"CR in MIMO"
Batch no:A14 Under the guidance of Asst.Prof. PRASHANTI(M.Tech) To compute optimal secrecy rate in MIMO channel which is a non-convex max-min problem Solution: Cognitive Radio(CR) communication which is in convex form CR MISO Transmission Interference Temperature Secrecy MISO Transmission Relationship between secrecy rate and CR Spectrum sharing capacity Multi-antenna secrecy receiver Multi-antenna eavesdropper receiver RELATIONSHIP BETWEEN SYSTEM MODEL SECRECY RATE MULTI-ANTENNA AND PROBLEM AND CR SECRECY FORMULATION SPECTRUM RECEIVER SHARING CAPACITY Lower Bound Upper Bound NUMERICAL CALCULATION MISO- 2 SA.E , MISO- 1-SA.E, MISO- 1 MA.E SECRECY EAVESDROPPER RECEIVER SECRECY TRANSMITTER PRIMARY SECONDARY RECEIVER RECEIVER SECONDARY USER PRIMARY TRANSMITTER TRANSMITTER PB- Secrecy rate Maximisation problem The CR spectrum sharing capacity problem can be formulated as P-SVD(partial singular value decomposition) Lagrangian Algorithm Military purpose Secrecy communication MATLAB 7.9 In this project quantified the relationship between the multi antenna CR transmission problem and the multi antenna secrecy transmission problem. By exploiting this relationship, we have transformed the non-convex secrecy rate computation problem into a quasi-convex optimization problem for the MISO case, and developed various algorithms to obtain the maximum achievable secrecy rate 1. Y. Liang, A. Somekh-Baruch, H. V. Poor, S. Shamai (Shitz), and S. Verdu,“Cognitive interference channels with confidential messages," in Proc.Annu. Allerton Conf. Commun., Control, Comput., Monticello, IL, USA,Sep. 2007 2.Y. Liang, G. Kramer, H. V. Poor, and S. Shamai (Shitz), “Compoundwire-tap channels," in Proc. Annu. Allerton Conf. Commun., Control, andComputing, Monticello, IL, USA, Sep. 2007. 3.Convex optimisation problem by Chakravarthi Vasu 4.www.rfcafe.com