Multidimensional Filter Bank Design using In Memory Computing

Filter banks play a crucial role in optimizing signal allocation and quality in wireless communication systems, addressing challenges like channelization and interference. However, traditional filter bank schemes suffer from high computational complexity and hardware costs. This paper proposes a novel approach for the hardware implementation of multidimensional filter banks, which significantly reduces computational complexity while maintaining high throughput. The underlying idea is to employ the in-memory computing (IMC) technique to perform filtering computations in a fully parallel manner using memristive devices. Additionally, this scheme offers scalability and flexibility, allowing it to realize multiple filters with diverse impulse responses and filter sizes.