在本篇論文當中,我們提出了IEEE 802.11ac在 多用戶多輸入多輸出(MU-MIMO)下 載網路中低利用率的問題,並且提出了一個新穎的傳輸機制acPad來有效的提升頻 道的利用率以及吞吐量。 其他相關的研究他們的目的是在MU-MIMO下載網路中 考慮無限資料量的需求,並且達到最大總傳輸率;與之不同的地方是,我們是考 慮不同封包長度下有限的資料量需求。 在這個前提下,無線網路基地台(AP)可能 會選擇不同傳輸時間需求的使用者一起傳輸,因而導致頻道利用率降低。 由於每 一組使用者團體的傳輸時間會被限制在有最長傳輸時間的使用者上,因此較短傳 輸時間的使用者會在傳輸完畢後產生頻道傳輸的浪費。 也就是說,當AP同時服務 多個使用者時,若有人先結束傳輸,一個傳輸機會就沒辦法完全有效的被運用。 為了要消彌這個低利用率的情況,我們提出了acPad來選出新的使用者以將空閒的 頻道傳輸時間填滿,以利提升頻道的利用率。 此外,acPad是一個擁有低時間成本 的PHY-MAC的設計,來讓AP選擇適當的使用者來服務,並且也不會降低原本的使 用者的吞吐量。 我們使用了大規模的軌跡式模擬器透過WARP來搜集真實的頻道資 訊來來測試acPad的結果。 結果顯示acPad相較於傳統MU-MIMO在IEEE802.11ac的 傳輸中,提升了136%-283%的吞吐量。

Multi-User Multiple Input Multiple Output (MU-MIMO) enables a multi-antenna access
point (AP) to serve multiple users simultaneously, and has been adopted as the IEEE
802.11ac standard. While several PHY-MAC designs have recently been proposed to improve
the throughput performance of a MU-MIMO WLAN, they, however, usually assume
that all the concurrent streams are of roughly equal length. In reality, users usually have
frames with heterogeneous lengths even after aggregation, leading to different lengths of
transmission time. Hence, the concurrent transmission opportunities might not always be
fully utilized when some streams finish earlier than the others in a transmission opportunity
(TXOP). To resolve this inefficiency, this thesis presents acPad, a PHY-MAC design that
adds additional frames to fill up the idle channel time and better utilize the spatial multiplexing
gain. acPad includes three schemes to better utilize the channel time and further
increase the throughput of padding users. The first scheme chooses padding users with
higher SINR based on the original precoder. The second scheme re-calculates the precoder
to further improve the bit-rate of padding users. The third one combines the two schemes to
simultaneously achieve high utilization and bit-rate. Our acPad identifies proper users as the
padding so as to improve the padding gain, while preventing this padding from harming all
the ongoing streams. Our evaluation via large-scale trace-driven simulations demonstrates
that acPad improves the throughput by up to 283%, or by 136% on average, as compared to
the conventional 802.11ac.

[1] “IEEE standard for information technology– telecommunications and information
exchange between systems local and metropolitan area networks– specific requirements–
part 11:Wireless lan medium access control (MAC) and physical layer (PHY) specifications–
amendment 4: Enhancements for very high throughput for operation in bands below
6 GHz,” IEEE Std 802.11ac-2013 (Amendment to IEEE Std 802.11-2012, as
amended by IEEE Std 802.11ae-2012, IEEE Std 802.11aa-2012, and IEEE Std 802.11ad-
2012), pp. 1–425, Dec. 2013.
[2] M. S. Gast, 802.11ac: A Survival Guide. O’Reilly Media, Inc., 2013.
[3] T. Yoo and A. Goldsmith, “On the optimality of multiantenna broadcast scheduling
using zero-forcing beamforming,” IEEE Journal on Selected Areas in Communications,
vol. 24, no. 3, pp. 528–541, Mar. 2006.
[4] E. Aryafar, N. Anand, T. Salonidis, and E. W. Knightly, “Design and experimental
evaluation of multi-user beamforming in wireless LANs,” in Proceedings of ACM
MobiCom, 2010.
[5] H. Yu, L. Zhong, A. Sabharwal, and D. Kao, “Beamforming on mobile devices: a
first study,” in Proceedings of ACM MobiCom, 2011.
[6] T. Wei and X. Zhang, “Random access signaling for network MIMO uplink,” in
Proceedings of IEEE INFOCOM, 2016.
[7] X. Xie and X. Zhang, “Scalable user selection for MU-MIMO networks,” in Proceedings
of IEEE INFOCOM, 2014.
[8] N. Anand, J. Lee, S. J. Lee, and E. W. Knightly, “Mode and user selection for multiuser
MIMO WLANs without CSI,” in Proceedings of IEEE INFOCOM, 2015.
[9] A. Zhou, T. Wei, X. Zhang, M. Liu, and Z. Li, “Signpost: scalable MU-MIMO signaling
with zero CSI feedback,” in Proceedings of ACM MobiHoc, 2015.
[10] W.-L. Shen, K. C.-J. Lin, M.-S. Chen, and K. Tan, “Sieve: scalable user grouping for
large MU-MIMO systems,” in Proceedings of IEEE INFOCOM, 2015.
[11] R. Sinha, C. Papadopoulos, and J. Heidemann, “Internet packet size distributions:
some observations,” USC/Information Sciences Institute, Tech. Rep. ISI-TR-2007-
643, May 2007.
