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Cognitive LTE Small Cell Networks
 

Cognitive LTE Small Cell Networks

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Alcatel-Lucent presentation by Mérouane Debbah explaining the Light Radio Concept

Alcatel-Lucent presentation by Mérouane Debbah explaining the Light Radio Concept

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    Cognitive LTE Small Cell Networks Cognitive LTE Small Cell Networks Presentation Transcript

    • Cognitive LTE Small Cell Networks Mérouane Debbah
    • The LTE Small Cells Flexible Framework LTE: (Long Term Evolution)  The new cellular communications standard aiming at very high data rates. Idea: A dense network of low-power base stations. Bell Labs lightradio antenna module – the next Motivation: generation small cell (picture from  Higher spectral efficiency is achievable www.washingtonpost.com)  “Green” technology:  Reduced energy consumption at the base stations  Reduced electromagnetic pollution (using beamforming to intended users)
    • Vision•1Gbps/Km2 for 10 MHz•Environment constraints = <1W EIRP•Constraint: ~10 W power consumption Bell Labs lightradio antenna module – the next generation small cell (picture from www.washingtonpost.com)
    • LightRadio Concept• 2-inch cube that aims to replace unsightly cell towers• LightRadio reduces energy consumption of mobile networks by up to 50% over current radio access network equipment• Networks will be redesigned as a system of federated broadband hotspots that can be set up anywhere and can be powered by electricity, wind or sun.• It is the end of the classical base station if we can provide a new radio radio interface for non-interfering networks.
    • Motivation Supélec
    • Motivation Supélec
    • Motivation Supélec
    • Motivation Supélec
    • Motivation Supélec
    • Motivation Supélec
    • Motivation Supélec
    • Motivation Supélec
    • Motivation Supélec
    • Motivation Supélec
    • Motivation Supélec
    • Motivation Supélec
    • Toy scenario
    • A bit of history on the LTE interface
    • Shannon’s point of view on OFDMC. E. Shannon, ”Communication in the presence of Noise”, Proceeding of the IRE, vol. 37,no.1, pp. 10-21, Jan, 1949. 2
    • Fourier”We can divide the band into a large number of small bands, with N (f ) approximatelyconstant in each”In Shannon’s terms, N (f ) is the power spectrum. 3
    • • OFDM is the best you can do for a point to point scenario….but not in a multi-user setting….
    • First OFDM schemeM. L. Doeltz, E. T. Heald and D. L. Martin, ”Binary data transmission techniques for linearsystems,” Proc. IRE, vol. 45, pp. 656-661, May 1957.• First system known as Kineplex (50 years ago!) for military purposes in the band [1.8- 30Mhz]. Unfortunately, not much is known about this system...classified! 4
    • The Analog age of OFDMB. R. Saltzberg, ”Performance of an efficient Parallel Data Transmission System,” IEEETrans. Commun, Vol. Com-15, p. 805-811, Dec. 1967S. B. Weinstein and P. M. Ebert, ”Data Transmission by frequency Division Multiplexing”,IEEE Trans. Commun, vol. COM-19, pp. 628-634, Oct, 1971. Joseph Fourier, 1768-1830The basic idea used the Fourier transform but the success was limited due to the highcost of orthogonal analog filters. 5
