Distributed MIMO has long been known theoretically to bring large throughput gains to wireless networks. Recent years have seen significant interest and progress in developing practical distributed MIMO systems. However, these systems only distribute the transmission function across the multiple nodes. The control fabric that synchronizes the nodes to a common reference phase still fundamentally requires a single leader that all nodes in the network are capable of hearing.

Recent years have seen a lot of work in moving distributed MIMO from theory to practice. While this prior work demonstrates the feasibility of synchronizing multiple transmitters in time, frequency, and phase, none of them deliver a full-fledged PHY capable of supporting distributed MIMO in real-time. Further, none of them can address dynamic environments or mobile clients. Addressing these challenges, requires new solutions for low-overhead and fast tracking of wireless channels, which are the key parameters of any distributed MIMO system. It also requires a software-hardware architecture that can deliver a distributed MIMO within a full-fledged 802.11 PHY, while still meeting the tight timing constraints of the 802.11 protocol. This architecture also needs to perform coordinated power control across distributed MIMO nodes, as opposed to simply letting each node perform power control as if it were operating alone. This paper describes the design and implementation of MegaMIMO 2.0, a system that achieves these goals and delivers the first real-time fully distributed 802.11 MIMO system.

This paper focuses on a simple, yet fundamental question: ``Can a node infer the wireless channels on one frequency band by observing the channels on a different frequency band?'' This question arises in cellular networks, where the uplink and the downlink operate on different frequencies. Addressing this question is critical for the deployment of key 5G solutions such as massive MIMO, multi-user MIMO, and distributed MIMO, which require channel state information.

Distributed coherent transmission is necessary for a variety of high-gain communication protocols such as distributed MIMO and creating codes over the air. Unfortunately, however, distributed coherent transmission is intrinsically difficult because different nodes are driven by independent clocks, which do not have the exact same frequency. This causes the nodes to have frequency offsets relative to each other, and hence their transmissions fail to combine coherently over the air. This paper presents AirShare, a primitive that makes distributed coherent transmission seamless. AirShare transmits a shared clock on the air and feeds it to the wireless nodes as a reference clock, hence eliminating the root cause for incoherent transmissions. The paper addresses the challenges in designing and delivering such a shared clock. It also implements AirShare in a network of USRP software radios, and demonstrates that it achieves tight phase coherence. Further, to illustrate AirShare's versatility, the paper uses it to deliver a coherent-radio abstraction on top of which it demonstrates two cooperative protocols: distributed MIMO, and distributed rate adaptation.

We present a demonstration of a real-time distributed MIMO system, DMIMO. DMIMO synchronizes transmissions from 4 distributed MIMO transmitters in time, frequency and phase, and performs distributed multi-user beamforming to independent clients. DMIMO is built on top of a Zynq hardware platform integrated with an FMCOMMS2 RF front end. The platform implements a custom 802.11n compatible MIMO PHY layer which is augmented with a lightweight distributed synchronization engine. The demonstration shows the received constellation points, channels, and effective data throughput at each client. It also shows how these vary as a function of interference, the timeliness of channel feedback, and the transmission rates used by the different transmitters.

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, 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 extended abstract, 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 two different systems: (1) distributed MIMO, and (2) distributed rate adaptation for wireless sensors, and show that they can provide significant performance benefits over today's systems.

We present joint multi-user beamforming (JMB), a system that enables independent access points (APs) to beamform their signals, and communicate with their clients on the same channel as if they were one large MIMO transmitter. The key enabling technology behind JMB is a new low-overhead technique for synchronizing the phase of multiple transmitters in a distributed manner. The design allows a wireless LAN to scale its throughput by continually adding more APs on the same channel. JMB is implemented and tested with both software radio clients and off-the-shelf 802.11n cards, and evaluated in a dense congested deployment resembling a conference room. Results from a 10-AP software-radio testbed show a linear increase in network throughput with a median gain of 8.1 to 9.4x. Our results also demonstrate that JMB's joint multi-user beamforming can provide throughput gains with unmodified 802.11n cards.

Diversity is an intrinsic property of wireless networks. Recent years have witnessed the emergence of many distributed protocols like ExOR, MORE, SOAR, SOFT, and MIXIT that exploit receiver diversity in 802.11-like networks. In contrast, the dual of receiver diversity, sender diversity, has remained largely elusive to such networks.

