Prerequisites & Notation

Before You Begin

This chapter builds directly on Chapter 1's channel hardening and favorable propagation analysis, but now asks: what does the actual channel matrix look like? Before proceeding, make sure you are comfortable with the following.

  • MIMO channel model: y=Hx+w\mathbf{y} = \mathbf{H}\mathbf{x} + \mathbf{w}, dimensions, role of channel matrix(Review mimo/ch01)

    Self-check: Can you write the received signal model for Nr×NtN_r \times N_t MIMO and identify each term?

  • Complex Gaussian random vectors: CN(μ,C)\mathcal{CN}(\boldsymbol{\mu}, \mathbf{C}) distribution, density, whitening(Review fsp/ch08)

    Self-check: What is the covariance matrix of Ax\mathbf{Ax} when xCN(0,C)\mathbf{x} \sim \mathcal{CN}(\mathbf{0}, \mathbf{C})?

  • Array steering vector for a ULA: a(θ)=[1,ejψ,,ej(N1)ψ]T\mathbf{a}(\theta) = [1, e^{j\psi}, \ldots, e^{j(N-1)\psi}]^T, ψ=πsinθ\psi = \pi \sin\theta(Review telecom/ch07)

    Self-check: Why does the steering vector depend on sinθ\sin\theta and not θ\theta directly?

  • Propagation basics: path loss, delay spread στ\sigma_\tau, coherence bandwidth BcB_c, coherence time TcT_c(Review telecom/ch05)

    Self-check: How is BcB_c related to στ\sigma_\tau?

  • Eigenvalue decomposition and positive semidefinite matrices(Review telecom/ch01)

    Self-check: If A0\mathbf{A} \succeq 0, what can you say about its eigenvalues?

  • Basic understanding of channel hardening and favorable propagation (Chapter 1 of this book)(Review mimo/ch01)

    Self-check: Under what channel model do channel hardening and favorable propagation hold exactly?

Notation for This Chapter

Symbols introduced or specialized in this chapter. Global conventions are in NGlobal Notation Table. The ntn\\ntn{} token enables per-user symbol customization.

SymbolMeaningIntroduced
HCNr×Nt\mathbf{H} \in \mathbb{C}^{N_r \times N_t}MIMO channel matrix (NrN_r receive × NtN_t transmit)s01
RtCNt×Nt\mathbf{R}_t \in \mathbb{C}^{N_t \times N_t}Transmit-side spatial covariance matrixs02
RrCNr×Nr\mathbf{R}_r \in \mathbb{C}^{N_r \times N_r}Receive-side spatial covariance matrixs02
Δθ\Delta\thetaAngular spread (half-angle) at base stations02
θ0\theta_0Mean angle of departure / arrivals02
GCNr×Nt\mathbf{G} \in \mathbb{C}^{N_r \times N_t}i.i.d. CN(0,1)\mathcal{CN}(0,1) random matrix (fast-fading component)s01
UCN×N\mathbf{U} \in \mathbb{C}^{N \times N}Unitary DFT matrix for virtual channel transformations03
H~=UrHHUt\tilde{\mathbf{H}} = \mathbf{U}_r^H \mathbf{H} \mathbf{U}_tVirtual (angular-domain) channel matrixs03
κ\kappaRicean KK-factor (ratio of LOS to diffuse power)s01
ddInter-element spacing (typically λ/2\lambda/2)s01
LLNumber of propagation paths (clusters)s02
α\alpha_\ellComplex gain of path \ells02
ϕ,ψ\phi_\ell, \psi_\ellAngle of departure and angle of arrival of path \ells02
WWCNt×Nt\mathbf{W}_W \in \mathbb{C}^{N_t \times N_t}Weichselberger coupling matrix (elementwise power in angle-angle domain)s02