1. Green Communication
Department of Electronics & Communication Engineering
National Institute of Technology, Rourkela
Varun Kumar
and
Prof . Sarat Kumar Patra
2. Outline:
Objective
Literature Survey
Technical Challenges
Open Research Issues in Green Communication
Simulation Result
Future Work
3. Introduction:
Green communication is a growing research area in wireless
communication. To make an energy efficient wireless
communication without disturbing the other performance matrices
(Capacity, BER etc).
Objective
To protect environment from harmful EM radiation
reducing green house gas
Reducing operational cost for wireless network.
5. Literature Survey
Year Title Author Contribution
2002 Communication Over Fading Channels with Delay
Constraints, IEEE Transaction on Information
Theory
Randall A berry and
Robert G. Gallanger
Impact of delay on SNR
2003 Diversity and Multiplexing: A Fundamental
Tradeoff in Multiple-Antenna Channels, IEEE
Transaction on Information Theory
Lizhong Zheng, David
N.C Tse
Tradeoff analysis between
diversity and multiplexing
2007 Power Control by Geometric Programming ,
IEEE Transaction on wireless Communication
Mung Chiang,Chee wei
Tan,Daniel P.Palomar
Power control analysis using
convex optimization
2012 Energy-Aware Resource Allocation for
Cooperative Cellular Network Using Multi-
Objective Optimization Approach , IEEE
Transaction on Wireless Communication
Rajiv Devrajan, Satish
C.Jha,Umesh Phuyal,Vijay
K Bhargava
Optimum solution between
capacity maximization and
power minimization (𝑃𝑠 𝑎𝑛𝑑 𝑃𝑟)
2012 Robust Power Allocation Designs for Cognitive
Radio Networks with Cooperative Relays, in
proceeding IEEE ICC 2012
Shankhanaad Mallick
,Vijay K Bhargavas
Analysis of deterministic
channel model vs probabilistic
channel model
6. Continued--
Year Title Author Contribution
2013 Energy Aware Power Allocation in Cooperative
Communication System with Imperfect CSI,``IEEE
Transaction on Communications”
Rajiv Devrajan, Anjana
Punchihewa, Vijay K
Bhargava
Power optimization and finding
end to end SNR in cooperative
networks
2013 Massive MIMO in the UL/DL of cellular Networks:
How Many Antenna Do We Need?,``IEEE Journal
on Selected Area in Communication
Jakob Hoydis, Stephan ten
Brink, Merouane Debbah
Number of Antenna
optimization using different
detection scheme
2014 An overview of Massive MIMO: Benefits and
Challenges, IEEE Journal of Selected Topics in
Signal Processing
Lu Lu, Geoffrey ye Li, Rui
zhang
Fundamental of Massive MIMO
and its design challenge
2015 Energy-Spectrum Efficiency trade off for a Massive
SU-MIMO System with Transceiver Power
Consumption , in Proceeding ICC
Sudarshan Mukherjee and
Saif Khan Mohammed
Relation between channel gain ,
number of antenna, EE and SE
7. Energy Consumption Survey
(ICT) industry include the energy requirements as follows;
PCs and monitor == 40% , Data Centre == 23% , Fixed and mobile telecommunication == 24%
----------------------------------------------------------------------------------
40% Power requirement == Grid Electricity
60% Power requirement == Diesel Gen-Set
1 litre petrol ==2.3Kgs CO2
Total number of tower==3.1 Lac (2010) (10-15KVA gen-set – 2lit/hr)
-----------------------------------------------------------------------------------
9 million tones of CO2/year==Diesel Gen-set
5 million tones of CO2/𝑦𝑒𝑎𝑟== Power grid Ref—trai.gov.in
8. Continued-
Frequency in MHz Power density limit (in 𝑾/𝒎 𝟐)
900 0.45
1800 0.90
2100 and above 1.00
Some Guidelines
10. Power Consumption Parameter in wireless domain:
Distance
Surrounding environment
Total number of user in a cell
Capacity
Delay in signal reception
Inter-cell Interference
BER or 𝑃𝑒
SE and EE
Number of Antenna
Modulation Technique
Free space path loss equation:
𝑃𝑟 𝑑, 𝑓𝑐, 𝑃𝑡 =
𝑃𝑡 𝐺𝑡 𝐺𝑟 𝜆2
4𝜋𝑑2 𝑤ℎ𝑒𝑟𝑒 𝜆 =
1
𝑓𝑐
14. Complex vs Simple Wireless Model and Adaptive Modulation Demodulation Approach:
15. Some Existing Solution for Energy Saving in Wireless Domain:
There are technique like
• MIMO HARQ (3G/4G)
• Beamforming
• wireless mess networks
• Distributed equipment
Impact of Proper Channel Estimation for Energy Saving:
Detection and Estimation:
MF,ZF,MMSE, MLE,MAP, MVU
16. Emerging Area or Open Research Area for Green Communication:
MIMO (3G/4G) or Massive MIMO(5G)
Co-Operative Communication (D2D Communication)
Space Time Wireless Communication (O-STBC, STTC)
Role of Multiple Antenna System
• To increase diversity
• To increase multiplexing gain
• SNR improvement through beamforming
23. Observation and Scope in Above Analysis:
Observation:
EE efficiency increase with increase in SE. (If SE is very small)
If the channel gain increases the EE gradually increases, but after certain limit EE almost remain
constant.
