In addition, when all users' SNRs and temporal correlations are also assumed to be the same, the optimal MMSE beamforming vector in (16) is simplified to similar expression as derived in [14 16] as w k, m ⋆ = M σ ̄ e + M ρ ̄ I M + ∑ i = 1 M h i,m τ i,m h i,m τ i,m ∗ - 1 h k, m τ k, m, where ρ ̄ and σ ̄ e are the same average SNR and channel error of users.
Two hypotheses were proposed prior to the study: The error of the technique's result is proportional to the error of user drawn arrows.
The left panel shows the Cumulative Density Function (CDF) of the prediction error of user locations when using only the data of disclosing alters.
For the given channel estimate at the BS, the channel realization is (mathbf {h}_{k}=widehat {mathbf {h}}_{k}+widetilde {mathbf {h}}_{k} ~text {and}~ forall kin {1,2}), where (widetilde {mathbf {h}}_{k}) is the estimation error of user-k.
For the given channel estimate at the BS, the channel realization is (mathbf {h}_{k}=widehat {mathbf {h}}_{k}+widetilde {mathbf {h}}_{k},forall kin {1,2,3}), where (widetilde {mathbf {h}}_{k}) is the estimated error of user-k.
By Theorem 1, it implies that the mean quantization errors of all users on each subcarrier n are identical, v k, n = v k', n.
Figure 8 Average probability of error for users adopting De Bruijn spreading codes of span 6, compared to Gold sequences in the uplink section, and to OVSF codes in the downlink section, in the outdoor test environment.
Let ({hat {mathbf {h}}_{k}}) and e k denote the estimated channel response vector and the error vector of user k, respectively.
where the interference cancellation is ideal, as the error probability of user 1 is zero, provided that its information rate does not exceed C1.
Γ k is the SNR gap due to the limited number of coding and modulation schemes and is related to the bit error rate of user k (B E R k ), through equation (Gamma _{k}=-frac {ln (5BER_{k})}{1.5BER_{k}.
