Challenges in CISE: Algorithm and Implementation Co-Design for Optimizing Average Complexity/Performance: A Case-Study in High-Performance Low-Power Mobile Multimedia Comm. Design

我们提出了一种新的系统设计范例，其中算法和电路实现共同设计，以实现高性能，同时最小化平均功耗。我们建议使用自适应均衡器/解码器的案例研究来推动研究，其中算法选择和异步硬件设计将使用最小平均复杂性（MAC）方法来解决。特别是，我们将开发MAC优化移动无线电接收机的代表性组件的详细异步设计，联合自适应均衡和解码的可变复杂度算法，这些算法对典型移动用户的平均计算负载的表征，MAC算法优化的一般程序，新算法的架构以及相对于标准设计的功耗的定量估计。

We propose a new paradigm for system design in which the algorithm and circuit implementations are jointly designed to achieve high-performance while minimizing average power consumption. We propose to drive the research using a case study of an adaptive equalizer/decoder where both algorithm selection and asynchronous hardware design will be tackled using a Minimum Average Complexity (MAC) approach. In particular, we will develop a detailed asynchronous design of representative components of a MAC optimized mobile radio receiver, variable complexity algorithms for joint adaptive equalization and decoding, a characterization of the average computational load of these algorithms for a typical mobile user, general procedures for MAC algorithm optimization, an architecture for the new algorithms and a quantitative estimate of the power savings relative to a standard design.