SYSTEMS AND METHODS FOR EXPLOITING INTER-CELL MULTIPLEXING GAIN IN WIRELESS CELLULAR SYSTEMS VIA DISTRIBUTED INPUT DISTRIBUTED OUTPUT TECHNOLOGY

• US 20140269492A1
• Filed: 03/12/2013
• Published: 09/18/2014
• Est. Priority Date: 03/12/2013
• Status: Active Grant

• Current Assignee: Rearden, LLC
• Original Assignee: Rearden, LLC
• Inventors: Forenza, Antonio, Perlman, Stephen G.
• Granted Patent: US 10,164,698 B2
• Time in Patent Office: Days
• US Class Current: 370/328
• CPC Class Codes: H04B 7/0452 Multi-user MIMO systems
• CPC Class Codes: H04B 7/0626 Channel coefficients, e.g. channel state information [CSI]

Abstract

A multiple antenna system (MAS) with multiuser (MU) transmissions (“MU-MAS”) exploiting inter-cell multiplexing gain via spatial processing to increase capacity in wireless communications networks.

Claims

1. A multiple antenna system (MAS) with multiuser (MU) transmissions (“

MU-MAS”

) exploiting inter-cell multiplexing gain via spatial processing to increase capacity in wireless communications networks.

2. The system as in claim 1 wherein power transmitted from the multiple antennas is constrained to minimize interference at the cell boundaries and spatial processing is employed to eliminate inter-cell interference.

3. The system as in claim 1 wherein power transmitted from the multiple antennas is not constrained to any particular power level, such that inter-cell interference is intentionally created throughout the cell and exploited to increase capacity of the wireless communications network.

4. The system as in claim 1 wherein the wireless communications network is a distributed antenna system and the multiple antennas are access points placed serendipitously without any transmit power constraint (as long as transmit power emissions meet the FCC rules).

5. The system as in claim 1 comprising of a plurality of distributed antennas interconnected to a centralized processor (CP) via the base stations network (BSN) and employing precoding to communicate with a plurality of client devices.

6. The system as in claim 5 wherein the centralized processor is aware of the channel state information (CSI) between the distributed antennas and the client devices, and utilizes the CSI to precode data sent over the downlink (DL) or uplink (UL) channels.

7. The system as in claim 6 wherein the CSI is estimated at the client devices and fed back to the distributed antennas.

8. The system as in claim 6 wherein the DL-CSI is derived at the distributed antennas from the UL-CSI using radio frequency (RF) calibration and exploiting UL/DL channel reciprocity.

9. The system as in claim 5 wherein the wireless communications network is a cellular network such as the LTE network, the client devices are LTE user equipments (UEs), the distributed antennas are LTE enhanced NodeBs (eNodeBs) or mobility management entities (MMEs), the CP is the LTE gateway (GW), the BSN is the S1 or X1 interface.

10. The system as in claim 9 wherein eNodeBs are grouped into “

antenna-clusters”

such that a different cell ID is associated to every antenna-cluster and all eNodeBs from the same antenna-cluster transmit the same cell ID via the primary synchronization signal (P-SS) and the secondary synchronization signal (S-SS).

11. The system as in claim 9 wherein multiple cell IDs are associated to the same antenna-cluster

12. The system as in claim 11 wherein eNodeBs within the same antenna-clusters are grouped into multiple “

antenna-subclusters”

, such that a different cell ID is associated to every antenna-subcluster.

13. The system as in claim 12 wherein the antenna-subclusters are defined statically based on predefined planning or GPS positioning information.

14. The system as in claim 12 wherein the antenna-subclusters are defined dynamically based on measurements of relative signal strength between eNodeBs or GPS positioning information.

15. The system as in claim 9 wherein a different cell ID is assigned to every area of coherence associated to the UEs.

16. The system as in claim 9 wherein all or a subset of the DL resource blocks (RBs) are assigned to every UE and simultaneous non-interfering data streams are sent from the BTSs to the UEs via precoding.