There has been burgeoning interest in wireless technologies that can use wider frequency spectrum. Technology advances, such as 802.11n and ultra-wideband (UWB), are pushing toward wider frequency bands. The analog-to-digital TV transition has made 100-250 MHz of digital whitespace bandwidth available for unlicensed access. Also, recent work on WiFi networks has advocated discarding the notion of channelization and allowing all nodes to access the wide 802.11 spectrum in order to improve load balancing. This shift towards wider bands presents an opportunity to exploit frequency diversity. Specifically, frequencies that are far from each other in the spectrum have significantly different SNRs, and good frequencies differ across sender-receiver pairs.

Wideband technologies in the unlicensed spectrum can satisfy the ever-increasing demands for wireless bandwidth created by emerging rich media applications. The key challenge for such systems, however, is to allow narrowband technologies that share these bands (say, 802.11 a/b/g/n, Zigbee) to achieve their normal performance, without compromising the throughput or range of the wideband network.

This paper proposes COPE, a new architecture for wireless mesh networks. In addition to forwarding packets, routers mix (i.e., code) packets from different sources to increase the information content of each transmission. We show that intelligently mixing packets increases network throughput. Our design is rooted in the theory of network coding. Prior work on network coding is mainly theoretical and focuses on multicast traffic. This paper aims to bridge theory with practice; it addresses the common case of unicast traffic, dynamic and potentially bursty flows, and practical issues facing the integration of network coding in the current network stack. We evaluate our design on a 20-node wireless network, and discuss the results of the first testbed deployment of wireless network coding. The results show that COPE largely increases network throughput. The gains vary from a few percent to several folds depending on the traffic pattern, congestion level, and transport protocol.

In this work, we apply network coding to unicast in wireless mesh networks to improve network throughput while reducing the bandwidth and power requirements. Our Opportunistic Coding protocol encodes and decodes packets based on distributed and local decisions, in order to reduce the number of transmissions required in forwarding. Unlike prior work which focuses on theorectical analysis, we take a systems approach and study the performance through both emulations and testbed experiments. Our protocol aims to balance the tradeoff between reliable and efficient packet delivery. Preliminary results show that the real benefit of network coding can exceed the theorectically predicted gain, due to cross-layer interactions.

This paper presents a novel framework for managing network congestion from an end-to-end perspective. Our work is motivated by trends in traffic patterns that threaten the long-term stability of the Internet. These trends include the use of multiple independent concurrent flows by Web applications and the increasing use of transport protocols and applications that do not adapt to congestion. We present an end-system architecture centered around a Congestion Manager (CM) that ensures proper congestion behavior and allows applications to easily adapt to network congestion. Our framework integrates congestion management across all applications and transport protocols. The CM maintains congestion parameters and exposes an API to enable applications to learn about network characteristics, pass information to the CM, and schedule data transmissions. Internally, it uses a window-based control algorithm, a scheduler to regulate transmissions, and a lightweight protocol to elicit feedback from receivers.We describe how TCP and an adaptive real-time streaming audio application can be implemented using the CM. Our simulation results show that an ensemble of concurrent TCP connections can effectively share bandwidth and obtain consistent performance, without adversely affecting other network flows. Our results also show that the CM enables audio applications to adapt to congestion conditions without having to perform congestion control or bandwidth probing on their own. We conclude that the CM provides a useful and pragmatic framework for building adaptive Internet applications.

We propose a new distributed route selection approach, called parallel probing, for real-time channel establishment in a point-to-point network. The existing distributed routing algorithms fall into two major categories: preferred neighbor based or flooding based. The preferred neighbor approach offers a better call acceptance rate, whereas the flooding approach is better in terms of call setup time and routing distance. The proposed approach attempts to combine the benefits of both preferred neighbor and flooding approaches in a way to improve all the three performance metrics simultaneously. This is achieved by probing k different paths in parallel, for a channel, by employing different heuristics on each path. Also, the proposed approach uses a notion called intermediate destinations (IDs), which are subset of nodes along the least-cost path between source and destination of a call, in order to reduce the excessive resource reservations while probing for a channel by releasing unused resources between IDs and initiating parallel probes at every ID. Further, it has the flexibility of adapting to different load conditions by its nature of using different heuristics in parallel, and hence, a path found for a channel would have different segments (a segment is a path between two successive IDs), and each of these segments would very well be selected by different heuristics. The effectiveness of the proposed approach has been studied through simulation for well-known network topologies for a wide range of quality-of-service and traffic parameters. The simulation results reveal that the average call acceptance rate offered by the proposed route-selection approach is better than that of both the flooding and preferred neighbor approaches, and the average call setup time and routing distance offered by it are very close to that of the flooding approach.