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Distributed MIMO - Patrick Maechler

Outline: 1. Motivation: Collaboration scheme achieving optimal capacity scaling 2. Distributed MIMO 3. Synchronization errors | Distributed MIMO Patrick Maechler April 2, 2008 Outline Motivation: Collaboration scheme achieving optimal capacity scaling Distributed MIMO Synchronization errors Implementation Conclusion/Outlook Throughput Scaling Scenario: Dense network Fixed area with n randomly distributed nodes Each node communicates with random destination node at rate R(n). Total throughput T(n) = nR(n) TDMA/FDMA/CDMA: T(n) = O(1) Multi-hop: T(n) = O( ) P. Gupta and P. R. Kumar, “The capacity of wireless networks,” IEEE Trans. Inf. Theory, vol. 42, no. 2, pp. 388–404, Mar. 2000. Hierarchical Cooperation: T(n) = O(n) Ayfer Özgür, Olivier Lévêque and David N. C. Tse, ”Hierarchical Cooperation Achieves Optimal Capacity Scaling in Ad Hoc Networks”, IEEE Trans. Inf. Theory, vol. 53, no. 10, pp. 3549-3572, Oct. 2007 Cooperation Scheme All nodes are divided into clusters of equal size Phase 1: Information distribution Each node splits its bits among all nodes in its cluster Cooperation Scheme Phase 2: Distributed MIMO transmissions All bits from source s to destination d are sent simultaneously by all nodes in the cluster of the source node s Cooperation Scheme Phase 3: Cooperative decoding The received signal in all nodes of the destination cluster is quantized and transmitted to destination d. Node d performs MIMO decoding. Hierarchical Cooperation The more hierarchical levels of this scheme are applied, the nearer one can get to a troughput linear in n. Outline Motivation: Collaboration scheme achieving optimal capacity scaling Distributed MIMO Synchronization errors Implementation Conclusion/Outlook Distributed MIMO Independent nodes collaborate to operate as distributed multiple-input multiple-output system Simple examples: Receive MRC (1xNr): Transmit MRC (Ntx1, channel knowledge at transmitter) Alamouti (2xNr): STBC over 2 timeslots Diversity gain but no multiplexing gain Alamouti, S.M., "A simple transmit diversity technique for wireless communications ," Selected Areas in Communications, | Distributed MIMO Patrick Maechler April 2, 2008 Outline Motivation: Collaboration scheme achieving optimal capacity scaling Distributed MIMO Synchronization errors Implementation Conclusion/Outlook Throughput Scaling Scenario: Dense network Fixed area with n randomly distributed nodes Each node communicates with random destination node at rate R(n). Total throughput T(n) = nR(n) TDMA/FDMA/CDMA: T(n) = O(1) Multi-hop: T(n) = O( ) P. Gupta and P. R. Kumar, “The capacity of wireless networks,” IEEE Trans. Inf. Theory, vol. 42, no. 2, pp. 388–404, Mar. 2000. Hierarchical Cooperation: T(n) = O(n) Ayfer Özgür, Olivier Lévêque and David N. C. Tse, ”Hierarchical Cooperation Achieves Optimal Capacity Scaling in Ad Hoc Networks”, IEEE Trans. Inf. Theory, vol. 53, no. 10, pp. 3549-3572, Oct. 2007 Cooperation Scheme All nodes are divided into clusters of equal size Phase 1: Information distribution Each node splits its bits among all nodes in its cluster Cooperation Scheme Phase 2: Distributed .