On Path Memory in List Successive Cancellation Decoder of Polar Codes

Polar code is a breakthrough in coding theory. Using list successive cancellation decoding with large list size L, polar codes can achieve excellent error correction performance. The L partial decoded vectors are stored in the path memory and updated according to the results of list management. In the state-of-the-art designs, the memories are implemented with registers and a large crossbar is used for copying the partial decoded vectors from one block of memory to another during the update. The architectures are quite area-costly when the code length and list size are large. To solve this problem, we propose two optimization schemes for the path memory in this work. First, a folded path memory architecture is presented to reduce the area cost. Second, we show a scheme that the path memory can be totally removed from the architecture. Experimental results show that these schemes effectively reduce the area of path memory.Comment: 5 pages, 6 figures, 2 table

Refining grain structure and porosity of an aluminium alloy with intensive melt shearing

The official published version of the article can be obtained at the link below.Intensive melt shearing was achieved using a twin-screw machine to condition an aluminium alloy prior to solidification. The results show that intensive melt shearing has a significant grain-refining effect. In addition, the intensive melt shearing reduces both the volume fraction and the size of porosity. It can reduce the density index from 10.50% to 2.87% and the average size of porosity in the samples solidified under partial vacuum from around 1 mm to 100 μm.Financial support was obtained from the EPSRC and the Technology Strategy Board