Also Available Domains Communications and Crypto Core|Xilinx ISE
The main objective of this project is to reduce the silicon area and power. In these two different finite-alphabet equalization hardware implementations that tightly integrate the memory and processing elements by a parallel array of multiply-accumulate (MAC) units and it-serial processing-in-memory (PIM) architecture
In this project, we explore two different finite-alphabet equalization hardware implementations that tightly integrate the memory and processing elements: (i) a parallel array of Multiply-Accumulate (MAC) units and (ii) a bit-serial Processing In Memory (PIM) architecture.
It is able to address both of these issues by using equalization matrices that contain low-resolution entries to lower the power and complexity of high-throughput matrix-vector products in hardware Our all-digital VLSI implementation results show that the bit-serial PIM architecture reduces the area and power consumption, when compared to a parallel MAC array that operates at the same throughput.
The effectiveness of the proposed design is synthesized and simulated using Xilinx Vivado software.
Keywords: Millimeter Wave (mmWave), massive multi-user MIMO, spatial equalization, quantization, Processing-In-Memory (PIM).
NOTE: Without the concern of our team, please don't submit to the college. This Abstract varies based on student requirements.

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