Channel Decoder Architectures for Energy-Constrained Wireless Communication Systems: Holistic Approach

无线传感器网络（WSNs）和无线体域网（WBANs）的机器对机器（M2M）应用将在EPSRC的“医疗保健技术”，“与环境变化共存”和“全球不确定性”主题中提供许多新功能，从而带来显著的社会和经济效益。这些网络包括许多地理上分离的传感器节点，这些节点从其环境中收集信息并使用无线传输进行交换。然而，这些网络还不能在要求苛刻的应用中使用，因为当前的传感器节点在不使用过大、重或昂贵的电池的情况下不能保持供电足够长的时间。在这项工作中，我们的目标是实现一个数量级的扩展的无线传感器网络和WBAN的电池充电时间，通过促进其能源消耗的主要原因，即用于传感器节点之间传输信息的能量显着减少。通常防止传感器节点的传输能量的减少，因为这会导致由于噪声或干扰而损坏的传输信息。然而，我们将保持可靠的通信时，使用一个低的传输能量，通过专门设计的信道编码实现，可以在传感器节点中使用，以纠正这些传输错误。虽然现有的信道编码实现可以实现这个目标，但是它们本身可能具有高能耗，这可能侵蚀它们所提供的传输能量降低。因此，在这项工作中，我们的目标是实现一个有益的步骤变化的信道编码实现的能量消耗，使其优势保持在能源受限的无线通信系统中，如M2M应用的无线传感器网络和WBAN。我们将通过显著降低用于为信道编码实现供电的电源电压来实现这一点。通常防止电源电压的降低，因为这降低了实现的速度，并且当其操作不再能够在分配的时间内执行时，导致处理的信息被破坏。然而，我们将保持可靠的操作时，使用低电源电压，通过专门设计所提出的信道码实现使用其固有的纠错能力，不仅纠正传输错误，而且这些定时错误。据我们所知，这种新颖的方法以前从未尝试过，尽管它有显著的好处。此外，我们将开发的方法，让无线传感器网络和WBAN的设计者估计拟议的信道编码实现的能源消耗，而不必制造它们。这将使其他研究人员能够迅速优化所提出的信道编码实现的设计，以适应他们的能量受限的无线通信系统，如无线传感器网络和WBAN。使用这种方法，我们将演示如何信道编码算法和实现可以整体设计，以找到最理想的复杂性和性能之间的权衡。

The Machine-To-Machine (M2M) applications of Wireless Sensor Networks (WSNs) and Wireless Body Area Networks (WBANs) are set to offer many new capabilities in the EPSRC themes of 'Healthcare technologies', 'Living with environmental change' and 'Global uncertainties', granting significant societal and economic benefits. These networks comprise a number of geographically-separated sensor nodes, which collect information from their environment and exchange it using wireless transmissions. However, these networks cannot as yet be employed in demanding applications, because current sensor nodes cannot remain powered for a sufficient length of time without employing batteries that are prohibitively large, heavy or expensive. In this work, we aim to achieve an order-of-magnitude extension to the battery charge-time of WSNs and WBANs by facilitating a significant reduction in the main cause of their energy consumption, namely the energy used to transmit information between the sensor nodes. A reduction in the sensor nodes' transmission energy is normally prevented, because this results in corrupted transmitted information owing to noise or interference. However, we will maintain reliable communication when using a low transmit energy by specifically designing channel code implementations that can be employed in the sensor nodes to correct these transmission errors. Although existing channel code implementations can achieve this objective, they themselves may have a high energy consumption, which can erode the transmission energy reduction they afford. Therefore, in this work we will aim for achieving a beneficial step change in the energy consumption of channel code implementations so that their advantages are maintained when employed in energy-constrained wireless communication systems, such as the M2M applications of WSNs and WBANs. We shall achieve this by facilitating a significant reduction in the supply voltage that is used to power the channel code implementations. A reduction in the supply voltage is normally prevented, because this reduces the speed of the implementation and causes the processed information to become corrupted, when its operations can no longer be performed within the allotted time. However, we will maintain reliable operation when using a low supply voltage, by specifically designing the proposed channel code implementations to use their inherent error correction ability to correct not only transmission errors, but also these timing errors. To the best of our knowledge, this novel approach has never been attempted before, despite its significant benefits. Furthermore, we will develop methodologies to allow the designers of WSNs and WBANs to estimate the energy consumption of the proposed channel code implementations, without having to fabricate them. This will allow other researchers to promptly optimise the design of the proposed channel code implementations to suit their energy-constrained wireless communication systems, such as WSNs and WBANs. Using this approach, we will demonstrate how the channel coding algorithm and implementation can be holistically designed, in order to find the most desirable trade-off between complexity and performance.