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    Asymptotic distributions of the signal-to-interference ratios of LMMSE detection in multiuser communications

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    Let sk=1N(v1k,...,vNk)T,{\mathbf{s}}_k=\frac{1}{\sqrt{N}}(v_{1k},...,v_{Nk})^T, k=1,...,Kk=1,...,K, where {vik,i,k\{v_{ik},i,k =1,...}=1,...\} are independent and identically distributed random variables with Ev11=0Ev_{11}=0 and Ev112=1Ev_{11}^2=1. Let Sk=(s1,...,sk1,{\mathbf{S}}_k=({\mathbf{s}}_1,...,{\mathbf{s}}_{k-1}, sk+1,...,sK){\mathbf{s}}_{k+1},...,{\mathbf{s}}_K), Pk=diag(p1,...,{\mathbf{P}}_k=\operatorname {diag}(p_1,..., pk1,pk+1,...,pK)p_{k-1},p_{k+1},...,p_K) and \beta_k=p_k{\mathbf{s}}_k^T({\mathb f{S}}_k{\mathbf{P}}_k{\mathbf{S}}_k^T+\sigma^2{\mathbf{I}})^{-1}{\math bf{s}}_k, where pk0p_k\geq 0 and the βk\beta_k is referred to as the signal-to-interference ratio (SIR) of user kk with linear minimum mean-square error (LMMSE) detection in wireless communications. The joint distribution of the SIRs for a finite number of users and the empirical distribution of all users' SIRs are both investigated in this paper when KK and NN tend to infinity with the limit of their ratio being positive constant. Moreover, the sum of the SIRs of all users, after subtracting a proper value, is shown to have a Gaussian limit.Comment: Published at http://dx.doi.org/10.1214/105051606000000718 in the Annals of Applied Probability (http://www.imstat.org/aap/) by the Institute of Mathematical Statistics (http://www.imstat.org
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