Dina Katabi

XORs in the air: practical wireless network coding

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 using COPE at the forwarding layer, without modifying routing and higher layers, increases network throughput. The gains vary from a few percent to several folds depending on the traffic pattern, congestion level, and transport protocol.

Embracing wireless interference: analog network coding

Traditionally, interference is considered harmful. Wireless networks strive to avoid scheduling multiple transmissions at the same time in order to prevent interference. This paper adopts the opposite approach; it encourages strategically picked senders to interfere. Instead of forwarding packets, routers forward the interfering signals. The destination leverages network-level information to cancel the interference and recover the signal destined to it. The result is analog network coding because it mixes signals not bits. So, what if wireless routers forward signals instead of packets? Theoretically, such an approach doubles the capacity of the canonical 2-way relay network. Surprisingly, it is also practical. We implement our design using software radios and show that it achieves significantly higher throughput than both traditional wireless routing and prior work on wireless network coding.

Congestion control for high bandwidth-delay product networks

Theory and experiments show that as the per-flow product of bandwidth and latency increases, TCP becomes inefficient and prone to instability, regardless of the queuing scheme. This failing becomes increasingly important as the Internet evolves to incorporate very high-bandwidth optical links and more large-delay satellite links.To address this problem, we develop a novel approach to Internet congestion control that outperforms TCP in conventional environments, and remains efficient, fair, scalable, and stable as the bandwidth-delay product increases. This new eXplicit Control Protocol, XCP, generalizes the Explicit Congestion Notification proposal (ECN). In addition, XCP introduces the new concept of decoupling utilization control from fairness control. This allows a more flexible and analytically tractable protocol design and opens new avenues for service differentiation.Using a control theory framework, we model XCP and demonstrate it is stable and efficient regardless of the link capacity, the round trip delay, and the number of sources. Extensive packet-level simulations show that XCP outperforms TCP in both conventional and high bandwidth-delay environments. Further, XCP achieves fair bandwidth allocation, high utilization, small standing queue size, and near-zero packet drops, with both steady and highly varying traffic. Additionally, the new protocol does not maintain any per-flow state in routers and requires few CPU cycles per packet, which makes it implementable in high-speed routers.

Zigzag decoding: combating hidden terminals in wireless networks

This paper presents ZigZag, an 802.11 receiver design that combats hidden terminals. ZigZags core contribution is a new form of interference cancellation that exploits asynchrony across successive collisions. Specifically, 802.11 retransmissions, in the case of hidden terminals, cause successive collisions. These collisions have different interference-free stretches at their start, which ZigZag exploits to bootstrap its decoding. ZigZag makes no changes to the 802.11 MAC and introduces no overhead when there are no collisions. But, when senders collide, ZigZag attains the same throughput as if the colliding packets were a priori scheduled in separate time slots. We build a prototype of ZigZag in GNU Radio. In a testbed of 14 USRP nodes, ZigZag reduces the average packet loss rate at hidden terminals from 72.6% to about 0.7%.

Resilient network coding in the presence of Byzantine adversaries

Network coding substantially increases network throughput. But since it involves mixing of information inside the network, a single corrupted packet generated by a malicious node can end up contaminating all the information reaching a destination, preventing decoding. This paper introduces the first distributed polynomial-time rate-optimal network codes that work in the presence of Byzantine nodes. We present algorithms that target adversaries with different attacking capabilities. When the adversary can eavesdrop on all links and jam zO links , our first algorithm achieves a rate of C - 2zO, where C is the network capacity. In contrast, when the adversary has limited snooping capabilities, we provide algorithms that achieve the higher rate of C - zO. Our algorithms attain the optimal rate given the strength of the adversary. They are information-theoretically secure. They operate in a distributed manner, assume no knowledge of the topology, and can be designed and implemented in polynomial-time. Furthermore, only the source and destination need to be modified; non-malicious nodes inside the network are oblivious to the presence of adversaries and implement a classical distributed network code. Finally, our algorithms work over wired and wireless networks.

Interference alignment and cancellation

The throughput of existing MIMO LANs is limited by the number of antennas on the AP. This paper shows how to overcome this limit. It presents interference alignment and cancellation (IAC), a new approach for decoding concurrent sender-receiver pairs in MIMO networks. IAC synthesizes two signal processing techniques, interference alignment and interference cancellation, showing that the combination applies to scenarios where neither interference alignment nor cancellation applies alone. We show analytically that IAC almost doubles the throughput of MIMO LANs. We also implement IAC in GNU-Radio, and experimentally demonstrate that for 2x2 MIMO LANs, IAC increases the average throughput by 1.5x on the downlink and 2x on the uplink.

