In view of the problem of computational redundancy due to the repeated computation of resource mapping positions in the traditional de-resource mapping method of Long Term Evolution-Advanced (LTE-A) physical layer, a new architecture of Physical Downlink Shared channel (PDSCH) de-resource mapping method was proposed, which provides support for the related physical layer processing of the LTE-A air interface analyzer. Firstly, before to the mapping of the physical downlink signal and the channel de-resource, the resource indexes of each signal and channel in single antenna port 0 mode, transmit diversity mode, single-stream beamforming, and dual-stream beamforming were generated; and then, the time-frequency location of the resource was directly located according to the resource index; finally, the PDSCH de-resource mapping module was put in the entire LTE-A link level simulation platform, and the simulations were given in four transmission modes, and the corresponding bit error rate and throughput comparison chart was obtained, which provides a theoretical reference to final hardware implementation. At the same time, compared with the de-resource mapping module under the traditional architecture, it shows that the de-resource mapping module under the new architecture costs 33.33% less time than the traditional computation mapping simulation, which reduces the de-resources and device resource consumption when de-resources mapping.

In order to improve the quality of speech signal and adaptability of cochlear implant under strong noise background, an improved method was proposed based on the combination of spectral subtraction and variable-step Least Mean Square error (LMS) adaptive filtering algorithm, and a speech enhancement hardware system for cochlear implant was constructed with this method. Concerning the problem of slow convergence rate and big steady-state error, the squared term of output error was used to adjust the step size of variable-step LMS adaptive filtering algorithm; besides, the combination of fixed and changed values of step was also considered, thus improved the adaptability and quality of speech signal. The speech enhancement hardware system for cochlear implant was composed of TMS320VC5416 and audio codec chip TLV320AIC23B, high-speed acquisition and real-time processing of voice data between TMS320VC5416 and TLV320AIC23B were realized by the interface of Muti-channel Buffered Serial Port (McBSP) and Serial Peripheral Interface (SPI).The Matlab simulation and test results prove that the proposed method has good performance in eliminating noise, the Signal-to-Noise Ratio (SNR) can be increased by about 10 dB in the case of low input SNR, and Perceptual Evaluation of Speech Quality (PESQ) score can be also greatly enhanced, the quality of the voice signal is improved effectively, and the system based on the proposed algorithm has stable performance which further improves the clarity and intelligibility of voice in cochlear implant.