Data Mining Practical Machine Learning Tools and Techniques

Millimeter wave (mmWave) signals experience orders-of-magnitude more pathloss than the microwave signals currently used in most wireless applications and all cellular systems. MmWave systems must therefore leverage large antenna arrays, made possible by the decrease in wavelength, to combat pathloss with beamforming gain. Beamforming with multiple data streams, known as precoding, can be used to further improve mmWave spectral efficiency. Both beamforming and precoding are done digitally at baseband in traditional multi-antenna systems. The high cost and power consumption of mixed-signal devices in mmWave systems, however, make analog processing in the RF domain more attractive. This hardware limitation restricts the feasible set of precoders and combiners that can be applied by practical mmWave transceivers. In this paper, we consider transmit precoding and receiver combining in mmWave systems with large antenna arrays. We exploit the spatial structure of mmWave channels to formulate the precoding/combining problem as a sparse reconstruction problem. Using the principle of basis pursuit, we develop algorithms that accurately approximate optimal unconstrained precoders and combiners such that they can be implemented in low-cost RF hardware. We present numerical results on the performance of the proposed algorithms and show that they allow mmWave systems to approach their unconstrained performance limits, even when transceiver hardware constraints are considered.

Spatially Sparse Precoding in Millimeter Wave MIMO Systems

It is shown that, particularly for terrestrial cellular telephony, the interference-suppression feature of CDMA (code division multiple access) can result in a many-fold increase in capacity over analog and even over competing digital techniques. A single-cell system, such as a hubbed satellite network, is addressed, and the basic expression for capacity is developed. The corresponding expressions for a multiple-cell system are derived. and the distribution on the number of users supportable per cell is determined. It is concluded that properly augmented and power-controlled multiple-cell CDMA promises a quantum increase in current cellular capacity. >

On the capacity of a cellular CDMA system

In-band full-duplex (IBFD) operation has emerged as an attractive solution for increasing the throughput of wireless communication systems and networks. With IBFD, a wireless terminal is allowed to transmit and receive simultaneously in the same frequency band. This tutorial paper reviews the main concepts of IBFD wireless. One of the biggest practical impediments to IBFD operation is the presence of self-interference, i.e., the interference that the modem's transmitter causes to its own receiver. This tutorial surveys a wide range of IBFD self-interference mitigation techniques. Also discussed are numerous other research challenges and opportunities in the design and analysis of IBFD wireless systems.

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In-Band Full-Duplex Wireless: Challenges and Opportunities

In-band full-duplex (IBFD) operation has emerged as an attractive solution for increasing the throughput of wireless communication systems and networks. With IBFD, a wireless terminal is allowed to transmit and receive simultaneously in the same frequency band. This tutorial paper reviews the main concepts of IBFD wireless. Because one the biggest practical impediments to IBFD operation is the presence of self-interference, i.e., the interference caused by an IBFD node's own transmissions to its desired receptions, this tutorial surveys a wide range of IBFD self-interference mitigation techniques. Also discussed are numerous other research challenges and opportunities in the design and analysis of IBFD wireless systems.

Neighbor discovery (ND) is a critical primitive for 60-GHz wireless networks with highly directional radios. Prior work has attempted to improve the ND efficiency but overlooks the unique properties of 60-GHz phased-array antennas and spatial channel profile. In this paper, we first conduct a systematic study of the ND problem using a reconfigurable 60-GHz radio. Combined with an analytical model, we find that environmental characteristics and client mobility substantially affect 60-GHz ND latency, and due to inherent spatial channel sparsity of 60-GHz channels, even short-distance links can experience intolerable latency. To solve these new challenges, we propose a mechanism called FastND that accelerates ND by actively learning the spatial channel profile. FastND leverages steerability of 60-GHz phased-array antennas and accumulates channel information by overhearing beacon preambles along different beam directions. Using a compressive sensing framework, together with a strategical beam selection mechanism, FastND can infer the strongest spatial angle to listen to, thereby increasing the likelihood to quickly decode beacons and achieve ND. Our testbed experiments and ray-tracing tests demonstrate that FastND can reduce 802.11ad ND latency to 1/10–1/2, with different levels of mobility, human blockage, environmental sparsity, and non-line-of-sight links.

