Low complexity multi-rate IF sampling receivers using CIC filters and polynomial interpolat

2 System description
We consider multi-rate burst transmission where the symbol rate during a burst is constant, but can change from one burst to the next. We denote the signal after RF to IF downconversion by
rate radio receiver with IF sampling. Timing cor- interpolator: this allows us to keep the matched filter
rection and sample rate conversion are performed by taps independent of the symbol rate, thus signific-
Abstract
and timing correction can be performed by a polyno-
mial interpolator (IP) [1]. To reduce receiver com-
This contribution deals with a fully digital multi- plexity, matched filtering (MF) is performed after the
In this contribution we consider decimating cascaded integrator-comb (CIC) filters [5] to perform anti-aliasing. We evaluate these filters in terms of bit error rate (BER) performance and computational complexity. Several side-effects of CIC filters are discussed and solutions suggested. We show that by careful selection of the CIC filter parameters low BER degradations (below 0 1 dB at a BER of 10 3) are achievable for all considered symbol rates.
ues from an interval ´Tmin Tmaxµ. Consequently, the Polynomial interpolators are time-varying filters bandwidth B of the transmit pulse is in a corres- which are able to correct arbitrary delays and per-
ate the computational complexity and BER perform- [2] at the output of the interpolator. Although inter-
ance when efficient cascaded integrator-comb (CIC) polators have good anti-imaging properties, they are
tion in complexity may be achieved. Low degrad- log in-phase and quadrature branches, the IF signal
ations are attainable when the receiver design para- (the signal after RF to IF conversion) is sampled dir-
the carrier phase (θ) and the IF ( fIF ) are assumed to ture [6].
be known at the receiver.
Decimating CIC filters are low-complexity decim-
After filtering r ´tµ by a fixed analog AAF, this sig- ation filters with good anti-aliasing properties. They
nal is converted to the digital domain by the (ideal) are generally used in form (B) in Fig. 2: a CIC
analog-to-digital converter (ADC) as illustrated in decimation filter of order L with decimation factor
a polynomial interpolator. By performing interpol- antly reducing the overall complexity of the receiver.
ation prior to matched filtering a significant reduc- Furthermore, to eliminate the need for identical ana-
¾ the block diagram in Fig. 1. The resulting samples at R (R L Æ ) consists of L integrators followed by
be overcome and how CIC parameters may be selec- due to aliasing is minimized [4] or filter the signal
ted to provide acceptable BER degradations for all by a digital anti-aliasing filter (AAF) prior to inter-
ponding interval ´Bmin Bmaxµ. As we are not dealing form arbitrary sample rate conversion. Moreover, with estimation matters, the propagation delay (τ), they can be implemented in an efficient Farrow struc-
symbol rates.
polation. Here we investigate the second solution by
employing an efficient AAF which is independent of
1 Introduction
the symbol rate.
In digital packet-based multi-rate bandpass communication, the symbol rate can vary from one packet to the next. Since it is impractical to let the sampling clock frequency depend on the symbol rate, we assume a fixed-rate sampling clock. Consequently, the signal, sampled at a rate 1 Ts, must be resampled a rate which is a fixed multiple (N) of the variable symbol rate 1 T . This operation is known as sample rate conversion (SRC). As packets may arrive with unknown inter-arrival times, timing synchronization needs to be performed. Both sample rate conversion
responding symbol rate 1 T . The delay (τ) can vary
from packet to packet but is assumed constant within 2.1 CIC filters and interpolation
a packet. The symbol interval, T , can take on val-
Á × ÒÐ
analog AAF
ÖØ
½ Ì×
ADC
Á
Á ØÓ ቤተ መጻሕፍቲ ባይዱÓÒÚ Ö× ÓÒ
ÖØ
ÆÌ
synchronizer
Á ´Ê ĵ
fixed
N
Ò
MF
interpolator
Figure 1: multi-rate receiver with IF-sampling. aˆn are the detected soft symbols
Figure 2: description of CIC filters
with power spectral density equal to N0 2 and sT ´tµ is the transmitted linearly modulated signal with cor- changes according to the symbol rate.
Low complexity multi-rate IF sampling receivers using CIC filters and polynomial interpolation
Henk Wymeersch and Marc Moeneclaey Digital Communications Research Group Dept. of Telecommunications and Information Processing Ghent University, Sint-Pietersnieuwstraat 41, 9000 GENT, BELGIUM E-mail: {hwymeers,mm}@telin.ugent.be
Þ½
=I
Á ´Ê ĵ
L
L
(A)
I I I C(R) C(R) C(R) R
Ê
Þ
L
L
= C(R) (B)
III
R C(1) C(1) C(1)
r ´tµ ℜ sT ´t τµ e j2π fIFt e jθ · n ´tµ (1)
where n ´tµ is real additive gaussian noise (AWGN)
filters are employed to perform anti-aliasing. We poor anti-aliasing filters [3]. To overcome this, we
show how some of the side-effects of CIC filters may may either limit the design space so that degradation
meters are carefully chosen. If this is not possible, ectly. When sampling an IF signal, high-frequency
digital anti-aliasing filters are required. We investig- (HF) components in the signal may cause aliasing