Symbol-level network coding for wireless mesh networks

This paper describes MIXIT, a system that improves the throughput of wireless mesh networks. MIXIT exploits a basic property of mesh networks: even when no node receives a packet correctly, any given bit is likely to be received by some node correctly. Instead of insisting on forwarding only correct packets, MIXIT routers use physical layer hints to make their best guess about which bits in a corrupted packet are likely to be correct and forward them to the destination. Even though this approach inevitably lets erroneous bits through, we find that it can achieve high throughput without compromising end-to-end reliability. The core component of MIXIT is a novel network code that operates on small groups of bits, called symbols. It allows the nodes to opportunistically route groups of bits to their destination with low overhead. MIXITs network code also incorporates an end-to-end error correction component that the destination uses to correct any errors that might seep through. We have implemented MIXIT on a software radio platform running the Zigbee radio protocol. Our experiments on a 25-node indoor testbed show that MIXIT has a throughput gain of 2.8x over MORE, a state-of-the-art opportunistic routing scheme, and about 3.9x over traditional routing using the ETX metric.

Dynamic load balancing without packet reordering

Dynamic load balancing is a popular recent technique that protects ISP networks from sudden congestion caused by load spikes or link failures. Dynamic load balancing protocols, however, require schemes for splitting traffic across multiple paths at a fine granularity. Current splitting schemes present a tussle between slicing granularity and packet reordering. Splitting traffic at the granularity of packets quickly and accurately assigns the desired traffic share to each path, but can reorder packets within a TCP flow, confusing TCP congestion control. Splitting traffic at the granularity of a flow avoids packet reordering but may overshoot the desired shares by up to 60% in dynamic environments, resulting in low end-to-end network goodput Contrary to popular belief, we show that one can systematically split a single flow across multiple paths without causing packet reordering. We propose FLARE, a new traffic splitting algorithm that operates on bursts of packets, carefully chosen to avoid reordering. Using a combination of analysis and trace-driven simulations, we show that FLARE attains accuracy and responsiveness comparable to packet switching without reordering packets. FLARE is simple and can be implemented with a few KB of router state

See through walls with WiFi

Wi-Fi signals are typically information carriers between a transmitter and a receiver. In this paper, we show that Wi-Fi can also extend our senses, enabling us to see moving objects through walls and behind closed doors. In particular, we can use such signals to identify the number of people in a closed room and their relative locations. We can also identify simple gestures made behind a wall, and combine a sequence of gestures to communicate messages to a wireless receiver without carrying any transmitting device. The paper introduces two main innovations. First, it shows how one can use MIMO interference nulling to eliminate reflections off static objects and focus the receiver on a moving target. Second, it shows how one can track a human by treating the motion of a human body as an antenna array and tracking the resulting RF beam. We demonstrate the validity of our design by building it into USRP software radios and testing it in office buildings.

Dude, where's my card?: RFID positioning that works with multipath and non-line of sight

RFIDs are emerging as a vital component of the Internet of Things. In 2012, billions of RFIDs have been deployed to locate equipment, track drugs, tag retail goods, etc. Current RFID systems, however, can only identify whether a tagged object is within radio range (which could be up to tens of meters), but cannot pinpoint its exact location. Past proposals for addressing this limitation rely on a line-of-sight model and hence perform poorly when faced with multipath effects or non-line-of-sight, which are typical in real-world deployments. This paper introduces the first fine-grained RFID positioning system that is robust to multipath and non-line-of-sight scenarios. Unlike past work, which considers multipath as detrimental, our design exploits multipath to accurately locate RFIDs. The intuition underlying our design is that nearby RFIDs experience a similar multipath environment (e.g., reflectors in the environment) and thus exhibit similar multipath profiles. We capture and extract these multipath profiles by using a synthetic aperture radar (SAR) created via antenna motion. We then adapt dynamic time warping (DTW) techniques to pinpoint a tags location. We built a prototype of our design using USRP software radios. Results from a deployment of 200 commercial RFIDs in our university library demonstrate that the new design can locate misplaced books with a median accuracy of 11~cm.