[12] B. H. Bloom, “Space/time trade-offs in hash coding with allowable errors,” Communications
of the ACM, vol. 13, no. 7, pp. 422–426, Jul. 1970.
[13] Warp: wireless open access research platform, http://warpproject.org/trac/.
[14] Q. Yang, X. Li, H. Yao, J. Fang, K. Tan, W. Hu, J. Zhang, and Y. Zhang, “Bigstation:
Enabling scalable real-time signal processing in large MU-MIMO systems,” in
Proceedings of ACM SIGCOMM, 2013.
38
[15] C. Shepard, H. Yu, N. Anand, E. Li, T. Marzetta, R. Yang, and L. Zhong, “Argos:
practical many-antenna base stations,” in Proceedings of ACM MobiCom, 2012.
[16] H. S. Rahul, S. Kumar, and D. Katabi, “JMB: Scaling wireless capacity with user
demands,” in Proceedings of ACM SIGCOMM, 2012.
[17] X. Zhang, K. Sundaresan, M. A. ( Khojastepour, S. Rangarajan, and K. G. Shin,
“Nemox: Scalable network MIMO for wireless networks,” in Proceedings of ACM
MobiCom, 2013.
[18] E. Hamed, H. Rahul, M. A. Abdelghany, and D. Katabi, “Real-time distributed MIMO
systems,” in Proceedings of ACM SIGCOMM, 2016.
[19] T. Yoo, S. Member, N. Jindal, and A. Goldsmith, “Multi-antenna downlink channels
with limited feedback and user selection,” IEEE Journal on Selected Areas in
Communications, vol. 25, no. 7, pp. 1478–1491, Sep. 2007.
[20] D. N. Tse, “Optimal power allocation over parallel gaussian broadcast channels,” in
Proceedings of IEEE ISIT, 1997.
[21] J. Wang, D. J. Love, and M. D. Zoltowski, “User selection with zero-forcing beamforming
achieves the asymptotically optimal sum rate,” IEEE Transactions on Signal
Processing, vol. 56, no. 8, pp. 3713–3726, Aug. 2008.
[22] Z. Shen, J. G. Andrews, and B. L. Evans, “Optimal power allocation in multiuser
OFDM systems,” in Proceedings of IEEE GLOBECOM, 2003.
[23] I. C. Wong, Z. Shen, B. L. Evans, and J. G. Andrews, “A low complexity algorithm
for proportional resource allocation in OFDMA systems,” in IEEE Workshop on Signal
Processing Systems (SIPS), 2004.
[24] K. K. Mukkavilli, A. Sabharwal, E. Erkip, and B. Aazhang, “On beamforming with
finite rate feedback in multiple-antenna systems,” IEEE Transactions on Information
Theory, vol. 49, no. 10, pp. 2562–2579, Oct. 2003.
[25] T. Eriksson and T. Ottosson, “Compression of feedback for adaptive transmission and
scheduling,” Proceedings of the IEEE, vol. 95, no. 12, pp. 2314–2321, Dec. 2007.
[26] O. E. Ayach and R. W. Heath, “Interference alignment with analog CSI feedback,”
in Proceedings of IEEE MILCOM, 2010.
[27] V. Hassel, D. Gesbert, M.-S. Alouini, and G. E. Øien, “A threshold-based channel
state feedback algorithm for modern cellular systems,” IEEE Transactions on Wireless
Communications, vol. 6, no. 7, pp. 2422–2426, Jul. 2007.
[28] S. Sanayei and A. Nosratinia, “Opportunistic downlink transmission with limited
feedback,” IEEE Transactions on Information Theory, vol. 53, no. 11, pp. 4363–
4372, Nov. 2007.
[29] Y. Du, E. Aryafar, and J. Camp, “Ibeam: intelligent client-side multi-user beamforming
in wireless networks,” in Proceedings of IEEE INFOCOM, 2014.
[30] D. Tse and P. Vishwanath, Fundamentals of Wireless Communications. Cambridge
University Press, 2005.
[31] J. G. Andrews, W. Choi, and R. W. H. JR., “Overcoming interference in spatial multiplexing
MIMO cellular networks,” IEEE Wireless Communications, vol. 14, no. 6,
pp. 95–104, Dec. 2007.
39
[32] A. Zhou, T. Wei, X. Zhang, M. Liu, and Z. Li, “Signpost: scalable mu-mimo signaling
with zero csi feedback,” in Proceedings of ACM MobiCom, 2015.
[33] W.-L. Shen, Y.-C. Tung, K.-C. Lee, K. C.-J. Lin, S. Gollakota, D. Katabi, and M.-S.
Chen, “Rate adaptation for 802.11 multiuser mimo networks,” in Proceedings of
ACM MobiCom, 2012.
[34] D. Halperin,W. Hu, A. Sheth, and D.Wetherall, “Predictable 802.11 packet delivery
from wireless channel measurements,” in Proceedings of ACM SIGCOMM, 2010.
[35] H. Rahul, F. Edalat, D. Katabi, and C. Sodini, “Frequency-aware rate adaptation and
MAC protocols,” in Proceedings of ACM MobiCom, 2009.
[36] S. Tarkoma, C. E. Rothenberg, and E. Lagerspetz, “Theory and practice of Bloom
filters for distributed systems,” IEEE Communications Surveys & Tutorials, vol. 14,
no. 1, pp. 131–155, 2012.
[37] J. Heiskala and J. Terry, OFDM Wireless LANs: A Theoretical and Practical Guide.
Sams Publishing, 2001.