Conventional thinking treats the wireless channel as a constraint,
so wireless network designs to date target endpoint
designs that best utilize the channel. Examples include rate
and power control at the transmitter, sophisticated receiver decoder
designs, and high-performance forward error correction
for the data itself. We instead explore whether it is possible
to reconfigure the environment itself to facilitate wireless
communication. In this work, we instrument the environment
with a large array of inexpensive antenna (LAIA) elements,
and design algorithms to configure LAIA elements in real
time. Our system achieves a high level of programmability
through rapid adjustments of an on-board phase shifter in
each LAIA element. We design a channel decomposition
algorithm to quickly estimate the wireless channel due to the
environment alone, which leads us to a process to align the
phases of the LAIA elements. Variations of our core algorithm
then improve wireless channels on the fly for singleand
multi-antenna links, as well as nearby networks operating
on adjacent frequency bands. We implement and deploy a
36-element LAIA array in a real indoor home environment.
Experiments in this setting show that, by reconfiguring the
wireless environment, we can achieve a 24% TCP throughput
improvement on average and a median improvement of 51.4%
in Shannon capacity over baseline single-antenna links. Over
baseline multi-antenna links, LAIA achieves an improvement
of 12.23% to 18.95% in Shannon capacity.
more »
« less
Towards Programming the Radio Environment with Large Arrays of Inexpensive Antennas
Conventional thinking treats the wireless channel as a given constraint. Therefore, wireless network designs to date center on the problem of the endpoint optimization that best utilizes the channel, for example, via rate and power control at the transmitter or sophisticated decoding mechanisms at the receiver. We instead explore whether it is possible to reconfigure the environment itself to facilitate wireless communication. In this work, we instrument the environment with a large array of inexpensive antennas (LAIA) and design algorithms to configure them in real time. Our system achieves this level of programmability through rapid adjustments of an on-board phase shifter in each LAIA device. We design a channel decomposition algorithm to quickly estimate the wireless channel due to the environment alone, which leads us to a process to align the phases of the array elements. Variations of our core algorithm can then optimize wireless channels on the fly for single- and multi-antenna links, as well as nearby networks operating on adjacent frequency bands. We design and deploy a 36-element passive array in a real indoor home environment. Experiments with this prototype show that, by reconfiguring the wireless environment, we can achieve a 24% TCP throughput improvement on average and a median improvement of 51.4% in Shannon capacity over the baseline single-antenna links. Over the baseline multi-antenna links, LAIA achieves an improvement of 12.23% to 18.95% in Shannon capacity.
more »
« less
- NSF-PAR ID:
- 10092827
- Date Published:
- Journal Name:
- 16th USENIX Symposium on Networked Systems Design and Implementation
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
More Like this
-
-
null (Ed.)Using ideas from Chu and Bode/Fano theories, we characterize the maximum achievable rate over the single-input single-output wireless communication channels under a restriction on the antenna size at the receiver. By employing circuit-theoretic multiport models for radio communication systems, we derive the information-theoretic limits of compact antennas. We first describe an equivalent Chu’s antenna circuit under the physical realizability conditions of its reflection coefficient. Such a design allows us to subsequently compute the achievable rate for a given receive antenna size thereby providing a physical bound on the system performance that we compare to the standard size-unconstrained Shannon capacity. We also determine the effective signal-to-noise ratio (SNR) which strongly depends on the antenna size and experiences an apparent finite-size performance degradation where only a fraction of Shannon capacity can be achieved. We further determine the optimal signaling bandwidth which shows that impedance matching is essential in both narrowband and broadband scenarios. We also examine the achievable rate in presence of interference showing that the size constraint is immaterial in interference-limited scenarios. Finally, our numerical results of the derived achievable rate as function of the antenna size and the SNR reveal new insights for the physically consistent design of radio systems.more » « less
-
There has been recent work on the design of antenna arrays for beamforming in dynamic evolving environments such as in vehicle-to-vehicle communication systems. A key problem is that of determining how to optimally use a large antenna array to communicate with multiple spatially located vehicles in dynamically changing channel conditions with minimal co-channel interference while minimizing overall power consumption of the wireless system. We envision disjoint subsets of antennas in the array being used to direct beams concurrently to different vehicles. The number of antennas, gain and phase of each RF-chain driving an antenna are optimized dynamically using a constrained quadratic cost formulation encompassing channel quality, interference and power consumption. This quadratic optimization problem is solved using behavior constrained bandit algorithm, a reinforcement learning based technique. A gaussian kernel is used to perform data clustering of vehicle environment and resulting solutions, allowing quick bootstrapping of the bandit solver to find optimal array configurations in real-time vehicle environments. Simulation studies prove the viability of the proposed scheme.more » « less
-
Full-duplex (FD) communication in many-antenna base stations (BSs) is hampered by self-interference (SI). This is because a FD node’s transmitting signal generates significant interference to its own receiver. Recent works have shown that it is possible to reduce/eliminate this SI in fully digital many-antenna systems, e.g., through transmit beamforming by using some spatial degrees of freedom to reduce SI instead of increasing the beamforming gain. On a parallel front, hybrid beamforming has recently emerged as a radio architecture that uses multiple antennas per FR chain. This can significantly reduce the cost of the end device (e.g., BS) but may also reduce the capacity or SI reduction gains of a fully digital radio system. This is because a fully digital radio architecture can change both the amplitude and phase of the wireless signal and send different data streams from each antenna element. Our goal in this paper is to quantify the performance gap between these two radio architectures in terms of SI cancellation and system capacity, particularly in multi-user MIMO setups. To do so, we experimentally compare the performance of a state-of-the-art fully digital many antenna FD solution to a hybrid beamforming architecture and compare the corresponding performance metrics leveraging a fully programmable many-antenna testbed and collecting over-the-air wireless channel data. We show that SI cancellation through beam design on a hybrid beamforming radio architecture can achieve capacity within 16% of that of a fully digital architecture. The performance gap further shrinks with a higher number of quantization bits in the hybrid beamforming system.more » « less
-
Orthogonal blinding based schemes for wireless physical layer security aim to achieve secure communication by injecting noise into channels orthogonal to the main channel and corrupting the eavesdropper’s signal reception. These methods, albeit practical, have been proven vulnerable against multiantenna eavesdroppers who can filter the message from the noise. The venerability is rooted in the fact that the main channel state remains stasis in spite of the noise injection, which allows an eavesdropper to estimate it promptly via known symbols and filter out the noise. Our proposed scheme leverages a reconfigurable antenna for Alice to rapidly change the channel state during transmission and a compressive sensing based algorithm for her to predict and cancel the changing effects for Bob. As a result, the communication between Alice and Bob remains clear, whereas randomized channel state prevents Eve from launching the knownplaintext attack. We formally analyze the security of the scheme against both single and multi-antenna eavesdroppers and identify its unique anti-eavesdropping properties due to the artificially created fast changing channel. We conduct extensive simulations and real-world experiments to evaluate its performance. Empirical results show that our scheme can suppress Eve’s attack success rate to the level of random guessing, even if she knows all the symbols transmitted through other antenna modes.more » « less
- Free Publicly Accessible Full Text
-
Accepted Manuscript1.0
- Conference Paper:
- The DOI is not currently available.
