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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. 

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.