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Open Access Publications from the University of California

On Enabling Concurrent Communications in Wireless Networks

  • Author(s): Saggar, Hemant
  • Advisor(s): Pottie, Gregory J
  • et al.

Today innumerable devices use the wireless spectrum for communication, including cell-phones, WiFi devices, military radios, public safety radios, satellite phones etc. This crowding is limiting the experience of each device either through interference or by waiting for

their turn to communicate. So, how do we allow a limited spectral resource to reliably scale to many more devices? This is possible through concurrent communication where multiple links share the spectrum and communicate simultaneously using multi-antenna techniques. One promising technique is Interference Alignment (IA), that has been shown to be Degrees-of-Freedom optimal under some conditions. Still, IA requires accurate channel knowledge to be effective and its ability to achieve high throughput under time varying wireless conditions is yet unproven. We make progress towards understanding these limitations and provide viable solutions.

We study an IA system under different models of the time varying channel and derive expressions for the achieved rate over time and the system throughput. Using these, we can arrive at the optimal duration of the data phase that maximizes throughput. We propose

two strategies that help to counter the effects of a time varying channel. First, data aided receiver beam-tracking along with link adaptation provides a sizable improvement in the received signal to interference and noise ratio. Second, updating the transmit beams during data transmission using short feedback pilots improves alignment at the receivers. In faster varying channels, we get a more stable achieved rate whereas in slower varying channels, we see additional throughput gains. The conclusion from this work is that an IA system must be trained more frequently than the channel coherence time to ensure high throughput and beam adaptation during the data phase gives significant robustness to the system.

Lastly, we present an IA based medium access control (MAC) protocol that outperforms traditional protocols. Our concurrent carrier sense multiple access (CSMA) protocol based on beam-nulling is compatible with CSMA and increases the sum throughput by 2 to 3x.

We also show that IA outperforms optimal time division multiple access under time varying conditions. Hence a well-designed IA system can enable reliable concurrent communications in a wireless network.

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