean square error (MMSE) criterion. First, nonlinear group delay models are introduced in satellite channels. Second, the criterion of the classical Godard’s constant modulus algorithm (CMA) is derived in the block vector form as the IBCMA for satellite signals with inter-symbol interference (ISI) caused by the above satellite channels. In the IBCMA, stochastic gradient descent and block minimum mean square error are adopted to reduce excess errors in equalization by adjusting block tap-weight vectors adaptively. Finally, the IBCMA is combined with the DD mode of equalization to both accelerate the parallel blind equalization with low complexity and improve the spectrum efficiency without any training data to occupy unnecessary bandwidth. Simulation results indicate that the proposed IBCMA-DD equalization possesses good performance in approaching ideal non-ISI transmissions. It achieves good bit error rate (BER) performance just within 0.3 dB of the theoretic performance under high signal-to-noise ratios (SNRs), even at satellite group delay channels by high-power nonlinear broadband filters. Therefore, it obtains excellent equalization under severely deteriorated group delay channels in broadband satellite sensor networks with high data rate.

Keywords

• Parallel equalization
• blind adaptive equalization
• improved block constant modulus algorithm
• block minimum mean square error
• intersymbol interference