Weighted OFDMA Time-Frequency Synchronization for Space Solar Power LEO Satellites Networks: Performance

and Cost Analysis

Mohsen Jamalabdollahi, Reza Zekavat

Michigan Technological University

2

Cities in the Equator Transmission Line Needed

3

LEO Satellite Networks

4

Ground Contact/Energy Transmission Period

5

International collaboration for SSP à Worldwide Ground station implementation

•  Total satellite ground contact •  Total ground contact period with sunlight •  Average path loss of wireless power transmission •  Difference in impact comparing SSO LEO, MEO, GEO;

SSO = Sun-synchronous Orbit (low-earth orbit zone) MEO = medium earth orbit GEO = geosynchronous orbit

Distributed ground station coverage area

LEO Implementation

6

Pros •  Lower altitudes à lower power loss •  Lower transmission power per unit à Less Environmental Impact •  Higher Number of Satellites à Higher reliability •  Lower Cost of Development and Launching

Cons •  LEO has 10 to 15mins contact period per ground stations à Multiple Ground Stations Needed à Handoff Process Needed •  LEO may use multiple satellite transmission à Synchronization Needed •  International Cooperation and Unified Policy; •  Routing or Battery Storage if a cluster is not in ground station field of view; Applications: SSP to remote and local area

Articles on SSP via LEO Satellite Networks �  S. T. Guh, S. A. Zekavat and O. Abdelkhalik, “Space-based Solar Power transfer via LEO satellites

network: Doppler Effect Analysis”, IEEE Trans. on Aerospace and Electronic Systems, vol. 51, no. 1, Jan. 2015.

�  S. T. Guh, S. A. Zekavat, “Space solar power orbit design and cost analysis,” proceedings Recent Advances in Space Technologies (RAST), 2015 7th International Conference on, 16-19 June 2015, pp. 753 – 758, Istanbul, Turkey.

�  S. T. Guh and S. A. Zekavat, “Space-based Solar Power via LEO Satellite Networks: Synchronization Efficiency Analysis,” proceedings IEEE Aerospace Conference, Big Sky, MT, March 03-09, 2013.

�  S. T. Guh, S. A. Zekavat, and O. Abdlekhalik, “Space-Based Wireless Solar Power transfer via a network of LEO satellites: Doppler Effect Analysis” proceedings IEEE Aerospace Conference, Big Sky, MT, March 03-09, 2012.

�  S. A. Zekavat, and O. Abdlekhalik, “An Introduction to Space-Based Power Grids: Feasibility Study,” proceedings, IEEE Aerospace Conf., Big Sky, MT, Mar. 06-12, 2011.

8

Multi-Satellite Synchronization? •  Different Doppler •  Different distance to ground

LEO Implementation: Direct Transmission

Time Synchronization

� Time offsets:

-1

-0.5

0

0.5

1

s 1(t)

-1

-0.5

0

0.5

1

s 2(t)

-1

-0.5

0

0.5

1

s 3(t)

-3

-2

-1

0

1

2

3

Σ ks k(t)

-1

-0.5

0

0.5

1

s 1(t)

-1

-0.5

0

0.5

1

s 2(t)

-1

-0.5

0

0.5

1

s 3(t)

-3

0

3

Σ k s k(t)

∑ −=m mmT tsts )()( τ { }Kmm 1=τ

Frequency Synchronization �  Frequency offsets:

-1

-0.5

0

0.5

1

s 1(t)

-1

-0.5

0

0.5

1

s 2(t)

-1

-0.5

0

0.5

1

s 3(t)

-3

-2

-1

0

1

2

3

Σ k s k(t)

-1

-0.5

0

0.5

1

s 1(t)

-1

-0.5

0

0.5

1

s 2(t)

-1

-0.5

0

0.5

1

s 3(t)

-3

-2

-1

0

1

2

3

Σ ks k(t)

∑ Δ+=m

tffjT

mcetr )(2)( π { }Kmmf 1=Δ

Idea! ◦ Design a proper training waveform for time synchronization which � Handles multi-satellite scenario � Could be easily detectable

◦ Use the detected waveform to estimate frequency offset which � Handles the unknown channel Impulse response � Computationally efficient

[1] M. Jamalabdollahi and S. A. R. Zekavat, "Joint Neighbor Discovery and Time of Arrival Estimation in Wireless Sensor Networks via OFDMA," Sensors Journal, IEEE, vol. 15, pp. 5821-5833, 2015. [2] M. Jamalabdollahi and S. Salari, "RLS-based estimation and tracking of frequency offset and channel coefficients in MIMO-OFDM systems," Wireless personal communications, vol. 71, pp. 1159-1174, 2013.

OFDMA [1]

RLS [2]

Outline

�  System Model � Proposed Technique ◦ Time Synchronization and Weighted OFDMA waveform ◦ Frequency Synchronization

�  Simulation Results �  Future Works and Conclusion

Outline

�  System Model � Proposed Technique ◦ Time Synchronization and Weighted OFDMA waveform ◦ Frequency Synchronization

�  Simulation Results �  Future Works and Conclusion

System Model

�  Received signal by target (power station at earth or the leader satellite):

�  : Training waveform of the m-th satellite

Frequency offset (FO) Channel impulse response (CIR)

Time offset

)()()( 2 ttshetr mmmmtfj

Tm ντπ +−=∑ Δ

)(tsm

Outline �  System Model � Proposed Technique ◦ Time Synchronization and Weighted OFDMA waveform ◦ Frequency Synchronization

�  Simulation Results �  Future Works and Conclusion

Time Synchronization

�  Allocating a set of OFDMA subcarriers to the m-th satellite:

�  Where: is the OFDM subcarrier spacing �  Number of allocated sub-carrier

NkekTsm

s

pfkTpj

sm ≤≤=∑ ∈Δ 1,)( 2

κπ

sNTf 1=Δ

msN κ=

Time Synchronization

𝑟 𝑘:𝑀:𝑘+𝑀

𝑁−1

Select

)𝒔(1,1)(𝑁 − 𝑛)/∗

)𝒔(1,𝑁𝑠)(𝑁 − 𝑛)/∗

)𝒔(𝑀,1)(𝑁 − 𝑛)/∗

)𝒔(𝑀,𝑁𝑠)(𝑁 − 𝑛)/∗

|.|

|.|

|.|

|.|

argmax

argmax

)𝒔(2,1)(𝑁 − 𝑛)/∗

)𝒔(2,𝑁𝑠)(𝑁 − 𝑛)/∗

|.|

|.|argmax

⋮

⋮

⋮

⋮

𝑘1∗

𝑘2∗

𝑘𝑀∗

⎭⎬⎫

⎩⎨⎧

= ∏∈

−+mp

NkkHm

km rs

κτ 1:maxargˆ

Time Synchronization

Weighted OFDMA waveform �  Increasing results high Peak to Average Power Ratio (PAPR)

sN

∑=

k

mk

mk

PAPR

sN

sG

2)(

2)(

1max

Ns = 1, GPAPR = 0 dBNs = 2, GPAPR = 3dBNs = 4, GPAPR = 6dBNs = 8, GPAPR = 9dBNs = 16, GPAPR = 11dB

Weighted OFDMA waveform

� Weighted OFDMA waveform

NkewkTsm

s

pfkTpjm

psm ≤≤=∑ ∈Δ 1,)( 2)(

κπ

{ }PAPRmN

mN

w

m Gccwm

γ−−= −)(1:1

)()( 2maxargˆ)(

( )∏∈

−+=mp

mp

NkkH

mmpm

k wrsw

cκ

)(1:

)()(

∑=

k

mk

mk

PAPR

sN

sG

2)(

2)(

1max

Weighted OFDMA waveform

𝑟 𝑘:𝑀:𝑘+𝑀

𝑁−1

Select

)𝑤1(1)𝒔(1,1)(𝑁 − 𝑛)0

∗

|.|

|.|

|.|

|.|

argmax

|.|

|.|

⋮

⋮

⋮

⋮

𝑘1∗

𝑘2∗

𝑘𝑀∗

)𝑤1(1)𝒔(1,1)(𝑁 − 𝑛)0

∗

)𝑤1(2)𝒔(2,1)(𝑁 − 𝑛)0

∗

)𝑤𝑁𝑠(1)𝒔(1,𝑁𝑠)(𝑁 − 𝑛)0

∗

)𝑤𝑁𝑠(2)𝒔(2,𝑁𝑠)(𝑁 − 𝑛)0

∗

)𝑤1(𝑀)𝒔(𝑀,1)(𝑁 − 𝑛)0

∗

)𝑤𝑁𝑠(𝑀)𝒔(𝑀,𝑁𝑠)(𝑁 − 𝑛)0

∗

1/𝑤1(1)

1/𝑤𝑁𝑠(1)

1/𝑤1(2)

1/𝑤𝑁𝑠(2)

1/𝑤1(𝑀)

1/𝑤𝑁𝑠(𝑀)

argmax

argmax

( )⎪⎭

⎪⎬⎫

⎪⎩

⎪⎨⎧

= ∏∈

−+

mpmp

NkkH

mmp

m wrsw

κτ )(

1:)(

maxargˆ

Outline

�  System Model � Proposed Technique ◦ Time Synchronization and Weighted OFDMA waveform ◦ Frequency Synchronization

�  Simulation Results �  Future Works and Conclusion

Frequency Synchronization

TimeSynchronization

Selectthetrainingwaveform

RLSbasedchannelEstimation

RLSbasedfrequencyoffsetEstimation

ℎ"𝑘

𝜀��

Frequency Synchronization

�  RLS based channel estimation minimizes: Where: Linear function respect to

�  RLS based frequency offset estimation minimizes:

Where: Non-Linear function respect to

( ) ∑=

−=k

n

nh

knk ehC

0

2)(|

)(1

ˆελ

kkkNkjn

h shreek

1

ˆ2)(|

ˆ1

−

−−=

−επ

ε

( ) ∑=

−=k

n

nh

knk eC

0

2)(|

)(2ˆ ελε

kkkNkj

knh shrere

k

ˆ1ˆ2

)(| −−=

−επ

ε

h ε

Outline

�  System Model � Proposed Technique ◦ Time Synchronization and Weighted OFDMA waveform ◦ Frequency Synchronization

�  Simulation Results �  Future Works and Conclusion

Simulation Results

�  Time Synchronization performance:

�  Frequency synchronization and Channel estimator performance:

KMSE

K

mmm∑

=

−= 1

2τττ K

MSE

K

mmm∑

=

−= 1

2εεε

K

hhMSE

K

mmm

h

∑=

−= 1

2ˆ

Simulation Results

Outline �  System Model � Proposed Technique ◦ Time Synchronization and Weighted OFDMA waveform ◦ Frequency Synchronization

�  Simulation Results �  Future Works and Conclusion

Future Works

� Proposing a frame-based structure for the proposed waveform in order to enable time-frequency offset tracking

� Extend the proposed method to handle frequency dispersive channels such as ionosphere layers

Conclusion

� Time-frequency Synchronization is vital for SSP � Weighted OFDM sub-carriers for ToA estimation which

handles ◦ Multi- satellite scenario ◦  Low PAPR

�  Joint CIR and CFO estimation � Low computational Complexity

Thank You!

Any Question?