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Radio Resource Management for 4G Based on Cross Layer Design


The IET 2rd International Conference on Wireless, Mobile & Multimedia Networks (ICWMMN2008)

Radio Resource Management for 4G Based on Cross Layer Design
Dongfeng Yuan
Wireless Mobile Communications and Transmission Lab.(WMCT) Shandong University Beijing, China Oct. 13, 2008

Outline
Overview of RRM and CLD
Radio Resource Management (RRM) Cross-Layer Design (CLD) RRM based on CLD

Typical examples
Link-based adaptive transmissions RRM to improve end-to-end QoS

Conclusions and future work

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What is RRM ?
Issues in wireless communication
What kind of resources can be used ? radio resources How to use these resources ? management

Radio resources include:
Transmission power frequency (FDMA) time-slots (TDMA) codes (CDMA) sub-carrier (OFDM, OFDMA) …
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What is RRM ? (Cont.)
Aim of RRM: Allocate and manage radio resources efficiently, such as
Power control to overcome near-far effects. Channel assignment, including frequency, codes, time-slots, sub-carriers, antennas Rate control, such as AMC and HARQ
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Why RRM is important
Increasing QoS requirements
Different services need to be supported with different QoS with the increasing of users’ number rapidly.

Wireless networks are inherently resource limited and has charactristics:
Time-varying wireless channels, due to multi-path fading; Interference resulted from the coexistence of different wireless networks; Almost no more spectrum available to be assigned; Assigned spectrum is wasted significantly--- result in CR

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Why RRM is important ? (Cont.)
So RRM becomes the bottleneck in future communication networks. Novel solutions have been proposed to overcome this bottleneck:
CLD: CLD aims at improving the performance of overall system. [Nossek2007] [Boche2007] [Krasniqi2008] [Schaar2005] Cognitive Radio (CR): CR intends to improve the spectrum efficiency. [Mitola2000] [Stanislav2008]

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Limitations of Layered Protocol
Layered protocols (e.g., OSI, TCP/IP) are designed for wired networks. Limitations: It does not consider the time-varying characteristics of wireless channels, so
Optimization in a layer with respective to its output might be counterproductive in the overall sense. Equivalently optimum parameters to a layer, may have different effects to other layers.

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Advantages of Cross-Layer Design
Given networks resources, CLD can improve the endto-end performance, but not the performance of a single layer.
Each layer decides its working status (not necessarily optimal), such that the overall output of system is optimized. Each layer chooses transmission strategy from equivalent ones to optimize the overall system.

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Existed Categories of CLD
Top-down method:
Idea: Lower layer performs optimization according to indication from upper layers.

Bottom-up method:
Idea: Upper layer adapts transmission strategies to perform optimization, based on CSI from lower layers.

Application layer Transport layer Network layer Data link layer

QoS Requirement

Application layer Transport layer Network layer Bottom up

Select optimal transmission strategy

Top-down

Minimize cost

Loss, bandwidth

Data link layer
Resource management

Physical layer

Physical layer

Top-down

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Bottom-up

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Integrated approach:
Idea: A new module is required to determine the optimal strategies by jointly considering all layers.

Parameter abstraction
Application layer Transport layer

Cross-Layer Optimization

Decision

Network layer

Data link layer

Parameter abstraction
Physical layer

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Methods to Solve CLD
Heuristic method
Basic idea: Search for the solution by investigating the structure of the problem Drawback: Not necessarily resulting in the optimal solution.

Optimization method
Basic idea: Formulate the problem as a convex or nonconvex optimizations problem, and get the optimal solution. Drawback:
? Cannot provide deep insight into the structure of the optimization problem with relatively high complexity

We focus on the heuristic method in our research.
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RRM Based on CLD
Application

Adaptive QoS, adaptive source coding… Adaptive congestion control… Utility function Optimization given resource constraints

resource state information

Transport

Network

Channel-aware routing,… Adaptive multi-access, opportunistic scheduling,ARQ… AMC, power, MIMO….

