37 1 Vol 37 No 1 2013 1 Journal of Jiangxi Normal UniversityNatural Science Jan 2013 1000-5862201301-0037-05 MISO 郭荣新, 袁继昌 361021 2 RVQ 2 MISO 3 TN 911 7 A 0 MIMO 2 MISO 3 MIMOnetwork MIMO 3GPP LTE-A 2 CoMP MIMO 1-3 DPC 4-6 DPC X x X T X H X I N 6 N N x x 7 1 8 2 MISO 1 SLNR 1 M 2012-10-09 61201264 2011J05152 3502Z20123035 2011ZD01GO1 Full-CSI 1980- MIMO
38 2013 y 1 = 槡 P 1 1h T 1 1f 1 s 1 + 槡 P 1 2g T 1 2 interference 2f 2 s y 2 = 槡 P 2 2h T 2 2f 2 s 2 + 槡 P 2 1g T 2 1 interference 1f 1 s + n 1 1 + n 2 2 P i j i j P i j = P 0 D 0 /d i j α α P 0 D 0 d i j 6 i j D 0 P 0 8 2 2 2 f i C M 1 i i f i = 1 n i SLNR i = P i i f T i h i n i ~ CN0 1 s i i 1 s i 2 = 1 1 2 2 i = 1 2 f i 3 8-11 1 BF i 1 MISO 1 1 f i = h i i h i i 6 1 h1 1 6 3 C M 1 2 1 g 1 2 C M 1 2 ZF h i i g i j i = 1 2j = 1 2i j g T j if i 2 = CN0 1 0 f i = 1 U i = h T i ig T j iw i = MISO 2 U H i U i -1 U H i f i = w i w i 7 w i W i 1 g T j iw i = 0 7 3 3 SLNR i h T i i f i P j i f T i g j i g T j i f i + 1 8 8 SLNR P f opt i i f T i hi ih T i i f i i arg max ii = 1 2 f i C M 1 P j i f T i g j i g T j i f i + 1 9 SINR i = P i i f T i hi ih T i i f i P i j f T j g i j g T i j f j + 1 3-9 f opt P i = λ j i max g R i = log 2 1 + SINR i 4 P j i g T -1 {( j I i i i P i i ) i h T i i } MISO 10 λ max A A R = 2 R i 5
1 MISO 39 3 CDI FDD i h i i g i j B Q B G h i i g i j B Q + B G = B h i i g i j 2 F Q = f 1 f 2 f 2 B Q F G = f 1 f 2 f 2 B G M 12 2 3 h i i = arg max h槇 H i i f 2 f F Q 11 gi j = arg max g槇 H i j f 2 f F G 12 2 BF 22 h槇 i i = h i i / h i i g槇 2 i j = g i j / g i j 2 Matlab ZF SLNR SLNR 2 3 3 D 0 = 1 1 1 2 2 2 0 1 2 1 M = 2 M > 2 2 1 N r = 1 α = 3 7 1 B = 6 BF 1 2 2 SINR 1 2 2 BF 2 ZF BF SLNR SNR SNR 2 D 0 = 1 P 0 = 15 db 1 2 1 0 1 2 2 M = 2 N r = 1 α = 3 7 B = 6 B = 8 BF 4 2 2 12 2 2 2 3 3 4 1 3 2 SLNR SLNRBF SLNR
40 2013 3 B = 6 4 B = 8 5 2 1 1 2 2 1 2 2 4 1 P 0 = 5 db D 0 = 1 M = 2 N r = 2 BF BF 1 α = 3 7 B = 6 BF 2 BF BF SLNR BF SLNR BF SLNR 4 SLNR 2 P 0 = 20 db 2 SLNR SLNR 3 P 0 = 10 db2
1 MISO 41 2 2 Theory 2007101-105 SLNR SLNR 2 3Yu Wei Lan Tian Transmitter optimization for the multiantenna downlink with per-antenna power constraints J 2 BF IEEE Transactions on Signal Processing 2007 5 6 2646-2660 4Costa M Writing on dirty paper J IEEE Transactions on Information Theory 1983 393 439-411 5Weingarten H Steinberg Y Shaimai S The capacity region SLNR of the Gaussian multiple-input multiple-output broadcast channel J IEEE Transactions on Information Theory 6 2006 529 3936-3964 6Zhang Jun Chen Runhua Andrews J G et al Networked MIMO with clustered linear precoding J IEEE Transactions on Wireless Communications 2009 8 4 1910-2 MISO 3 1921 7 Nakagami-m J 2011 354 396-399 8Sadek M Tarighat A Sayed A A leakage-based precoding scheme for downlink multi-user MIMO channels J IEEE Transactions on Wireless Communications 2007 6 5 1711-1721 9Bhagavatula R Heath Jr R W Adaptive limited feedback for sumrate maximizing beamforming in cooperative multicell systems J IEEE Transactions on Signal Processing 2011 592 800-811 10Zhang Jun Andrews J G Adaptive spatial intercell interference cancellation in multicell wireless networks J 7 IEEE Journal on Selected Areas in Communications 2010 289 1455-1468 1Boccardi F Huang H Zero-forcing precoding for the MIMO broadcast channel under per-antenna power constraints C CannesIEEE 7th Workshop on Signal Processing Advances in Wireless Communications 20061-5 2Karakayali K Yates RFoschini G et al Optimum zeroforcing beamforming with per-antenna power constraints C NiceIEEE International Symposium on Information 11Shi Fengfeng Xu Wei Zhao Cunming A Limited Feedback Strategy for Cooperative Multicell MISO Systems C NanjingInternational Conference on Wireless Communications and Signal Processing 20111-5 12Santipach W Honig M Signature optimization for CDMA with limited feedback J IEEE Transactions on Information Theory 2005 5110 3475-3492 The Study of Interference Cancellation Schemes in Multi-Cell MISO Communication Systems GUO Rong-xin YUAN Ji-chang School of Information Science and Engineering Huaqiao University Xiamen Fujian 361021 China AbstractThe inter-cell interference cancellation schemes were investigated with partial channel state information The sum-rate performance of three kinds of beamforming transmission strategy i e eigen-beamforming zero-forcing beamforming and signal to leakage and noise ratio beamformingby exploiting two independent random vector quantization codebooks to quantize the desired channel and the interference channel respectively is analyzed The optimal transmission strategy choice of the base station according to user locations and average cell-edge signal to noise ratio is studied Simulation results demonstrate that when the user is noise-limited the neighbor base station will choose eigen-beamforming transmission strategy and when the user is interference-limited the neighbor base station will choose signal to leakage and noise ratio beamforming transmission strategy Key wordsinter-cell interferencebeamforminglimited feedbacksum-rate