Low-latency and High-Reliability FBMC Modulation scheme using Optimized Filter design for enabling NextG Real-time Smart Healthcare Applications.

This paper presents a prototype filter design using the orthant optimization technique to assist a filter bank multicarrier (FBMC) modulation scheme of a NextG smart e-healthcare network framework. Low latency and very high reliability are one of the main requirements of a real-time e-healthcare system. In recent times, FBMC modulation has gotten more attention due to its spectral efficiency. The characteristics of a filter bank are determined by t's, prototype filter. A prototype filter cannot be designed to achieve an arbitrary time localization (for low latency) and frequency localization (spectral efficiency), as time and frequency spreading are conflicting goals. Hence, an optimum design needed to be achieved. In this paper, a constraint for perfect or nearly perfect reconstruction is formulated for prototype filter design and an orthant-based enriched sparse ℓ1-optimization method is applied to achieve the optimum performance in terms of higher availability of subcarrier spacing for the given requirement of signal-to-interference ratio. Larger subcarrier spacing ensures lower latency and better performance in real-time applications. The proposed FBMC system, based on an optimum design of the prototype filter, also supports a higher data rate as compared to traditional FBMC and OFDM systems, which is another requirement of real-time communication. In this paper, the solution for the different technical issues of physical layer design is provided. The presented modulation scheme through the proposed prototype filter-based FBMC can suppress the side lobe energy of the constituted filters up to large extent without compromising the recovery of the signal at the receiver end. The proposed system provides very high spectral efficiency; it can sacrifice large guard band frequencies to increase the subcarrier spacing to provide low-latency communication to support the real-time e-healthcare network.