Resource allocation Cross layer strategy

Data link

Physical

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Typical examples about RRM based on CLD
Link-based adaptive transmissions
CLD: PHY + MAC Aim of RRM: Improve spectrum efficiency

End-to-end QoS guaranteed RRM
CLD: PHY + MAC + Transport Aim of RRM: Improve end-to-end throughput

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Link-based adaptive transmissions
System model and problem Cross-layer design combining Type-I/II/III HARQ with AMC Cross-layer design combining T-ARQ(truncated ARQ) with AMC in MIMO systems

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System Model
Transmitter Buffer ARQ Controller Feedback Channel Buffer ARQ Controller Receiver AMC Controller Nakagami-m fading channel AMC Selector Channel estimator

Problems:
How to improve performance and spectral efficiency of systems efficiently under QoS Constraints over wireless links?

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Solution I
Cross-layer design combining Type-I/II/III HARQ with AMC Cross-layer design combining T-ARQ with AMC in MIMO systems

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Adaptive Modulation and Coding
M0
M1
M2

M3

M4

M5

0

γ1

γ2

γ3

γ4

γ5



When SNR γ ∈ [γ n , γ n +1 ) , the mode n AMC scheme will be chosen. Approximate PER expression [Q. Liu 2004]
PERn ( γ ) ≈

{

1, if an exp ( ?gnγ ) , if
γ pn
an gn

0 < γ < γ pn γ ≥ γ pn

γ

: instantaneous SNR

n : AMC mode

: fitting parameters
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Wireless Mobile Communication and Transmission Lab. (WMCT)

Type-II/III HARQ
PER expressions for each ARQ transmission[L. Xu 2007]
PER0,n = a0,n exp( ? g 0,nγ ) PERNmax ,n = aNmax , n exp( ? g Nmax ,nγ )

......

PER limits (Cross-layer Information)
PER0,n PER1,n … PERN
Plink :
max

≤ Plink := P0 Nmax +1 ,n

PER limit in link layer, different traffics have different PER requirements, e.g., voice traffic PER limit is 0.01

P0 : PER limit in physical layer
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Type-II/III HARQ
Define the approximate average PER for each transmission/retransmission

PERn = an exp( ?gnγ )
=
Nmax +1

a0,n...aN
N r +1

max,n

exp?? g0,n +...+ gNmax,n γ ( Nmax +1)? ? ?
? ?

(

)

where

an =

a0, n ...a N max , n

g n = g 0, n + ... + g N max , n

(

)

( N max + 1)

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Average Packet Error Rate
PER(γ ) = ∑ n =1 Pγ ( n ) PER n
N

where P E R n =

1 Pγ

( n ) ∫γ

γ n +1
n

P E R n (γ

) p γ ( γ )d γ
( Nakagami ? m channel)

? mγ ? exp ? ? pγ (γ ) = m ? γ ? ? γ Γ (m ) m mγ Pγ ( n ) =

m ?1

∫γ

γ n +1
n

? ? mγ n ? m γ n +1 ? Γ ? m, ? ? Γ ? m, ? γ ? γ ? ? ? p γ ( γ )d γ = Γ (m )

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Average Spectral Efficiency
N 1 Se ( N max ) = ∑ Rn Pγ ( n ) N ( N max ) n =1

where

Rn = Rc log 2 M n
Rc ( N max ) =

Rinf * N N max , PER (γ )

Rcode + Rinc * N N max , PER (γ ) ? 1

( (

(

)

) )

Rinf is the number of the information bits in one packet
Rcode is the number of coded bits in one packet for the first transmission

Rinc is the number of the incremental bits transmitted for each retransmission

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Average Spectral Efficiency

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Cross-layer combining Type-I HARQ with AMC achieve higher spectral efficiency than traditional layered method [Q. Liu 2004]. Cross-layer combining Type-II, III HARQ with AMC could achieve further higher spectral efficiency. (Our research) More retransmissions, higher spectral efficiency.

