Computationally efficient wireless reception algorithms under a long term low energy constraint

长期低能量约束下计算高效的无线接收算法

• 批准号: 121849-2010
• 负责人: Gagnon, François
• 金额: $ 3.13万
• 依托单位: École de technologie supérieure
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2013
• 资助国家: 加拿大
• 起止时间: 2013-01-01 至 2014-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=522220
• 关键词: Computationally; efficient; wireless; reception; algorithms

Multi-user wireless communication with active mobility is computationally challenging. Additionally, the complexity typically squares when the Multiple Input Multiple Output, MIMO, architectures are taken into account. A rapid appearance of several long echoes combined with high data rates favor the use of Orthogonal Frequency Division Multiplexing, OFDM. OFDM-based communications are particularly appealing because of the very low complexity frequency equalizing scheme which is used. However, new strategies such as channel shortening and sparse Recursive Least-Squares, SPARLS, equalization are emerging. These render single carrier techniques more computationally competitive by selecting only significant paths for channel equalization. All these issues have a direct impact on power consumption, thereby on battery life. This project aims at reducing the long term average energy consumption related to signal processing. In this context, long term averaging refers either to a multiplicity of successive connections, or calls, for mobile energy efficiency, or equivalently to short-term power consumption for hundreds of simultaneous users detection at a base station.

具有主动移动性的多用户无线通信在计算上具有挑战性。此外，当考虑多输入多输出 (MIMO) 架构时，复杂性通常成平方。多个长回波的快速出现与高数据速率相结合有利于正交频分复用 (OFDM) 的使用。基于 OFDM 的通信特别有吸引力，因为所使用的频率均衡方案的复杂性非常低。然而，诸如通道缩短和稀疏递归最小二乘、SPARLS、均衡等新策略正在出现。通过仅选择重要路径进行信道均衡，这些使得单载波技术在计算上更具竞争力。所有这些问题都会直接影响功耗，从而影响电池寿命。该项目旨在减少与信号处理相关的长期平均能耗。在本文中，长期平均指的是针对移动能源效率的多个连续连接或呼叫，或者等同地指在基站处同时检测数百个用户的短期功耗。