17. The system as in claim 16 wherein precoding is used in combination with carrier aggregation (CA) and applied to different portions of the radio frequency (RF) spectrum (inter-band CA) or different bands within the same portion of the spectrum (intra-band CA) to increase per-user data rate.

18. The system as in claim 1 wherein the multiple antennas are small-cells transceivers or WiFi access points.

19. The system as in claim 12 wherein every antenna-subcluster is assigned with one of the three orthogonal cell-specific reference signals (CRSs)

20. The system as in claim 12 wherein multiple antenna-subclusters are placed within one antenna-cluster with repetition patterns designed such that their respective CRSs do not interfere, thereby enabling simultaneous non-interfering transmissions from a plurality of eNodeBs.

21. The system as in claim 9 wherein closed-loop precoding methods are employed to send simultaneous non-interfering data streams from the eNodeBs to the UEs over the DL channel.

22. The system as in claim 21 wherein every UE uses the CRS to estimate the channel state information (CSI) from all eNodeBs or from only the BTSs within its own user-cluster.

23. The system as in claim 22 wherein the system estimates the time and frequency selectivity of the channel and dynamically re-allocates the CRS for different BTSs to different resource elements.

24. The system as in claim 21 wherein every UE uses the CSI reference signal (CSI-RS) or the demodulation reference signal (DM-RS) or combination of both to estimate the CSI from all eNodeBs or from only the eNodeBs within its own user-cluster.

25. The system as in claim 24 wherein the transmit power from the eNodeBs is decreased to reduce the number of eNodeBs in the user-cluster below the maximum number of antennas (i.e., eight) supported by the CSI-RS scheme in the LTE standard.

26. The system as in claim 24 wherein the eNodeBs within the user-cluster are divided into subsets of eight antennas each and the CSI-RS is sent from one subset at a time with given periodicity.

27. The system as in claim 26 wherein the periodicity of the CSI-RS for different subsets is determined based on the channel coherence time of the UE as well as the periodicity values supported by the LTE standard.

28. The system as in claim 24 wherein different patterns and periodicity than in the LTE standard are allowed for the CSI-RS to enable higher number of eNodeBs in the system.

29. The system as in claim 21 wherein the UE reports the rank indicator (RI), precoding matrix indicator (PMI) and channel quality indicator (CQI) to the CP via the PUCCH.

30. The system as in claim 21 wherein the UE report the RI, PMI and CQI to the CP via the PUSCH.

31. The system as in claim 30 wherein the system estimates the channel frequency-selectivity and dynamically adjusts the PMI to support larger number of eNodeBs for the same available UL resource.

32. The system as in claim 9 wherein open-loop precoding methods are employed to send simultaneous non-interfering data streams from the eNodeBs to the UEs over the DL channel.

33. The system as in claim 9 wherein open-loop MU-MIMO methods are employed to receive simultaneous non-interfering data streams from the UEs to the eNodeBs over the UL channel.

34. The system as in claims 32 and 33 wherein the DMRS is used to estimate the channel impulse response from all UEs to at eNodeBs.

35. The system as in claim 34 wherein the DMRS are assigned to the UEs over orthogonal interleaved RBs to increase the number of simultaneous UEs being supported in via spatial processing over the UL and DL channels.

36. The system as in claim 35 wherein the interleaved RBs are assigned statically.

37. The system as in claim 35 wherein the interleaved RBs are assigned dynamically according to certain frequency hopping pattern.

38. The system as in claim 34 wherein the active UEs are divided into groups such that the same set of DMRS is assigned to each group over consecutive time slots.

39. The system as in claim 38 wherein the shortest channel coherence time is estimated for all active UEs, and the maximum number of UE groups as well as the periodicity of the DMRS time multiplexing scheme is calculated based on that information.

40. The system as in claim 34 wherein groups of UEs employing the same set of orthogonal DMRSs are spatially separated to avoid interference between the groups.

41. The system as in claim 40 wherein the same set of orthogonal DMRSs is employed by different-subclusters identified by the same cell ID.