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Solution II
Cross-layer design combining Type-I/II/III HARQ with AMC Cross-layer design combining T-ARQ with AMC in MIMO systems

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MIMO Parameters
Ideal condition implicates that adjacent antennas are far enough and uncorrelated. This is impractical in real communication networks. We consider correlated antennas
Alamouti space-time coding with NT=2, NR=1
ρ = exp[ ? (i ? j ) 2 ( ) 2 ] i, j = 1,.......N R NT 2 λ Nakagami-m channels: m=1(Rayleigh), m=2
k d

Bessel correlation model ---correlation coefficient
d : the distance between adjacent antennas λ: the wavelength of the carrier k =21.4 was chosen to give the same -3dB point

Performance constraint at data link layer PERlink=0.01
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Cross Layer Average Spectral Efficiency
S physical 1 S ( N max ) = = N N
1 ? PER N = 1 ? PER
Average number of transmissions
N max + 1

∑ R P ( n)
n =1 n r

N

1 /( P E R p h y = P E R lin kN m ax + 1)

Maximum number of retransmissions
[Q ,L iu 0 4 ]

Rn = Rc log 2 M n : information rate of AM-STBC where, Rc denotes the code-rate of STBC
Pr ( n ) =



rn + !

rn

p ( r ) dr

PDF of effective SNR by STBC in correlated Nakagami-m fading channel

Pr (n): the probability that AMC of mode n is chosen
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PDF of the effective SNR by STBC
p (r ) = ∑ ∑ Aij
i =1 j =1 u mpi

r j ?1 exp(?

mN T Rc r λi r

)

ith nonzero distinct eigenvalue of covariance matrix C

Γ( j )( mNiT Rc ) j
? 1 ?N

λ r

?1 Covariance matrix: = ? C ?ρ

ρ?

R NT × N R NT

= 2×2

Convariance matrix C has: * u distinct nonzero eigenvalues * the ith nonzero distinct eigenvalue denoted as λ i , and repeated pi times.

Coefficient Aij :
A ij = ( mp
i

1 ? j )! ( r λi ) mp i ? j N T Rcm

r λi ? mp i ? j × [( 1 + s ) mp i Φ r ( s )] | s = ? N T R c m r λi N T Rcm ? s mp i ? j

Characteristic function of r:

Φ r (s) =

1


i =1

u

(1 + s

r λi ) mp i N T Rc m
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Wireless Mobile Communication and Transmission Lab. (WMCT)

Spectral efficiency for different retransmission number with fixed correlation coefficient
ASE over Rayleigh fading channel (m=1) with d/λ=∞
6 Nr=0 Nr=1 Nr=2

ASE over Rayleigh channel (m=1) with d/λ=0.2
6 Nr=0 Nr=1 Nr=2

Average Spectral Efficiency (bits/symbol)
30

Average Spectral Efficiency (bits/symbol)

5

5

4

4

3

3

2

2

1

1

0

0

5

10

15 20 Average SNR(dB)

25

0

0

5

10

15 20 Average SNR(dB)

25

30

Attain better average spectral efficiency when the maximum number of retransmissions is 2.
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Spectral efficiency for different correlation coefficients (d/λ=∞, 0.2, or 0.1)
Compare the ASE over Rayleigh channel (m=1)
6 5.5 Average Spectral Efficiency (bits/symbol) 5 4.5 4 3.5 3 2.5 2 1.5 1 0.5 0 0 5 10 15 20 Average SNR(dB) 25 30 d/λ=∞ d/λ=0.2 d/λ=0.1

Compare the ASE over Nakagami-2 channel (m=2)
6 5.5 Average Spectral Efficiency (bits/symbol) 5 4.5 4 3.5 3 2.5 2 1.5 1 0.5 0 0 5 10 15 20 Average SNR(dB) 25 30 d/λ=∞ d/λ=0.2 d/λ=0.1

I: Lager correlation coefficient, lower spectral efficiency. II: The impact of correlation in Rayleigh channel is more than that in Nakagami-2 channel.
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Typical examples about RRM based on CLD
Link-based adaptive transmissions
CLD: PHY + MAC Aim of RRM: Improve spectrum efficiency

End-to-end QoS guaranteed RRM
CLD: PHY + MAC + Transport Aim of RRM: Improve end-to-end throughput

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End-to-end QoS guaranteed RRM
System and problem description Cross-layer design combining HARQ with AMC for TCP performance optimization Performance evaluation

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System description
TCP Wireless link

