A method for analysing operational complexity in supply chains

This paper proposes a method for analysing the operational complexity in supply chains by using an entropic measure based on information theory. The proposed approach estimates the operational complexity at each stage of the supply chain and analyses the changes between stages. In this paper a stage is identified by the exchange of data and/or material. Through analysis the method identifies the stages where the operational complexity is both generated and propagated (exported, imported, generated or absorbed). Central to the method is the identification of a reference point within the supply chain. This is where the operational complexity is at a local minimum along the data transfer stages. Such a point can be thought of as a ‘sink’ for turbulence generated in the supply chain. Where it exists, it has the merit of stabilising the supply chain by attenuating uncertainty. However, the location of the reference point is also a matter of choice. If the preferred location is other than the current one, this is a trigger for management action. The analysis can help decide appropriate remedial action. More generally, the approach can assist logistics management by highlighting problem areas. An industrial application is presented to demonstrate the applicability of the method.

Efficient low-power design and implementation of IQ-imbalance compensator using early termination

In this paper, we propose a low-complexity architecture for the implementation of adaptive IQ-imbalance compensation in quadrature zero-IF receivers. Our blind IQ-compensation scheme jointly compensates for IQ phase and gain errors without the need for test/pilot tones. The proposed architecture employs early-termination of the iteration process; this enables the powering-down of the parts of the adaptive algorithm thereby saving power. The complexity, in terms of power-down efficiency is evaluated and shows a reduction by 37-50 % for 32-PSK and 37-58 % for 64-QAM modulated signals.