42. The system as in claim 34 wherein different DMRSs are assigned to different areas of coherence around the UEs.

43. The system as in claim 34 wherein different DMRS are assigned to different clusters to reduce inter-cluster interference.

44. The system as in claim 33 wherein time and frequency synchronization among UEs is achieved by exploiting DL signaling information.

45. The system as in claim 44 wherein the BTSs are synchronized to the same reference clock via direct wiring to the same physical clock or sharing a common time and frequency reference through GPSDOs.

46. The system as in claim 44 wherein relative propagation delays between UEs are avoided by processing only UEs within the same cluster via UL MU-MIMO, thereby guaranteeing UEs time synchronization.

47. The system as in claim 44 wherein relative propagation delays between UEs are compensated at the UE side before UL transmission to guarantee time synchronization of the UEs at the UL MU-MIMO receiver.

48. The system as in claim 33 wherein non-linear spatial filters, such as maximum likelihood (ML), decision feedback equalization (DFE) or successive interference cancellation (SIC) receivers, are employed to remove interference between UEs'"'"' data streams.

49. The system as in claim 33 wherein linear spatial filters, such as zero-forcing (ZF) or minimum mean squared error (MMSE) receivers, are employed to remove interference between UEs'"'"' data streams.

50. The system as in claim 33 wherein SC-FMDA is used to multiplex the UEs in the frequency domain.

51. The system as in claim 9 wherein eNodeBs are grouped into “

user-clusters” and

every UE estimates the signal-to-noise ratio (SNR) from all the eNodeBs in its neighborhood and selects the eNodeBs that belong to its user-cluster based on the SNR information.

52. The system as in claim 51 wherein the CP is aware of the SNR from the eNodeBs to every UE (based on feedback information from the UEs or information obtained from the UL channel, assuming UL/DL channel reciprocity) and selects the set of eNodeBs to be included in every user-cluster.

53. The system as in claim 51 wherein the CP selects the optimal number of BTSs per user-cluster to maximize SINR and data rate to the UE.

54. The system as in claim 51 wherein the BTSs per user-cluster are dynamically selected to adapt to the changing conditions of the propagation environment or UE mobility.

55. The system as in claim 51 wherein the BTSs per user-cluster are selected to achieve optimal tradeoff between SINR or data rate performance and computational complexity of the MU-MAS precoder.

56. The system as in claim 51 wherein the BTSs per user-cluster are dynamically selected based on tradeoffs between propagation conditions and computational resources available in the MU-MAS.

57. A method implemented within a multiple antenna system (MAS) with multiuser (MU) transmissions (“

MU-MAS”

) exploiting inter-cell multiplexing gain via spatial processing to increase capacity in wireless communications networks.

58. The method as in claim 57 wherein power transmitted from the multiple antennas is constrained to minimize interference at the cell boundaries and spatial processing is employed to eliminate inter-cell interference.

59. The method as in claim 57 wherein power transmitted from the multiple antennas is not constrained to any particular power level, such that inter-cell interference is intentionally created throughout the cell and exploited to increase capacity of the wireless communications network.

60. The method as in claim 57 wherein the wireless communications network is a distributed antenna system and the multiple antennas are access points placed serendipitously without any transmit power constraint (as long as transmit power emissions meet the FCC rules).

61. The method as in claim 57 comprising of a plurality of distributed antennas interconnected to a centralized processor (CP) via the base stations network (BSN) and employing precoding to communicate with a plurality of client devices.

62. The method as in claim 61 wherein the centralized processor is aware of the channel state information (CSI) between the distributed antennas and the client devices, and utilizes the CSI to precode data sent over the downlink (DL) or uplink (UL) channels.

63. The method as in claim 62 wherein the CSI is estimated at the client devices and fed back to the distributed antennas.

64. The method as in claim 62 wherein the DL-CSI is derived at the distributed antennas from the UL-CSI using radio frequency (RF) calibration and exploiting UL/DL channel reciprocity.

