Small-Scale Fading Prof. Michael Tsai 2016/04/15.

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Presentation transcript:

Small-Scale Fading Prof. Michael Tsai 2016/04/15

Multipath Propagation RX just sums up all Multi Path Component (MPC).

Multipath Channel Impulse Response An example of the time-varying discrete-time impulse response for a multipath radio channel Excess delay: the delay with respect to the first arriving signal (𝜏) hb(t,) t Maximum excess delay: the delay of latest arriving signal Summed signal of all multipath components arriving at 𝜏 𝑖 ~ 𝜏 𝑖+1 . The channel impulse response when 𝑡= 𝑡 0 (what you receive at the receiver when you send an impulse at time 𝑡 0 ) t0 0 1 2 3 4 5 6 (t0) 𝜏 0 =0, and represents the time the first signal arrives at the receiver.

Time-Variant Multipath Channel Impulse Response Because the transmitter, the receiver, or the reflectors are moving, the impulse response is time-variant. hb(t,) t t3 (t3) t2 (t2) (t1) t1 t0 0 1 3 2 4 5 6 (t0)

Multipath Channel Impulse Response The channels impulse response is given by: If assumed time-invariant (over a small-scale time or distance): Summation over all MPC Additional phase change due to reflections Amplitude change (mainly path loss) Phase change due to different arriving time

Two main aspects of the wireless channel hb(t,) Following this axis, we study how fast the channel changes over time. (related to the moving speed of the TX, the RX, and the reflectors) t t3 (t3) t2 (t2) (t1) t1 t0 0 1 3 2 4 5 6 (t0) Following this axis, we study how “spread-out” the impulse response are. (related to the physical layout of the TX, the RX, and the reflectors at a single time point)

Two main aspects of the wireless channel hb(t,) t t3 (t3) t2 (t2) (t1) t1 t0 0 1 3 2 4 5 6 (t0) Following this axis, we study how “spread-out” the impulse response are. (related to the physical layout of the TX, the RX, and the reflectors at a single time point)

Power delay profile To predict hb() a probing pulse p(t) is sent s.t. Therefore, for small-scale channel modeling, POWER DELAY PROFILE is found by computing the spatial average of |hB(t;)|2 over a local area. 𝑝 𝑡 ≈𝛿(𝑡−𝜏) k relates the transmitted power in the probing pulse p(t) to the total power received in a multipath delay profile. TX RX 𝑝(𝑡) 𝑃 𝑡;𝜏 ≈𝑘 ℎ 𝑏 𝑡;𝜏 2 Average over several measurements in a local area

Example: power delay profile From a 900 MHz cellular system in San Francisco

Example: power delay profile Inside a grocery store at 4 GHz

Time dispersion parameters Power delay profile is a good representation of the average “geometry” of the transmitter, the receiver, and the reflectors. To quantify “how spread-out” the arriving signals are, we use time dispersion parameters: Maximum excess delay: the excess delay of the latest arriving MPC Mean excess delay: the “mean” excess delay of all arriving MPC RMS delay spread: the “standard deviation” of the excess delay of all arriving MPC Already talked about this

Time dispersion parameters Mean Excess Delay RMS Delay Spread First moment of the power delay profile Square root of the second central moment of the power delay profile Second moment of the power delay profile

Time dispersion parameters Maximum Excess Delay: Original version: the excess delay of the latest arriving MPC In practice: the latest arriving could be smaller than the noise No way to be aware of the “latest” Maximum Excess Delay (practical version): The time delay during which multipath energy falls to X dB below the maximum. This X dB threshold could affect the values of the time- dispersion parameters Used to differentiate the noise and the MPC Too low: noise is considered to be the MPC Too high: Some MPC is not detected

Example: Time dispersion parameters

Coherence Bandwidth Coherence bandwidth is a statistical measure of the range of frequencies over which the channel can be considered “flat”  a channel passes all spectral components with approximately equal gain and linear phase. r(t) = h(t) * s(t) R(f) = H(f) . S(f)

Coherence Bandwidth Bandwidth over which Frequency Correlation function is above 0.9 Bandwidth over which Frequency Correlation function is above 0.5 Those two are approximations derived from empirical results.

Typical RMS delay spread values

Signal Bandwidth & Coherence Bandwidth Transmitted Signal 𝑇 𝑠 : symbol period 𝐵 𝑠 : signal bandwidth 𝑇 𝑠 ≈ 1 𝐵 𝑠 f t 𝐵 𝑠 𝑇 𝑠 𝑃(𝑡;𝜏) 𝐵 𝑐 𝜎 𝜏 t0 0 1 2 3 4 5 6

Frequency-selective fading channel 𝑇 𝑠 < 𝜎 𝜏 𝐵 𝑠 > 𝐵 𝑐 𝐵 𝑠 TX signal f t 𝑇 𝑠 × ∗ 𝑃(𝑡;𝜏) 𝜎 𝜏 𝐵 𝑐 Channel t0 0 1 2 3 4 5 6 = = 𝑇 𝑠 These will become inter-symbol interference! RX signal f

Flat fading channel 𝑇 𝑠 > 𝜎 𝜏 𝐵 𝑠 < 𝐵 𝑐 𝑃(𝑡;𝜏) 0 1 2 3 4 5 TX signal f 𝐵 𝑠 t 𝑇 𝑠 × ∗ 𝑃(𝑡;𝜏) 𝜎 𝜏 𝐵 𝑐 Channel t0 0 1 2 3 4 5 6 = = No significant ISI 𝑇 𝑠 RX signal f

Equalizer 101 An equalizer is usually used in a frequency-selective fading channel When the coherence bandwidth is low, but we need to use high data rate (high signal bandwidth) Channel is unknown and time-variant Step 1: TX sends a known signal to the receiver Step 2: the RX uses the TX signal and RX signal to estimate the channel Step 3: TX sends the real data (unknown to the receiver) Step 4: the RX uses the estimated channel to process the RX signal Step 5: once the channel becomes significantly different from the estimated one, return to step 1. Y=HX

Example P() Would this channel be suitable for 0 1 2 3 4 5 -30dB -20dB -10dB 0dB  P() Would this channel be suitable for AMPS or GSM without the use of an equalizer?

Example Therefore: Since BC > 30KHz, AMPS would work without an equalizer. GSM requires 200 KHz BW > BC  An equalizer would be needed.