Wired Networks
TCP Sender Base Station TCP Receiver

End-to-End Wired-Wireless Connection

Problems:
TCP assumes that packet loss is due to congestion; In wireless networks, most packet losses are due to high BER on wireless link (noise, fading) or handoffs; If using TCP of wired networks in the wireless environment, it will surely cause significant reductions in throughput.
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Cross-Layer Solutions
The cross-layer optimization improves the TCP performance by searching the optimal PER for AMC (PHY) the maximum number of retransmission for HARQ (MAC)

( N r , P0
opt

opt

max ) = arg N ∈Ω; P ∈Ψ η ( N r , P )
0

subject to

{

r

0

p ( N r , P0 ) ≤ ρ , D ( N r , P0 ) ≤ δ .

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TCP Model
The long-term steady-state TCP segment send rate is [J. Padhye 2000]
1

λ=
where:

RTT 2bp / 3 + TOUT 3 3 p / 8 p 1 + 32 p 2

(

) (

)

b is the number of sending that are acknowledged by a
received ACK;
TOUT is the average retransmission timeout value;
RTT is the average end-to-end round-trip-time;
RTT = 2T0 + D + Twf

T0 is the delay due to the wired network; D is the total delay at the data link layer, and Twf is the feedback delay for an ACK over the wireless channel from the client to the base station.

p is the segment loss rate.
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Fixed-Point Procedure
λ
TCP Model Link Layer Model
[C. F. Chiasserini 2002] The TCP model takes the sending rate λ as output that can be fed into the link layer, and derives average delay D and segment loss rate p from the link layer. The procedure is repeated until convergence on the estimate of three parameters is reached. Then the steady-state behavior of the system can be analyzed.

p D

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Queueing Model
FIFO mode
λ

B

Nr

Queueing system operates in a First-in-first-out mode; The buffer of transmitter can store B packets; If no space in buffer, packet will be discarded; Packet loss comes from both dropped due to buffer overflow and packet failures at the date link layer after N r retransmissions .

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Queueing Model
(c
i ?1

, qi ?1 , ri ?1 )
frame

( c , q , r ) ( ci +1 , qi +1 , ri +1 )
i i i

ci = n, K n = 2

frame frame

t i ?1

Tf

ti

slot

ti +1

[X. Wang 2007]

Tf : coherence interval

qi : number of packets in the buffer

ti : starting point of the ith interval
ci : channel state

ri

: retransmission times

K n : number of slots per Tf block

Parameters derived from queueing analysis: Segment loss rate

p;
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Average delay D .
Wireless Mobile Communication and Transmission Lab. (WMCT)

TCP Throughput versus Target PER
45 40

35

Throughput η (segments/s)

No ARQ ARQ, Nr=2 ARQ, Nr=3 Type-III HARQ, Nr=2 Type-III HARQ, Nr=3

Parameter Setting: coherence interval delay due to wired network
T f = 10 ms
T0 = 50 ms

30

25

feedback delay T = 3 ms wf average SNR
γ = 10 dB
fd = 1Hz

20

15

Doppler frequency buffer size Nakagami parameter

10

B = 10 m = 1.0

5 10
-3

10

-2

10

-1

P0

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TCP Throughput versus Target PER (Cont.)

TCP throughput increases significantly when Type-III HARQ is employed to eliminate the errors from the transport layer. Even “pure” ARQ can improve the TCP throughput considerably.

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Segment Loss Rate versus Target PER
0.22 0.2 0.18 0.16

No ARQ ARQ, Nr=2 ARQ, Nr=3 Type-III HARQ, Nr=2 Type-III HARQ, Nr=3

Segment loss rate p

0.14 0.12 0.1 0.08 0.06 0.04
-3 -2 -1

10

10

10

P0

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Segment Loss Rate versus Target PER (Cont.)
Utilizing the great error-correcting capability of Type-III HARQ, the system has the lowest segment loss rate. The increment of the maximum number of retransmission could lead to the decrease of the segment loss rate.

