mohatta2015.pdf
signal processing from power amplifier operation control point of view
signal processing from power amplifier operation control point of view
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94 LINEAR EQUALIZATION<br />
4.6 THE LITERATURE<br />
A survey of early work on linear equalization can be found in [Luc73, Bel79]. Early<br />
work on LE for cochannel interference suppression can be found in [Geo65].<br />
According to [Mon84], LE with multiple receive antennas is considered as early<br />
as [Bra70j. In [Bal92], an MF front end is used to collapse the multiple streams<br />
of data into one (symbol-level equalization). Cochannel interference can be suppressed<br />
by modeling it as spatially colored noise [Win84, Cla94]. To avoid temporal<br />
processing (multiple processing delays), multiple antennas can be used to suppress<br />
ISI due to dispersion (as well as cochannel interference) [Won96]. A mix of temporal<br />
and spatial processing to suppress ISI from dispersion is also possible [Fuj99].<br />
Different forms of interference suppression result, depending on what aspects of the<br />
interference are known or estimated (amplitude, channel response, symbol values)<br />
[Aff02, Han04].<br />
As for different criteria, development of minimum distortion linear equalization<br />
is provided in [Pro89]. Work on minimum BER linear equalization can be found<br />
in [WanOO]. Block linear equalization for TDM is considered in [Cro92] and is<br />
extended to include cochannel interference suppression in [Gin99].<br />
When the number of processing delays is limited, different strategies can be<br />
used to select the delays. Such strategies apply to both LE and the forward filter<br />
of DFE, so literature on both is discussed here. One strategy is to find a set of<br />
delays that minimizes MSE [Rag93b, LeeOl] or maximizes SNR, (or an approximation<br />
to it [Ari97] (DFE)). An order-recursive approach can be used, in which<br />
processing delays are added one at a time to maximize SNR, or an approximation to<br />
it [Kha05, Zhi05] (LE), [Sui06, Kut07] (LE, DFE). Another approach is to find the<br />
locations that have the largest weight magnitudes [Bun89] (DFE) or are expected<br />
to have the largest weight magnitudes [Lee04] (LE, DFE). Another is a mirroring<br />
approach [Kut05, Ful09], which can be related to approximate inverse channel filtering<br />
[Ful09]. This approach is similar to the idea of placing fingers where copies<br />
of interfering symbols are present [Has02, Sou]. A matching pursuit-based strategy<br />
is proposed in [Zhi05|. Strategies for addressing dispersive cochannel interference<br />
are discussed in [Ari99].<br />
Sometimes the cochannel interference can be better modeled as noncircular (improper)<br />
noise. For example, BPSK interference occupies only one dimension in<br />
the complex plane. When this occurs, there are two, equivalent approaches for<br />
formulating the linear equalization problem. One is linear conjugate linear (LCL)<br />
filtering [Bro69], also known as widely linear filtering [Pic95], in which the equalizer<br />
processes both the received signal and its conjugate. The other is to break apart the<br />
complex received signal into its real and imaginary components [Bro69]. Such filtering<br />
has been applied to BPSK cochannel interference [Yoo97] and GMSK cochannel<br />
interference in GSM [Ger03, Mey06]. In this latter context it is sometimes called<br />
single antenna interference cancellation (SAIC) because it allows interference suppression<br />
similar to that obtained with two receive antennas but without the need<br />
for a second antenna. Such filtering can also be applied to CDMA systems employing<br />
BPSK [BuzOl], including early versions of the US CDMA (IS-95) standard that<br />
employ BPSK with QPSK spreading [Bot03b].