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DPC for MU-MIMO

DPC for MU-MIMO. Authors:. Date: 2010-05-16. Abstract. What is DPC? Why use DPC? Detailed DPC use-case examples: Dynamic insertion/deletion of users Per-antenna power utilization DPC Implementation issues Multiple antenna user Dithering Low SNR issues: Inflating, improved LLRs.

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DPC for MU-MIMO

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  1. DPC for MU-MIMO Authors: Date: 2010-05-16 Nir Shapira, Celeno Communications

  2. Abstract • What is DPC? Why use DPC? • Detailed DPC use-case examples: • Dynamic insertion/deletion of users • Per-antenna power utilization • DPC Implementation issues • Multiple antenna user • Dithering • Low SNR issues: Inflating, improved LLRs Nir Shapira, Celeno Communications

  3. T1 x h11 T1 x h12 T2 x h22 mod a What is DPC R1 T1 Pre-processing Data 1 S1 - T2 Data 2 + + mod a R2 S2 Virtual effective triangular channel after LQ factorization mod a subtraction modulo the size of the constellation Nir Shapira, Celeno Communications

  4. What is DPC (cont’d) Power Control Modulo Factor Power Increasing Term Nir Shapira, Celeno Communications

  5. Why DPC? Increased throughput for MU-MIMO Significant gain for some channel realizations Can group “less-orthogonal” users Scenario with limited user diversity (TGac in-home scenario#3, AP serves 7 STAs, of which only 3 carrying significant traffic) Ease problem of user grouping (optimal grouping is highly complex) Can group more users. With linear ZF usually Nss<Nt. With Nt=4 can be significant. Nir Shapira, Celeno Communications

  6. Why DPC? (cont’d) LQ decomposition Triangular effective channel Solve by successive cancellation LQ user sorting according to priority Last user in LQ gets same effective channel as ZF High QoS user is assigned zero interference (first in LQ) Nir Shapira, Celeno Communications

  7. Example: DPC gain over ZF Example: An AP with 2 antennas transmitting to 2 single-antenna users By LQ factorization, we may assume a triangular channel matrix: and normalized ZF precoding: User#1 squared equivalent channel User#2 squared equivalent channel Nir Shapira, Celeno Communications

  8. Example: DPC gain (cont’d) ZF – small projection for small angles DPC - Weaker user is assigned zero interference (1’st user in LQ) Weaker user enjoys coherent beamforming, as if in SU! For stronger user: same as ZF User#1 squared equivalent channel is 1 (opposed to in ZF). Large gain for small angle ZF DPC Nir Shapira, Celeno Communications

  9. Example: DPC gain (cont’d) Ratio of integrating both curves: 1.17 • For a multi bin transmission, assuming rich multipath (uniform angle distribution), sum-rate gain of DPC for both users 17% Nir Shapira, Celeno Communications

  10. Example: DPC gain (cont’d) For large x, we care mostly about user 1: Ratio of integrating both curves: 1.34 • For a multi bin transmission, assuming rich multipath (uniform angle distribution), rate gain for weak user 34% Nir Shapira, Celeno Communications

  11. MU-DPC Preamble Design Aspects • LTFs must be resolvable • LQ - each client antenna is considered a separate user • For multi antenna client the same stream can be directed to several antennas • AP must select client antenna in advance – in case a subset of user antennas are served • Selection can be signaled in SIG field or as part of MU-MIMO group definition • LTF’s are sent without DPC cancellation • User “knows” it should not consider interference for selected antennas, since AP will cancel them during Data transmission. … … VHT LTF VHT LTF VHT LTF VHT LTF VHT LTF VHT LTF temporal SS for Linear group spatial 2SS for DPC STA#1 1SS for DPC STA#2 Nir Shapira, Celeno Communications

  12. Use case: Dynamic insertion & deletion of users within frame • “main” group of linear users + “secondary” DPC user • Main users: need constant service • High throughput requirements • Low SNR -> Low MCS -> large Air-Time consumption • Enjoy priority of LQ assignment • Secondary user: needs occasional service • With DPC, occasional service of the secondary user can be seamless for the main users Nir Shapira, Celeno Communications

  13. Insert/Delete Scheme Resolvable LTFs for all users are sent in advance Opt1 - Switch point is declared in advance (in SIGb field or in MU Group declaration) Opt2 – Switch point detected in real-time using MAC header Opt3 - Another set of Resolvable LTFs is sent at switch point Main group users can choose to update receive vectors upon switch point … VHT LTF VHT LTF VHT LTF VHT LTF DATA DATA temporal SS for Main linear group spatial SS for DPC STA#1 MAC header MAC header SS for DPC STA#2 MU Group Switch Point STA#1 – out STA#2 - in Nir Shapira, Celeno Communications

