SCIENCE CHINA Information Sciences, Volume 59 , Issue 10 : 102312(2016) https://doi.org/10.1007/s11432-016-5534-8

Transceiver designs with matrix-version water-filling architecture under mixed power constraints

More info
  • ReceivedAug 5, 2015
  • AcceptedNov 19, 2015
  • PublishedJun 12, 2016



National Natural Science Foundation of China(61421001)

111 Project of China(B14010)

National High Technology Research and Development Program of China(2014AA01A701)

China Mobile Research Institute([2014]451)



This work was supported by National Natural Science Foundation of China (Grant No. 61421001), 111 Project of China (Grant No. B14010), National High Technology Research and Development Program of China (Grant No. 2014AA01A701), and China Mobile Research Institute (Grant No. [2014]451).


[1] Telatar I E. Capacity of muti-antenna Gaussian channels. European Trans Commun, 1999, 10585-595 Google Scholar

[2] Palomar D P, Cioffi J M, Lagunas M A. Joint Tx-Rx beamforming design for multicarrier MIMO channels: a unified framework for convex optimization. IEEE Trans Signal Process, 2003, 512381-2401 CrossRef Google Scholar

[3] Scaglione A, Stoica P, Barbarossa S, et al. Optimal designs for space-time linear precoders and decoders. IEEE Trans Signal Process, 2002, 501051-1064 CrossRef Google Scholar

[4] Sampath H, Stoica P, Paulraj A. Generalized linear precoder and decoder design for MIMO channels using the weighted MMSE criterion. IEEE Trans Commun, 2001, 492198-2206 CrossRef Google Scholar

[5] Yang J, Roy S. On joint transmitter and receiver optimization for mutiple-input-mutiple-output (MIMO) transmission systems. IEEE Trans Commun, 1994, 423221-3231 CrossRef Google Scholar

[6] Yu W, Lan T. Transmitter optimization for the multi-antenna downlink with per-antenna power constraints. IEEE Trans Signal Process, 2007, 552646-2660 CrossRef Google Scholar

[7] Tolli A, Codreanu M, Juntti M. Linear multiuser MIMO transceiver design with quality of service and per-antenna power constraints. IEEE Trans Signal Process, 2008, 563049-3055 CrossRef Google Scholar

[8] Zhu H L, Wang J Z. Radio resource allocation in multiuser distributed antenna systems. IEEE J Sel Areas Commun, 2013, 312058-2066 CrossRef Google Scholar

[9] Mai V. MIMO capacity with per-antenna power constraint. IEEE Trans Commun, 2011, 591268-1274 CrossRef Google Scholar

[10] Chen X, Xu X D, Tao X F. Energy efficient power allocation in generalized distributed antenna system. IEEE Commun Lett, } 2012, 161022-1025 CrossRef Google Scholar

[11] Zhu H L, Karachontzitis S, Toumpakaris D. Low complexity resource allocation and its application to distributed antenna systems [Coordinated and Distributed MIMO]. IEEE Wirel Commun Mag, } 2010, 1744-50 Google Scholar

[12] Chen H H, Gershman A B, ShahbazPanahi S. Filter-and-forward distributed beamforming in relay networks with frequency selective fading. IEEE Trans Signal Process, } 2010, 581251-1262 CrossRef Google Scholar

[13] Luan T, Gao F, Zhang X. Joint resource scheduling for relay-assisted broadband cognitive radio networks. IEEE Trans Wirel Commun, } 2012, 113090-3100 CrossRef Google Scholar

[14] Li N, Fei Z S, Xing C W, et al. Robust low-complexity MMSE precoding algorithm for cloud radio access networks. IEEE Commun Lett, 2014, 18773-776 CrossRef Google Scholar

[15] Wang H-M, Yin Q Y, Xia X-G. Distributed beamforming for physical-layer security of two-way relay networks. IEEE Trans Signal Process, } 2012, 603532-3545 CrossRef Google Scholar

[16] Gao F F, Jiang B, Gao X-Q, et al. Superimposed training based channel estimation for OFDM modulated amplify-and-forward relay networks. IEEE Trans Commun, 2011, 592029-2039 CrossRef Google Scholar

[17] China Mobile Research Institue. C-RAN White Paper. v2.5. http://labs.chinamobile.com/cran/2014/06/16/c-ran-white-paper-3-0/. 2012. Google Scholar

[18] Boyd S, Vandenberghe L. {Convex Optimization}. Cambridge: Cambridge University Press, 2004. Google Scholar

[19] Palomar D P, Fonollosa J R. Practical algorithms for a family of waterfilling solutions. IEEE Trans Signal Process, 2005, 53686-695 CrossRef Google Scholar

[20] Hansen P C. Rank-deficient and discrete ill-posed problems: numerical aspects of linear inversion. In: SIAM Monographs on Mathematical Modeling and Computation. Philadelphia: Society for Industrial and Applied Mathematics, 1998. Google Scholar

[21] Xing C W, Li W Z, Ma S D, et al. A matrix field weighted mean-square-error model for MIMO transceiver design. IEEE Commun Lett, 2013, 171652-1655 CrossRef Google Scholar

[22] Zhang Z S, Long K P, Wang J. Self-organization paradigms and optimization approaches for cognitive radio technologies: a survey. IEEE Wirel Commun, } 2013, 2036-42 Google Scholar

[23] Zhu F, Gao F, Yao M, et al. Joint information- and jamming-beamforming for physical layer security with full duplex base station. IEEE Trans Signal Process, } 2014, 626391-6401 CrossRef Google Scholar

[24] Zhang Z, Long K, Wang J, et al. On swarm intelligence inspired self-organized networking: its bionic mechanisms, designing principles and optimization approaches. IEEE Commun Surv Tut, } 2014, 16513-537 CrossRef Google Scholar

[25] Liu P, Gazor S, Kim I M. A practical differential receiver for amplify-and-forward relaying. IEEE Wirel Commun Lett, 2014, 3349-352 CrossRef Google Scholar

[26] Liu P, Kim I M, Gazor S. Maximum-likelihood detector for differential amplify-and-forward cooperative networks. IEEE Trans Veh Tech, } 2013, 624097-4104 CrossRef Google Scholar

[27] Liu P, Gazor S, Kim I M, et al. Noncoherent amplify-and-forward cooperative networks: robust detection and performance analysis. IEEE Trans Commun, } 2013, 613644-3659 CrossRef Google Scholar

[28] Xing C W, Ma S D, Fei Z S, et al. A Generalt robust linear transceiver design for multi-hop amplify-and-forward MIMO relaying systems. IEEE Trans Signal Process, } 2013, 611196-1209 CrossRef Google Scholar

[29] Wiesel A, Eldar Y C, Shamai S. Zero-forcing precoding and generalized inverses. IEEE Trans Signal Process, 2008, 564409-4418 CrossRef Google Scholar

[30] Grant M, Boyd S. CVX: Matlab Software for Disciplined Convex Programming. Version 2.0 beta. http://cvxr.com/ cvx/. Google Scholar


Contact and support