If number of antenna increases the spectrum efficiency increases taking channel gain constant.
At very low gain and high SE nearly 50% power is consumed by power amplifier for fixed SE/fixed
channel gain and rest of power is utilised by other operation.
Note: Above analysis has been performed for Massive SU-MIMO when perfect CSI is
known and channel are uncorrelated
Scope or Future Works:
Massive MU-MIMO with perfect CSI. (Same Analysis)
Massive SU/MU-MIMO with imperfect CSI or when the channel is correlated. (Same Analysis)
Low complexity precoder design for large number of array processing.
32. Observation and Scope of the above analysis:
Observation:
Maximum capacity depends on inter-cell interference and total no of interfering cell.
MMSE/RZF gives better performance in UL/DL scenario in comparison to MF/(Eigen BF).
If total number of active antenna increases the ergodic achievable rate also gradually increases.
Note: Large number of antenna is utilized in adaptive manner . Two type of detector/precoder
performance has been observed in non cooperative multi cellular UL/DL scenario. All UT are equi-
spaced and equal in number with respective BS.
Scope or Future Works:
If UT are not equi-spaced from respective BS and not equal in number across each cell.
Case study in cooperative; multi cellular Massive MU-MIMO scenario.
Other technique may be cross checked like, MMSE-SIC, ZF-SIC, implementation of convex
optimization for performance improvement of eigen beamforming.
40. Observation and Scope of Above Analysis
If 𝑆𝑁𝑅𝑡ℎ is less the total sum of the required power is also less.
If relay is placed in the mid of source and destination and error variance is also
identical across (S-R) and (R-D) we get maximum SNR.
41. References:
[1] A. Goldsmith, Wireless communications, Cambridge university press, 2005.
[2] L. Zheng and D. N. Tse, "Diversity and multiplexing: a fundamental tradeoff in multiple-antenna
channels," Information Theory, IEEE Transactions on, vol. 49, no. 5, pp. 1073-1096, 2003.
[3] R. Zhang, L. Wang, G. Parr, O. G. Aliu, B. Awoseyila, N. Azarmi, S. Bhatti, E. Bodanese, H. Chen, M.
Dianati and others, "Advances in base-and mobile-station aided cooperative wireless
communications: An overview," Vehicular Technology Magazine, IEEE, vol. 8, no. 1, pp. 57-69,
2013.
[4] L. Wang and L. Hanzo, "Optimum time resource allocation for TDMA-based differential decode-
and-forward cooperative systems: a capacity perspective," Communications Letters, IEEE, vol. 14,
no. 6, pp. 506-508, 2010.
[5] S. Mukherjee and S. K. Mohammed, "Energy-Spectral Efficiency Trade-off for a Massive SU-MIMO
System with Transceiver Power Consumption," arXiv preprint arXiv:1410.5240, 2014.
[6] S. Mallick, R. Devarajan, M. M. Rashid and V. K. Bhargava, "Robust power allocation designs for
cognitive radio networks with cooperative relays," in Communications (ICC), 2012 IEEE
International Conference on, 2012.
[7] L. Lu, G. Y. Li, A. L. Swindlehurst, A. Ashikhmin and R. Zhang, "An overview of massive MIMO:
benefits and challenges," Selected Topics in Signal Processing, IEEE Journal of, vol. 8, no. 5, pp.
742-758, 2014.
[8] W. Liu, S. Han, C. Yang and C. Sun, "Massive MIMO or small cell network: Who is more energy
efficient?," in Wireless Communications and Networking Conference Workshops (WCNCW), 2013
IEEE, 2013.
42. [9] J. Hoydis, S. Ten Brink and M. Debbah, "Massive MIMO in the UL/DL of cellular networks: How
many antennas do we need?," Selected Areas in Communications, IEEE Journal on, vol. 31, no. 2,
pp. 160-171, 2013.
[10] A. J. Fehske, P. Marsch and G. P. Fettweis, "Bit per joule efficiency of cooperating base stations
in cellular networks," in GLOBECOM Workshops (GC Wkshps), 2010 IEEE, 2010.
[11] R. Devarajan, S. C. Jha, U. Phuyal and V. K. Bhargava, "Energy-aware resource allocation for
cooperative cellular network using multi-objective optimization approach," Wireless
Communications, IEEE Transactions on, vol. 11, no. 5, pp. 1797-1807, 2012.
[12] R. Devarajan, A. Punchihewa and V. K. Bhargava, "Energy-aware power allocation in cooperative
communication systems with imperfect CSI," Communications, IEEE Transactions on, vol. 61, no.
5, pp. 1633-1639, 2013.
[13] M. Chiang, C. W. Tan, D. P. Palomar, D. O'Neill and D. Julian, "Power control by geometric
programming," Wireless Communications, IEEE Transactions on, vol. 6, no. 7, pp. 2640-2651,
2007.
[14] S. Bu, F. R. Yu, Y. Cai and X. P. Liu, "When the smart grid meets energy-efficient
communications: Green wireless cellular networks powered by the smart grid," Wireless
Communications, IEEE Transactions on, vol. 11, no. 8, pp. 3014-3024, 2012.
[15] R. Berry, R. G. Gallager and others, "Communication over fading channels with delay
constraints," Information Theory, IEEE Transactions on, vol. 48, no. 5, pp. 1135-1149, 2002.