65. The method as in claim 61 wherein the wireless communications network is a cellular network such as the LTE network, the client devices are LTE user equipments (UEs), the distributed antennas are LTE enhanced NodeBs (eNodeBs) or mobility management entities (MMEs), the CP is the LTE gateway (GW), the BSN is the S1 or X1 interface.

66. The method as in claim 65 wherein eNodeBs are grouped into “

antenna-clusters”

such that a different cell ID is associated to every antenna-cluster and all eNodeBs from the same antenna-cluster transmit the same cell ID via the primary synchronization signal (P-SS) and the secondary synchronization signal (S-SS).

67. The method as in claim 65 wherein multiple cell IDs are associated to the same antenna-cluster

68. The method as in claim 67 wherein eNodeBs within the same antenna-clusters are grouped into multiple “

antenna-subclusters”

, such that a different cell ID is associated to every antenna-subcluster.

69. The method as in claim 68 wherein the antenna-subclusters are defined statically based on predefined planning or GPS positioning information.

70. The method as in claim 68 wherein the antenna-subclusters are defined dynamically based on measurements of relative signal strength between eNodeBs or GPS positioning information.

71. The method as in claim 65 wherein a different cell ID is assigned to every area of coherence associated to the UEs.

72. The method as in claim 65 wherein all or a subset of the DL resource blocks (RBs) are assigned to every UE and simultaneous non-interfering data streams are sent from the BTSs to the UEs via precoding.

73. The method as in claim 72 wherein precoding is used in combination with carrier aggregation (CA) and applied to different portions of the radio frequency (RF) spectrum (inter-band CA) or different bands within the same portion of the spectrum (intra-band CA) to increase per-user data rate.

74. The method as in claim 57 wherein the multiple antennas are small-cells transceivers or WiFi access points.

75. The method as in claim 69 wherein every antenna-subcluster is assigned with one of the three orthogonal cell-specific reference signals (CRSs).

76. The method as in claim 69 wherein multiple antenna-subclusters are placed within one antenna-cluster with repetition patterns designed such that their respective CRSs do not interfere, thereby enabling simultaneous non-interfering transmissions from a plurality of eNodeBs.

77. The method as in claim 65 wherein closed-loop precoding methods are employed to send simultaneous non-interfering data streams from the eNodeBs to the UEs over the DL channel.

78. The method as in claim 77 wherein every UE uses the CRS to estimate the channel state information (CSI) from all eNodeBs or from only the BTSs within its own user-cluster.

79. The method as in claim 78 wherein the method estimates the time and frequency selectivity of the channel and dynamically re-allocates the CRS for different BTSs to different resource elements.

80. The method as in claim 77 wherein every UE uses the CSI reference signal (CSI-RS) or the demodulation reference signal (DM-RS) or combination of both to estimate the CSI from all eNodeBs or from only the eNodeBs within its own user-cluster.

81. The method as in claim 80 wherein the transmit power from the eNodeBs is decreased to reduce the number of eNodeBs in the user-cluster below the maximum number of antennas (i.e., eight) supported by the CSI-RS scheme in the LTE standard.

82. The method as in claim 80 wherein the eNodeBs within the user-cluster are divided into subsets of eight antennas each and the CSI-RS is sent from one subset at a time with given periodicity.

83. The method as in claim 82 wherein the periodicity of the CSI-RS for different subsets is determined based on the channel coherence time of the UE as well as the periodicity values supported by the LTE standard.

84. The method as in claim 82 wherein different patterns and periodicity than in the LTE standard are allowed for the CSI-RS to enable higher number of eNodeBs in the system.

85. The method as in claim 77 wherein the UE reports the rank indicator (RI), precoding matrix indicator (PMI) and channel quality indicator (CQI) to the CP via the PUCCH.

86. The method as in claim 77 wherein the UE report the RI, PMI and CQI to the CP via the PUSCH.

87. The method as in claim 86 wherein the method estimates the channel frequency-selectivity and dynamically adjusts the PMI to support larger number of eNodeBs for the same available UL resource.

