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Frequency diversity in digital communications, focusing on channels with l-fold frequency diversity and its implications for data transmission. The concept of frequency diversity, the diversity gain, and the use of orthogonal frequency division multiplexing (ofdm) to harness frequency diversity while maintaining a reasonable data rate. The document also touches upon the limitations of frequency diversity due to the coherence bandwidth.
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In many instances, temporal diversity is either not available (in stationary scenarios) or cannot be efficiently harnessed due to the strict delay constraints of the data being commu- nicated. In these instances, and as an added source of diversity, looking to the frequency domain is a natural option.
Frequency diversity occurs in channels where the multipaths are spread out far enough, relative to the sampling period, so that multiple copies of the same transmit symbol are received over different received samples. Basically, we want a multitap ISI channel response: the L-tap wireless channel
y[m] =
`=
hx[m −] + w[m], m ≥ 1 (1)
is said to have L-fold frequency diversity. The diversity option comes about because the different channel taps h 0 ,... , hL− 1 are the result of different multipath combinations and are appropriately modeled as statistically independent. Thus the same transmit symbol (say x[m]) gets received multiple times, each over a statistically independent channel, (in this case, at times m, m + 1,... , m + L − 1).
Suppose we have just a single bit to transmit. The simplest way to do this is to transmit the appropriate symbol x = ±
E and stay silent. : i.e., we set
x[1] = ±
x[m] = 0 m > 1. (3)
At the receiver, we have L (complex) voltages that all contain the same transmit symbol immersed in multiplicative and additive noises:
y[+ 1] = hx + w[+ 1], = 0,... , L − 1. (4)
As before, we suppose coherent reception, i.e., the receiver has full knowledge (due to accurate channel tracking) of the channel coefficients h 0 ,... , hL− 1. We see that the situation is entirely
similar to that of the time diversity channel with repetition coding (as seen in the previous lecture). Then, the appropriate strategy at the receiver (as seen several times, including in the previous lecture on time diversity) is to match filter:
yMF^ def = <
`=
h∗ y[ + 1]
`=
|h`|^2
x + ˜w. (6)
Here ˜w is real Gaussian with zero mean and variance ( (^) L ∑
`=
|h`|^2
σ^2 2
Thus, the average error probability is generalizes to
Pe = E
`=
|h`|^2
Again, there is an exact expression for the unreliability level when the channel coefficients are independent Rayleigh distributed (just as in the time diversity case):
( (1 − μ) 2
k=
L − 1 + k k
1 + μ 2
)k , (9)
where μ is as in the previous lecture. Finally, we can look for a high SNR approximation; as earlier, we have:
Pe ≈
The diversity gain is now L: doubling of SNR reduces the unreliability by a factor of
1 2 L^