Cochlear implant (CI) patients have difficulty§understanding tonal languages which use pitch§variations to convey meaning because of poor pitch§perception. The ability of CI patients to communicate§in noisy environments is severely degraded.§Therefore, pitch-detection and (spatial) noise§suppression is of importance to current cochlear§implant devices. This thesis provides the details of§real-time implementations that address these§concerns. A pitch-detector was implemented to§estimate the pitch and a beamformer was implemented§to suppress spatial noise. The pitch-detection and§the beamforming algorithms were implemented on an ARM§based processor of a Personal Digital Assistant§(PDA). The pitch-detection algorithm is based on the§autocorrelation function. Its real-time performance§was measured and its efficiency in the presence of§speech-shaped noise and babble noise was evaluated.§The beamforming algorithm implemented was the§Griffith s beamformer. Objective and subjective tests§for different signal-to-noise ratio levels of§speech-shaped noise were conducted to evaluate its§performance. This thesis includes the results of§these evaluations.