88. The method as in claim 65 wherein open-loop precoding methods are employed to send simultaneous non-interfering data streams from the eNodeBs to the UEs over the DL channel.

89. The method as in claim 65 wherein open-loop MU-MIMO methods are employed to receive simultaneous non-interfering data streams from the UEs to the eNodeBs over the UL channel.

90. The method as in claims 88 and 89 wherein the DMRS is used to estimate the channel impulse response from all UEs to at eNodeBs.

91. The method as in claim 90 wherein the DMRS are assigned to the UEs over orthogonal interleaved RBs to increase the number of simultaneous UEs being supported in via spatial processing over the UL and DL channels.

92. The method as in claim 91 wherein the interleaved RBs are assigned statically.

93. The method as in claim 85 wherein the interleaved RBs are assigned dynamically according to certain frequency hopping pattern.

94. The method as in claim 90 wherein the active UEs are divided into groups such that the same set of DMRS is assigned to each group over consecutive time slots.

95. The method as in claim 94 wherein the shortest channel coherence time is estimated for all active UEs, and the maximum number of UE groups as well as the periodicity of the DMRS time multiplexing scheme is calculated based on that information.

96. The method as in claim 90 wherein groups of UEs employing the same set of orthogonal DMRSs are spatially separated to avoid interference between the groups.

97. The method as in claim 96 wherein the same set of orthogonal DMRSs is employed by different-subclusters identified by the same cell ID.

98. The method as in claim 90 wherein different DMRSs are assigned to different areas of coherence around the UEs.

99. The method as in claim 90 wherein different DMRS are assigned to different clusters to reduce inter-cluster interference.

100. The method as in claim 89 wherein time and frequency synchronization among UEs is achieved by exploiting DL signaling information.

101. The method as in claim 90 wherein the BTSs are synchronized to the same reference clock via direct wiring to the same physical clock or sharing a common time and frequency reference through GPSDOs.

102. The method as in claim 90 wherein relative propagation delays between UEs are avoided by processing only UEs within the same cluster via UL MU-MIMO, thereby guaranteeing UEs time synchronization.

103. The method as in claim 90 wherein relative propagation delays between UEs are compensated at the UE side before UL transmission to guarantee time synchronization of the UEs at the UL MU-MIMO receiver.

104. The method as in claim 89 wherein non-linear spatial filters, such as maximum likelihood (ML), decision feedback equalization (DFE) or successive interference cancellation (SIC) receivers, are employed to remove interference between UEs'"'"' data streams.

105. The method as in claim 89 wherein linear spatial filters, such as zero-forcing (ZF) or minimum mean squared error (MMSE) receivers, are employed to remove interference between UEs'"'"' data streams.

106. The method as in claim 89 wherein SC-FMDA is used to multiplex the UEs in the frequency domain.

107. The method as in claim 65 wherein eNodeBs are grouped into “

user-clusters” and

every UE estimates the signal-to-noise ratio (SNR) from all the eNodeBs in its neighborhood and selects the eNodeBs that belong to its user-cluster based on the SNR information.

108. The method as in claim 107 wherein the CP is aware of the SNR from the eNodeBs to every UE (based on feedback information from the UEs or information obtained from the UL channel, assuming UL/DL channel reciprocity) and selects the set of eNodeBs to be included in every user-cluster.

109. The method as in claim 107 wherein the CP selects the optimal number of BTSs per user-cluster to maximize SINR and data rate to the UE.

110. The method as in claim 107 wherein the BTSs per user-cluster are dynamically selected to adapt to the changing conditions of the propagation environment or UE mobility.

111. The method as in claim 107 wherein the BTSs per user-cluster are selected to achieve optimal tradeoff between SINR or data rate performance and computational complexity of the MU-MAS precoder.

112. The method as in claim 107 wherein the BTSs per user-cluster are dynamically selected based on tradeoffs between propagation conditions and computational resources available in the MU-MAS.