  14. Insertion/deletion of users (cont’d) ZF DPC Nir Shapira, Celeno Communications

  15. Use case: Per-antenna power utilization • Practical limitation on the TX power of the AP: per-chain power constraint, due to power amplifiers compression • Linear processing: usually optimized for an overall power constraint • Usual design rule: design for overall power constraint, then back off for per-chain constraint • With DPC, all chains can be “filled” after first stage linear processing Nir Shapira, Celeno Communications

  16. Use case: Per-antenna power utilization (cont’d) New 2 ->1 interference canceled with DPC Nir Shapira, Celeno Communications

  17. DPC implementation issues: multiple-antenna users • If total number of users antennas > number of AP antennas: need to reduce dimension Nir Shapira, Celeno Communications

  18. Multiple-antenna users (cont’d) • Option 1: User antenna selection, AP-controlled • AP learns entire channel and then selects antennas • Antenna selection can be signaled as part of MU-MIMO group => less sounding overhead • Good solution in case some user antennas do not “fit” in group Nir Shapira, Celeno Communications

  19. Multiple-antenna users (cont’d) • Option 2: User mode selection, user-controlled • User reduces effective channel dimension from number of user antennas to a predetermined number of user streams • From the sounding LTFs, the user decides on some ‘first stage’ RX BF (say, several first max. eigenmodes) • First stage RX BF fixed • Explicit User→AP CSI: only for “smaller dimension” effective channel • After AP designs TX BF, user may add second stage RX BF after modulo operation • Good solution for the case of correlated user antennas • Enjoy users’ multiple antennas MRC gain Nir Shapira, Celeno Communications

  20. Multiple-antenna users (cont’d) • User doesn’t know other users’ channels, hence first stage RX BF is suboptimal • Relevant also for linear processing, but DPC is less sensitive to non-optimal choices of the first stage BF Nir Shapira, Celeno Communications

  21. DPC Implementation issues:Dithering • What is the power of something like ? • The power depends on the “modulo constant” a, on the desired signal x, and on the interference I Nir Shapira, Celeno Communications

  22. Dithering (cont’d) • Transmit • For strong dither, the TX power is a2/12, independent of I and x • Now the constellation (“x”) is optimized within the modulo cell • The receiver can subtract the known dither Nir Shapira, Celeno Communications

  23. Summary • DPC has significant gain for particular MU channel scenarios • Ease ZF “orthogonality” constrains • DPC enables new system level features • Dynamic user insertion/deletion • Per RF-chain constraint • Several antenna/mode selection schemes introduced • Relevant to linear ZF as well Nir Shapira, Celeno Communications

  24. Backup Slides Nir Shapira, Celeno Communications

  25. Low SNR issues: Inflating • Recall: for linear processing, MMSE can be much better than ZF at low SNR • Explanation: Since the noise is large, we may gain from relaxing the total cross-stream interference cancellation constraint • There is an analog for DPC: • Relax the total interference constraint • Tradeoff between noise and residual interfernce • requires action on both AP and user Nir Shapira, Celeno Communications

  26. Inflating (cont’d) • It can be shown [Erez-Shamai-Zamir ’05] that we get desired signal + (α-1) * uniform noise + α * Gaussian noise • Dither necessary to make “uniform noise” independent of the desired signal • Theoretically optimal α (capacity): SNR/(1+SNR) • Option: pre-optimize α per SNR • Transmitter and receiver must have the same α: requiresdata exchange through control channel Nir Shapira, Celeno Communications

  27. Low SNR issues: LLR calculation • At the receiver, the RX noise is not Gaussian after the modulo operation High SNR Low SNR [Figures from Forney et al. “Sphere bound achieving coset codes and multilevel coset codes,” IEEE T-IT, vol. 46, Nov. 2000, pp. 820 – 850] • At low SNR, feeding the decoder with the modulo output “as is” is far from optimal • Significant gain by appropriate LLR calculation Nir Shapira, Celeno Communications

  28. LLR calculation (cont’d) • Example, assume BPSK, as in • LLR for modulo output y calculated as • Simplifications: small N, log-max (this is not like taking y “as is” for |y|>a/4) Nir Shapira, Celeno Communications

  29. References • M. Costa, “Writing on dirty paper,” IEEE Trans. Inform. Theory, vol. 29, pp. 439-441, May 1983. • U. Erez, S. Shamai, and R. Zamir, “Capacity and lattice strategies for canceling known interference,” IEEE Trans. Inform. Theory, vol. 51, pp. 3820-3833, Nov. 2005. • U. Erez and S. ten Brink, “A close-to-capacity dirty paper coding scheme,” IEEE Trans. Inform. Theory, vol. 51, pp. 3417-3432, Oct. 2005. Nir Shapira, Celeno Communications

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