    • The digital age of OFDMA. Peled and A. Ruiz, ”Frequency domain data transmission using reduced computationalcomplexity algorithms”, in Proc. IEEE Int. Conf. Acoustics, Speech and SignalProcessing, Apr. 1980, pp. 964-967B. Hirosaki, ”An Orthogonally multiplexed QAM system using the discrete FourierTransform,” IEEE Trans. Commun,. vol. Com-29, pp. 982-989, Jul. 1981The modulator was based on the FFT and had well celebrated features thanks to Cooley(IBM) and Tukey (Princeton) in 1965.But how does one cope with frequency selective channels? 6
    • OFDM AfterwardsWO9004893, oct, 1989, First worldwide patent introducing the guard interval in OFDM Tristan de Couasnon, 1946- ,Supelec then TH-CSFThe idea is based on the use of a guard interval.The unexploited guard interval trades complexity for performance but this is exactly thedegree of freedom we needWe have to exploit it! 7
    • Our proposal: VFDM Vandermonde-subspace Frequency Division Multiplexing A linear Vandermonde-based orthogonal precoder that generates zero interference on the primary network by ex- ploiting the frequency selective nature of the channel. [1] L. S. Cardoso, M. Kobayashi, Ø. Ryan, and M. Debbah, “Vandermonde frequency division multiplexing for cognitive radio,” SPAWC 2008 [2] L. S. Cardoso, R. Calvacanti, M. Kobayashi and M. Debbah, “Vandermonde-Subspace Frequency Division Multiplexing Receiver Analysis,” PIMRC 2010 Supélec
    • System Model Supélec
    • System Model Supélec
    • System Model s1 x1 = AFH s1 y1 = F T (h(11) )x1 + n1 Supélec
    • System Model s1 x1 = AFH s1 s2 y1 = F T (h(11) )x1 + n1 Supélec
    • System Model s1 x1 = AFH s1 x2 = Es2 s2 y2 = F T (h(22) )x2 + T (h(12) )x1 + n1 y1 = F T (h(11) )x1 + T (h(21) )x2 + n1 Supélec
    • System Model s1 x1 = AFH s1 x2 = Es2 s2 y2 = F T (h(22) )x2 + T (h(12) )x1 + n1 y1 = F T (h(11) )x1 + T (h(21) )x2 + n1 Supélec
    • System Model s1 x1 = AFH s1 x2 = Es2 s2 y2 = F T (h(22) )x2 + T (h(12) )x1 + n1 y1 = F T (h(11) )x1 + T (h(21) )x2 + n1 Supélec
    • Precoder Our objective is to find an E ∈ C (N+L)×L such that for any s2 : T (h(21) )E = 0. (1) Supélec
    • Precoder Our objective is to find an E ∈ C (N+L)×L such that for any s2 : T (h(21) )E = 0. (1) One solution to (1) is given by the Vandermonde-subspace matrix: 1 ··· 1    a1 ··· aL   a12 ··· aL2  V= , (2)    . . .. . .   . . .  N+L−1 N+L−1 a1 ··· aL L (21) L−i where {al , . . . , aL } are the roots of S(z) = i=0 hi z . Supélec
    • PrecoderA bit of linear algebra 1 1 1 1     h2 h1 h0 0 0 0  a1 a2 a3 a4   2 2 2 2   0  h2 h1 h0 0 0   a1 a2 a3 a4   0 0 h2 h1 h0 0   3 3 3 3   a1 a2 a3 a4  4 4 4 4   0 0 0 h2 h1 h0  a1 a2 a3 a4  5 5 5 5 a1 a2 a3 a4 Supélec
    • PrecoderA bit of linear algebra 1 1 1 1     h2 h1 h0 0 0 0  a1 a2 a3 a4   2 2 2 2   0  h2 h1 h0 0 0   a1 a2 a3 a4   0 0 h2 h1 h0 0   3 3 3 3   a1 a2 a3 a4  4 4 4 4   0 0 0 h2 h1 h0  a1 a2 a3 a4  5 5 5 5 a1 a2 a3 a4 2 = h2 + h1 a1 + h0 a1 Supélec
    • PrecoderA bit of linear algebra 1 1 1 1     h2 h1 h0 0 0 0  a1 a2 a3 a4   2 2 2 2   0  h2 h1 h0 0 0   a1 a2 a3 a4   0 0 h2 h1 h0 0   3 3 3 3   a1 a2 a3 a4  4 4 4 4   0 0 0 h2 h1 h0  a1 a2 a3 a4  5 5 5 5 a1 a2 a3 a4 2 = h2 + h1 a1 + h0 a1 = 0 Supélec
    • PrecoderA bit of linear algebra 1 1 1 1     h2 h1 h0 0 0 0  a1 a2 a3 a4   2 2 2 2   0  h2 h1 h0 0 0   a1 a2 a3 a4   0 0 h2 h1 h0 0   3 3 3 3   a1 a2 a3 a4  4 4 4 4   0 0 0 h2 h1 h0  a1 a2 a3 a4  5 5 5 5 a1 a2 a3 a4 2 3 = h2 a1 + h1 a1 + h0 a1 = 0 Supélec
    • PrecoderA bit of linear algebra 1 1 1 1     h2 h1 h0 0 0 0  a1 a2 a3 a4   2 2 2 2   0  h2 h1 h0 0 0   a1 a2 a3 a4   0 0 h2 h1 h0 0   3 3 3 3   a1 a2 a3 a4  4 4 4 4   0 0 0 h2 h1 h0  a1 a2 a3 a4  5 5 5 5 a1 a2 a3 a4 2 3 4 = h2 a1 + h1 a1 + h0 a1 = 0 Supélec
