Sentence examples for matrix of interference from inspiring English sources

Assuming the interference symbols have Alamouti's STBC structure, the effective matrix of interference H i can be written as H i = H 1, i H 2, i T, (36).

In this case, owing to the data exchange between adjacent BSs, the covariance matrix of interference plus noise at BS 1 can be written as R I ( k ) = H 11 H 11 H + Σ - ∑ i = 1 k h 11, i h 11, i H - ∑ j = 0 k - 1 Ψ j, (22).

In this equation, Rnn,k stands for the M × M spatial covariance matrix of interference plus noise, and it is expressed by R nn, k = E ∑ u = 1 U h z, k, u z k, u + n k ∑ u = 1 U h z, k, u z k, u + n k H (6). Considering the decorrelation between interferer signals and noise terms, we have R nn, k = ∑ u = 1 U E h z, k, u * h z, k, u T + σ n 2 I M (7).

The noise is assumed with double-sided spectral density σ 2 = N 0 2 W/Hz, I is the identity matrix, Σ models the covariance matrix of interferences, and δ t n, t m stands for the Kronecker delta.

The main problem, in the estimation of the optimum combiner filter, resides in the estimation of the covariance matrix of the interference plus noise in addition to the estimation of the useful user propagation channel.

where ({{mathbf {S}}_{k}} = hat {mathbf {Lambda }}_{k}^{- 2} + lambda cdot {hat {mathbf {V}}^{T}}{{mathbf {h}}_{p}}{mathbf {h}}_{p}^{T}hat {mathbf {V}}) is the correlation matrix of the interference plus noise.

With delayed CSIT, denote B k [ n ] = H k [ n ] ∑ i ≠ k T i ( D ) [ n ] s i [ n ] = E k [ n ] ∑ i ≠ k T i ( D ) [ n ] s i [ n ], then A k [ n ] = B k [ n ] B k H [ n ] and the covariance matrix of the interference plus noise is then R k [ n ] = P t N S A k [ n ] + N 0 W I [ n ]. (25).

represents the covariance matrix of the interference (both intracell and intercell) plus noise, Σ = H 10 H 10 H + H 12 H 12 H + σ 2 I represents the covariance matrix of the overall intercell interference plus noise, while h11,1 is the first column of H11, as seen in (7).

Besides, most of these proposed adaptive algorithms are based on the covariance matrix of the interference.

The covariance matrix of the interference term can be calculated as (32).

Defining, we can rewrite the covariance matrix of the interference as (21).