Network-Wide Distributed Carrier Frequency Offsets Estimation and Compensation via Belief Propagation

In this paper, we propose a fully distributed algorithm for frequency offsets estimation in decentralized systems. The idea is based on belief propagation, resulting in that each node estimates its own frequency offsets by local computations and limited exchange of information with its direct neighbors. Such algorithm does not require any centralized information processing or knowledge of global network topology, thus is scalable with network size. It is shown analytically that the proposed algorithm always converges to the optimal estimates regardless of network topology. Simulation results demonstrate the fast convergence of the algorithm and show that estimation mean-squared-error at each node approaches the centralized Craḿer-Rao bound within a few iterations of message exchange.published_or_final_versio

Distributed CFOs Estimation and Compensation in Multi-cell Cooperative Networks

In this paper, we propose a fully distributed algorithm for frequency offsets estimation in multi-cell cooperative networks. The idea is based on belief propagation, resulting in that each base station or mobile user estimates its own frequency offsets by local computations and limited exchange of information with its direct neighbors in the cellular network. Such algorithm does not require any centralized information processing or knowledge of global network topology, thus is scalable with network size. Simulation results demonstrate the fast convergence of the algorithm and show that estimation mean-squared-error at each node touches the centralized Cramér-Rao bound within a few iterations of message exchange. © 2013 IEEE

Timing and Carrier Synchronization in Wireless Communication Systems: A Survey and Classification of Research in the Last 5 Years

Timing and carrier synchronization is a fundamental requirement for any wireless communication system to work properly. Timing synchronization is the process by which a receiver node determines the correct instants of time at which to sample the incoming signal. Carrier synchronization is the process by which a receiver adapts the frequency and phase of its local carrier oscillator with those of the received signal. In this paper, we survey the literature over the last 5 years (2010–2014) and present a comprehensive literature review and classification of the recent research progress in achieving timing and carrier synchronization in single-input single-output (SISO), multiple-input multiple-output (MIMO), cooperative relaying, and multiuser/multicell interference networks. Considering both single-carrier and multi-carrier communication systems, we survey and categorize the timing and carrier synchronization techniques proposed for the different communication systems focusing on the system model assumptions for synchronization, the synchronization challenges, and the state-of-the-art synchronization solutions and their limitations. Finally, we envision some future research directions

One Clock to Rule Them All: A Primitive for Distributed Wireless Protocols at the Physical Layer

Implementing distributed wireless protocols at the physical layer today is challenging because different nodes have different clocks, each of which has slightly different frequencies. This causes the nodes to have frequency offset relative to each other, as a result of which transmitted signals from these nodes do not combine in a predictable manner over time. Past work tackles this challenge and builds distributed PHY layer systems by attempting to address the effects of the frequency offset and compensating for it in the transmitted signals. In this paper, we address this challenge by addressing the root cause - the different clocks with different frequencies on the different nodes. We present AirClock, a new wireless coordination primitive that enables multiple nodes to act as if they are driven by a single clock that they receive wirelessly over the air. AirClock presents a synchronized abstraction to the physical layer, and hence enables direct implementation of diverse kinds of distributed PHY protocols. We illustrate AirClock's versatility by using it to build three different systems: distributed MIMO, distributed rate adaptation for wireless sensors, and pilotless OFDM, and show that they can provide significant performance benefits over today's systems