    • PrecoderA bit of linear algebra 1 1 1 1     h2 h1 h0 0 0 0  a1 a2 a3 a4   2 2 2 2   0  h2 h1 h0 0 0   a1 a2 a3 a4   0 0 h2 h1 h0 0   3 3 3 3   a1 a2 a3 a4  4 4 4 4   0 0 0 h2 h1 h0  a1 a2 a3 a4  5 5 5 5 a1 a2 a3 a4 3 4 5 = h2 a1 + h1 a1 + h0 a1 = 0 Supélec
    • TDD Mode required
    • Simulation Scenario 802.11a standard; N = 64, L = 16; OFDM symbol time tblk of 4 µs; (3.2 µs of useful data and 0.8 µs of guard interval) Output metrics: Pe (for QPSK constellation); Spectral efficiency Cross interference factor α ∈ [0, 1] to scale the interference coming from the primary system: y2 = F T (h(22) )x2 + αT (h(12) )x1 + n2 . Supélec
    • Equalizers for VFDM 3 2 L=8 α=0 L=16 1.8 α=0.1 L=32 2.5 α=0.5 1.6 α=1 1.4 2Ropt [bps/Hz] Ropt [bps/Hz] 1.2 1.5 1 0.8 1 0.6 0.4 0.5 0.2 0 0 0 4 8 12 16 20 24 28 0 4 8 12 16 20 24 28 1/σ2 [dB] n 1/σ2 [dB] n Optimal Receiver — N = 64 and L = 16. 0 10 MF ZF 1.2 MMSE Optimal Receiver 1 −1 10Ropt,Rlin [bps/Hz] 0.8 Pe 0.6 −2 10 ZF α = 0 0.4 MMSE α = 0 ZF α = 0.5 MMSE α = 0.5 0.2 ZF α = 1 MMSE α = 1 −3 10 0 4 8 2 12 16 20 0 4 8 12 16 20 1/σn [dB] 1/σ2 [dB] Optimal and linear receivers — N = 64 and L = 16. Supélec
    • MU-VFDM Multi-user Vandermonde-subspace Frequency Division Multiplexing A linear cascaded precoder that generates zero interfer- ence on the primary network and manages multi-user in- terference in the secondary network [4] L. S. Cardoso, M. Maso, M. Kobayashi, and M. Debbah. ”Orthogonal LTE two-tier cellular networks”. To appear in proceedings of International Conference on Communications 2011 [5] M. Maso, L. S. Cardoso, M. Debbah, and L. Vangelista. ”Orthogonal precoder for LTE Small-Cells networks”. IEEE Journal on Selected Areas in Communications (submitted), 2011. Supélec
    • System Model Supélec
    • System Model Supélec
    • System Model sm ss Supélec
    • System Model sm ss ym = Hmm sm + νp Supélec
    • System Model sm ss ys = Hss Wss + Hms sm + νs ym = Hmm sm + Hsm Wss + νp Supélec
    • System Model sm ss ys = Hss Wss + Hms sm + νs ym = Hmm sm + Hsm Wss + νp Supélec
    • System Model sm ss ys = Hss Wss + Hms sm + νs ym = Hmm sm + Hsm Wss + νp Supélec
    • Precoder W = ZE Supélec
    • Precoder W = ZE Inner precoder E (Vandermonde) Hsm E = 0, (4) K where E is defined as E = i=1 Ei . (4) is satisfied when (i,·) Hsm Ei = 0 ∀i ∈ [1, K ]. Supélec
    • Precoder W = ZE Inner precoder E (Vandermonde) Hsm E = 0, (4) K where E is defined as E = i=1 Ei . (4) is satisfied when (i,·) Hsm Ei = 0 ∀i ∈ [1, K ]. Outer precoder Z (ZFBF) H† ss Z= tr(H† H†H ) ss ss where Hss = Hss E. Z is feasible only when TX dimensions ≥ RX dimensions. Supélec
    • Channel estimation Channel estimation protocol Design of a channel estimation protocol, that takes into consideration the primary system’s own channel estima- tion, and tries to minimize errors. [7] M. Maso, L. Cardoso, M. Debbah, and L. Vangelista. ”Channel Estimation Impact for MU-VFDM LTE Small Cells”. IEEE Global Communications Conference (submitted), 2011 Supélec
    • Imperfect CSITModel Block fading channel of coherence time T Channel estimation in the MC is performed during τ ≤ T τ is divided into two parts, τ1 (UL channel estimation phase) and τ2 (DL channel estimation phase) τ τ1 τ2 transmission time t T Figure: Channel estimation and transmission times. Supélec
    • Protocol t T Supélec
    • Protocol Training τ1 t T Supélec