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Conclusions
Two typical examples of RRM based on CLD are presented. RRM based on CLD could improve the system performance (spectral efficiency, end-to-end throughput). Cross-layer methods can satisfy the requirements of different services from the global perspective. How to use the cross-layer information to realize RRM is really a challenging topic.
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Future Work RRM based on CLD in cognitive, relay and cooperative communication networks.
RRM Based on CLD

合作电磁环境感知 Sensing

Cognitive+Relay/Cooperation

认知中继传输 Execution

多中继传输资源博弈 Decision
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Wireless Mobile Communication and Transmission Lab. (WMCT)

Future Work (Cont.)
Four sub-topics
Sensing: Dynamically select cooperator in sensing. Relay selection: Design new routing protocol. Fairness issue: Use game theory for RRM in multi-hop networks. RRM based on CLD: Cross-layer design to improve overall performance.
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Thanks for your attention !

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References
[Nossek2007] J. A. Nossek, “CLARA: Cross-layer Assisted Resource Allocation – Theory and Application,” invited report in the 1st IEEE international workshop on cross-layer design (IWCLD), Jinan, China, Sept. 2007. [Boche2007] H.Boche, S. Naik, M. Schubert, “Characterization of Dictatorial and Egalitarian Solutions of Wireless Resource Allocation Problems and Consequences for Cross-Layer Design,” invited report in the 1st IEEE international workshop on cross-layer design (IWCLD), Jinan, China, Sept. 2007. [Schaar2005] M. Schaar, D.Shankar “ Cross-Layer wireless multimedia transmission: Challenges, principles, and new paradigms”, IEEE Wireless Communications, Aug. 2005 [Mitola2000] J. Mitola III, “Cognitive radio: an integrated agent architecture forsoftware defined radio,” Ph.D. Thesis, KTH Royal Inst. Technology,Stockholm, Sweden, 2000.

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References (Cont.)
[Kwan2005] Kwan; R.; Leung, C.; Adaptive Modulation and Coding with Multicodes over Nakagami Fading Channels, in the Proc. of IEEE WCNC2005, vol. 2, pp. 927-932. 2005. [Liu2005] Q. Liu, S. Zhou, G. B. Giannakis, Queuing With Adaptive Modulation and Coding Over Wireless Links: Cross-Layer Analysis and Design,IEEE Trans. on Wireless Commun. vol. 4, no. 3, May 2005. [Liu2006] Q. Liu, X. Wang, G. B. Giannakis, A Cross-Layer Scheduling Algorithm With QoS Support in Wireless Networks,IEEE Trans. on VT, vol. 55, no. 3, May 2006. [Wan2007] X. Wang, Q. Liu, and G. B. Giannakis, “Analyzing and optimizing adaptive modulation and coding jointly with ARQ for QoS-guaranteed traffic,” IEEE Trans.VT, vol. 56, no. 2, pp.710–720, Mar. 2007.

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References (Cont.)
[L. Xu 2007] L. Xu, The Application of HARQ In the Cross Layer Design, MS Thesis, June 2007. [Q. Liu 2004] Q. Liu, S. Zhou, G. B. Giannakis, “Cross-layer Combining of Adaptive Modulation and Coding With Truncated ARQ Over Wireless Links”,IEEE Transactions on Wireless Communications, vol. 3, pp. 1746 – 1755, Sept. 2004. [X. Wang 2007] X. Wang, Q. Liu, and G. B. Giannakis, “Analyzing and optimizing adaptive modulation and coding jointly with ARQ for QoS-guaranteed traffic,” IEEE Trans. Veh. Tech., vol. 56, no. 2, pp.710–720 , Mar. 2007. [FCC2002] FCC Spectrum Policy Task Force, “Report of the Spectrum Efficiency Working Group,” Nov. 2002, http://www.fcc.gov/sptf/files/SEWGFinalReport_1.pdf.

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References (Cont.)
[Khan2006] S. Khan, Y. Peng, and E. Steinbach, et al., “Application-Driven CrossLayer Optimization for Video Streaming over Wireless Networks,” IEEE Communications Magazine, Jan. 2006. [Choi2006] Lai-U Choi, W. Kellerer, E. Steinbach, “On-Cross-Layer Design for Streaming Video Delivery in Multiuser Wireless Environments,” Journal on Wireless Communications and Networking, pp. 1-10, May 2006. [Palomar2006] D. P. Palomar, M. Chiang, “A Tutorial on Decomposition Methods for Network Utility Maximization,” IEEE JSAC, vol. 24, no. 8, Aug. 2006. [Brandenburger1997] A. M. Brandenburger and B. J. Nalebuff, “Co-opetition: A Revolution Mindset that Combines Competition and Cooperation – The Game Theory Strategy That’s Changing the Game of Business,” Currency, 1997.