FastND: Accelerating Directional Neighbor Discovery for 60-GHz Millimeter-Wave Wireless Networks

Beamforming can improve the communication and sensing capabilities for a wide range of IoT applications. However, most existing IoT devices cannot perform beamforming due to form factor, energy, and cost constraints. This paper presents RFlens, a reconfigurable metasurface that empowers low-profile IoT devices with beamforming capabilities. The metasurface consists of many unit-cells, each acting as a phase shifter for signals going through it. By encoding the phase shifting values, RFlens can manipulate electromagnetic waves to "reshape" and resteer the beam pattern. We prototype RFlens for 5 GHz Wi-Fi signals. Extensive experiments demonstrate that RFlens can achieve a 4.6 dB median signal strength improvement (up to 9.3 dB) even with a relatively small 16 × 16 array of unit-cells. In addition, RFlens can effectively improve the secrecy capacity of IoT links and enable passive NLoS wireless sensing applications.

RFlens: metasurface-enabled beamforming for IoT communication and sensing

Voice assistants (VAs) are becoming highly popular recently as a general means of interacting with the Internet of Things. However, the use of always-on microphones on VAs imposes a looming threat on users' privacy. In this paper, we propose MicShield, the first system that serves as a companion device to enforce privacy preservation on VAs. MicShield introduces a novel selective jamming mechanism, which obfuscates the user's private speech while passing legitimate voice commands to the VAs. It achieves this by using a phoneme level jamming control pipeline. Our implementation and experiments demonstrate that MicShield can effectively protect a user's private speech, without affecting the VA's responsiveness.

https://dl.acm.org/doi/pdf/10.1145/3384419.3430727

"Alexa, stop spying on me!": speech privacy protection against voice assistants

Increasing popularity of mobile devices and upload-intensive applications is rapidly driving the uplink traffic demand in wireless LANs. Network MIMO (netMIMO) can potentially meet the demand by enabling concurrent uplink transmissions to an AP cluster (APC) comprised of multiple access points. NetMIMO's PHY-layer communication algorithms have been well explored, but the MAC-level signaling procedure remains an open issue: prior to uplink transmission, a group of clients must gain channel access, and ensure synchronization and channel orthogonality with each other. But such signaling is fundamentally challenging, because netMIMO clients tend to be widely distributed and may not even sense each other. In this paper, we introduce the first signaling protocol, called NURA, to meet the challenge. NURA clients employ a novel medium-access-signaling mechanism to realize group-based random access and synchronization, without disturbing ongoing uplink transmissions. The APC leverages a lightweight user-admission mechanism to group users with orthogonal channels (and hence high uplink capacity), without requiring costly channel-state feedback from all users. We have implemented NURA on a software-radio based netMIMO platform. Our experiments show that NURA is feasible, efficient, and can readily serve as the a priori signaling mechanism for distributed asynchronous netMIMO clients.

Random access signaling for network MIMO uplink

To meet the diverse traffic demands of different applications, emerging WLAN standards have been incorporating a variety of channel widths ranging from 5 to 160 MHz. The coexistence of variable-width channels imposes a new challenge to the 802.11 protocols, since the 802.11 MAC is agnostic of, and thus incapable of, adapting to the PHY-layer spectrum heterogeneity. To address this challenge, we uncover the cause and effect of variable-width channel coexistence, and develop a MAC-layer scheme, called Fine-grained Spectrum Sharing (FSS), that solves the general problem of fair and efficient spectrum sharing among users with heterogeneous channel-widths. Instead of deeming its spectrum band as an atomic block, an FSS user divides the spectrum into chunks, and adapts its chunk usage on a per-packet basis. FSS's spectrum adaptation is driven by a decentralized optimization framework. It preserves the 802.11 CSMA/CA primitives while allowing users to contend for each spectrum chunk, and can opportunistically split a wide-band channel or bond multiple (discontiguous) chunks to ensure fair and efficient access to available spectrum. In making such adaptation decisions, it balances the benefit from discontiguous chunks and the cost of guardband – a unique tradeoff in WLANs with heterogeneous channel-widths. Our in-depth evaluation demonstrates that FSS can improve throughput by multiple folds, while maintaining fairness of spectrum sharing for heterogeneous WLANs.

Xinyu Zhang

Papers

FastND: Accelerating Directional Neighbor Discovery for 60-GHz Millimeter-Wave Wireless Networks

RFlens: metasurface-enabled beamforming for IoT communication and sensing

"Alexa, stop spying on me!": speech privacy protection against voice assistants

Random access signaling for network MIMO uplink

Fair and Efficient Coexistence of Heterogeneous Channel Widths in Next-Generation Wireless LANs