    • Protocol Training τ1 t T Supélec
    • Protocol Training τ1 t T Supélec
    • Protocol S1 E τ1 t T Supélec
    • Protocol Xm Training Xs Training τ1 τ2 t T Supélec
    • Protocol Xm Training Xm ⊥ Xs Xs Training τ1 τ2 t T Supélec
    • Protocol Xm Training Xm ⊥ Xs Xs Training τ1 τ2 t T Supélec
    • Protocol Hmm W = ZE τ τ1 τ2 t T Supélec
    • Protocol τ τ1 τ2 transmission time t T Supélec
    • Performance The precoder W is based on an imperfect channel estimation affecting the performance of both systems. N SUM, I T −τ Cm = log2 (1 + SINRi (τ )) and T (N + L) i=1 γrx KN T −τ CsSUM, I = log2 (1 + SINRi (τ )) T (N + L) i=1 Supélec
    • Performance 0.46 0.7 0.44 0.42 0.6 0.4 0.5Rate loss Rate loss 0.38 0.36 0.4 0.34 0.32 0.3 0.3 SNR = 20 dB SNR = 20 dB 0.28 SNR = 10 dB 0.2 SNR = 10 dB SNR = 0 dB SNR = 0dB 0.26 0.05 0.1 0.15 0.2 0.25 0.3 0.35 0.05 0.1 0.15 0.2 0.25 0.3 0.35 τ τ T TFigure: Rate loss of the MC due to Figure: Rate loss of the SCs due toimperfect CSIT as τ changes. imperfect CSIT as τ changes. Supélec
    • DemoIntroduction MU-VFDM case; User configurable: physical layer and network parameters; Macro Cell and Small Cells randomly deployed on a 3D map representing a realistic scenario; Mobility of all user equipments (Random Walk @ 3km/h); Instantaneous and time evolving capacity user equipments; Developed in MATLAB and exported to C# Supélec
    • DemoInit MU-VFDM demo, opening screen. Supélec
    • DemoConfiguration MUVFDM demo, configuration panel. Supélec
    • DemoRunning MU-VFDM demo, simulation running. Supélec
    • DemoResults MU-VFDM, single MUE and SUE performance. Supélec
    • Conclusions and Further Work VFDM is viable for interference cancellation for cognitive radio networks Non-negligible rates in the single cell scenario if perfect CSI is available Zero interference achieved at the expense of a lower rate for the secondary system, though competitive with the primary system in high-user scenario Thanks to the dense network layout and cognitive capabilities the capacity per area is increased. The achievable sum-rate increases so more users can be served Further work: Implementation of a VFDM testbed; VFDM with limited backhaul capacity; Analysis of the clustered MIMO case. Supélec
    • Bibliography L.S. Cardoso, M. Kobayashi, Ø. Ryan, and M. Debbah. Vandermonde frequency division multiplexing for cognitive radio. In Proceedings of the 9th IEEE Workshop on Signal Processing Advances in Wireless Communications, pages 421–425, 2008. L.S. Cardoso, F.R.P. Cavalcanti, M. Kobayashi, and M. Debbah. Vandermonde-subspace frequency division multiplexing receiver analysis. In PIMRC 2010, September 2010. H. Holma and A. Toskala. LTE for UMTS OFDMA and SC-FDMA Based Radio Access. 2009. L.S. Cardoso, M. Maso, M. Kobayashi, and M. Debbah. Orthogonal LTE two-tier cellular networks. In To appear in proceedings of International Conference on Communications 2011, 2011. M. Maso, L. S. Cardoso, M. Debbah, and L. Vangelista. Orthogonal precoder for LTE Small-Cells networks. IEEE Journal on Selected Areas in Communications (submitted), 2011. J. Hoydis, M. Kobayashi, and M. Debbah. Optimal channel training in uplink network MIMO systems. IEEE Transactions on Signal Processing (accepted for publication), 2010. M. Maso, L. S. Cardoso, M. Debbah, and L. Vangelista. Channel estimation impact for MU-VFDM LTE Small Cells. In IEEE Global Communications Conference (submitted), 2011. Supélec
    • The road ahead