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References (Cont.)
[C. F. Chiasserini 2002] C. F. Chiasserini and M. Meo, “A reconfigurable protocol setting to improve TCP over wireless,” IEEE Trans. Veh. Tech., vol. 51, no. 6, pp.1608 – 1620, Nov. 2002. [J. Padhye 2000] J. Padhye, V. Firoiu, D. F. Towsley, and J. F. Kurose, “Modeling TCP Reno performance: a simple model and its empirical validation,” IEEE/ACM Trans. Networking, vol. 8, no. 2, pp. 133-145, Apr. 2000. [Assaad2006] M. Assaad, and D. Zeghlache, “Cross Layer Design in HSDPA System to Reduce the TCP Effect,” IEEE JSAC, vol. 24, no. 3, March 2006.

[Tang1999] Tang, X .; Alouini, M .S .; Goldsmith, A J.; Effect of Channel Estimation Error on M-QAM BER Performance in Rayleigh Fading, IEEE Trans. Common., vol. 47, pp. 1856-1864, Dec. 1999.

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References (Cont.)
[Goldsmith1998] Goldsmith, A. J.; Chug, S; G ., Adaptive Coded Modulation for Fading Channels, IEEE Trans. On Commun., vol. 46, No. 5, May 1998. [Alouini2000] Alouini, M.S.; Goldsmith, A.J.; Adaptive modulation over Nakagami fading channels, in the Kluwer Journal on Wireless Commun., 2000, vol. 13, no.1-2, pp. 119-143. [Krasniqi2008] B. Krasniqi, “Cross Layer Issues in UMTS-LTE,” Technical Report, Vienna University of Technology, July 2008. [Li06]W. Li, H. Zhang, and T.A. Gulliver, “Capacity and Error Probability Analysis of Orthogonal Space-time Block Codes over Correlated Nakagami Fading Channels”, IEEE Trans. on Wireless Communications, vol. 5(9), pp. 2408 - 2412 Sept. 2006 [Chen03] Z. Chen, J. Yuan, B. Vucetic, and Z. Zhou, “Performance of the Alamouti scheme with transmit antenna selection,” IEEE Electron. Lett., vol. 39, pp. 1666-1668, Nov. 2003.

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References (Cont.)
[F. Shi 2008] F. Shi, D. Yuan, “Cross-Layer Performance Analysis of TCP over Wireless Link with AMC and Type-III HARQ”, the 10th International Symposium on Spread Spectrum Techniques and Applications (ISSSTA), Bologna, Italy, Aug. 2008. [Stanislav2008] F. Stanislav, H. Hiroshi, H. Mikio, “Performance Evaluation of Dynamic Spectrum Assignment and Access Technologies,” IEEE PIMRC 2008.

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Management Entity (MME) Product Category Definitions...(such as SONET/SDH or IP) layers in a single...This includes Radio Resource Control, Paging ...
The Design and Implementation of a Broadcasting Management ....unkown
Design and Implementation of a Broadcasting ... of the subscribed group is twolayered: the ...Amongst the many available database management ...
...for Mobile Ad Hoc Networks based on a Cross-layer Design p....unkown
Hoc Networks based on a Cross-layer Design p. ...Management Interference Aware Bluetooth Scatternet (...252 Scheduling algorithms for 4G wireless networks ...
A Cross-Layer Design Based on Geographic Information for ....unkown
A Cross-Layer Design Based on Geographic Information for Cooperative Wireless Networks Teck Aguilar, Mohamed Chedly Ghedira, Syue-Ju Syue, ...
A Cross-Layer Design Based on Geographic Information for ....unkown
A cross-layer design based on geographic information for cooperative wireless networks Teck Aguilar, Mohamed Chedly Ghedira, Syue-Ju Syue, Vincent Gauthier,...
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