Research Laboratories, NTT DoCoMo, Inc., 3-5 Hikarinooka, Yokosuka, Kanagawa 239-8536, Japan
Abstract
In the future, there will be a growing need for more
flexible but efficient utilization of radio resources. Increased flexibility
in radio transmission, however, yields a higher likelihood
of interference owing to limited coordination among users. In this
paper, we address the problem of flexible spectrum sharing where
a wideband single carrier modulated signal is spectrally overlapped
by unknown narrowband interference (NBI) and where a
cyclic Wiener filter is utilized for nonparametric NBI suppression
at the receiver. The pulse shape design for the wideband signal is
investigated to improve the NBI suppression capability of cyclic
Wiener filtering. Specifically, two pulse shaping schemes, which
outperform existing raised cosine pulse shaping schemes even
for the same amount of excess bandwidth, are proposed. Based
on computer simulation, the interference suppression capability
of cyclic Wiener filtering is evaluated for both the proposed
and existing pulse shaping schemes under several interference
conditions and over both AWGN and Rayleigh fading channels.
1. Introduction
In future wireless systems, there is a need to
support the explosive growth in number of users, be they persons or machines,
and the ever-increasing diversity in wireless applications and user
requirements. Nevertheless, one of the most challenging issues is the need to
maximize the utilization of scarce radio resources. In recent years, as a
solution towards a more efficient, yet flexible usage of spectrum resources,
opportunistic overlay sharing of underutilized, already assigned spectrum has
been under consideration [1, 2]. Design flexibility in radio, however, entails
several challenging technical problems because of the eventual interference
owing to limited coordination between multiple users of possibly heterogeneous
transmission characteristics, for example, symbol rate, symbol timing, carrier
frequency, and modulation scheme. Thus, with the aim of achieving a higher
degree of flexibility in spectrum usage, the development of non-parametric
interference suppression/avoidance techniques to deal with heterogeneous
unknown in-band interference is regarded as a crucial issue. In previous
studies, interference suppression/avoidance techniques for orthogonal frequency
division multiplexing- (OFDM-) based systems were investigated [3, 4]. In this
paper, a spectrum sharing scenario where a wideband single carrier modulated
signal is jammed by unknown NBI is investigated and a cyclic Wiener (CW) filter
is utilized to take advantage of the property of cyclostationarity for
nonparametric NBI suppression.
A signal is said to exhibit cyclostationarity if its
cyclic autocorrelation function is nonzero for a nonzero cycle frequency.
Single carrier modulated signals are known to exhibit cyclostationarity and so
are said to be cyclostationary [5, 6]. Cylostationarity-exploiting signal
processing algorithms are known to outperform classical algorithms, that is,
algorithms that have been designed assuming a stationary model for all the
signals involved in the reception problem. The utilization of cyclostationarity
in signal processing has been studied from several aspects, for example, blind
channel estimation, equalization, and direction estimation in adaptive array
antennas [7–10]. For nonparametric interference suppression, early studies
and proposals on utilizing cyclostationarity using CW filtering were
established in [6, 11, 12]. Compared to classical Wiener filters optimized against
only the presence of additive white Gaussian noise (AWGN), CW filters are shown
to be able to better suppress cochannel interference [6, 13–16]. In [13],
for example, the CW filter is shown to be effective in suppressing NBI in CDMA
systems, where the cyclostationarity of the NBI is utilized after estimating
its corresponding cycle frequencies. Nevertheless, in a flexible spectrum usage
environment, with limited coordination it is not always possible to rely on the
cyclostationarity property of the NBI, for example, the case when the NBI does
not exhibit sufficient cyclostationarity to be utilized. Other papers that
perform blind source separation (BSS) based on cyclostationarity also include
[17, 18]. However, interference suppression in these papers utilizes spatial
filtering by assuming multiple antennas at the receiver. In this paper, we
focus mainly on the exploitation of the spectral structure owing to the
cyclostationarity property of the wideband signal. The NBI is assumed
stationary and the exploitation of the spatial structure by multiple antennas
at the receiver is left as optional.
The interference suppression capability of a CW filter
is proportional to the amount of cyclostationarity available. For a single
carrier modulated signal, the amount of cyclostationarity is strongly related
to the spectral structure of the signal, represented by the cyclic nature of
its second-order statistics, which itself is related to the pulse shaping
filter used for limiting its occupied spectrum. In the context of crosstalk
suppression, a near-optimal solution for transmit pulse shaping is derived to
maximize the usage of cyclostationarity [19, 20]. Unfortunately, this solution,
besides being computationally intensive, is impractical in our scenario as it
is dependent on the channel impulse response of NBI and also the
signal-to-noise ratio (SNR) value. On the other hand, other existing raised
cosine pulse shaping schemes are designed to satisfy the Nyquist criterion of
zero intersymbol interference (ISI) to reduce self-interference; however, they
do not take the existence of external interference into consideration and they
are widely used for excess bandwidths of less than 100
, that is, a roll-off factor of less than 1.0. To
improve the CW capability to suppress the external in-band interference, a
larger amount of cyclostationarity needs to be induced by expanding the excess
bandwidth of the existing pulse shaping schemes. For this purpose, raised
cosine pulses derived for excess bandwidths beyond 100
can be utilized
[21, 22]. However, it is not clear to what extent the interference suppression
capability of CW filtering can be enhanced using such pulse shaping.
1.1. Contributions
The objective
of this work is to clarify the impact of pulse shaping design on the
interference suppression capability of CW filtering. Specifically, we propose
for a wideband signal, for both the cases of unknown and known carrier
frequency offsets (CFOs), two new pulse shaping schemes that outperform
existing raised cosine pulse shaping schemes even for the same amount of excess
bandwidth. Based on computer simulation, the performance of CW filtering is
evaluated under several interference conditions and over both AWGN and Rayleigh
fading channels. With regard to the impact of pulse shaping on the interference
suppression capability of CW filtering, simulation results reveal that there is
no advantage derived from increasing the excess bandwidth of existing pulse
shaping for the case of NBI with a large CFO, that is, NBI lying outside the
Nyquist bandwidth of the wideband signal. Also, the results show that for the
case of NBI with a small unknown or known CFO, the proposed pulse shaping
schemes, compared to existing pulse shaping schemes, yield (1) substantially
improved quality of extraction for the wideband signal; and (2) less
interference from the wideband signal-to-narrowband signal.
The remainder of this paper is structured as follows.
Section 2 introduces the fundamentals of cyclostationarity and CW filtering.
Section 3 presents the assumed signal model and basic receiver structure. In
Section 4 after a brief review of near-optimal and existing pulse shaping
schemes, the concept of the proposed pulse shaping is explained and examples
are described for both the cases of unknown and known CFO. Section 5 presents
extended receiver structures for the narrowband signal, frequency-selective
channels, and multiple receive antennas. Simulation results are presented in
Section 6. The paper concludes in Section 7 with a summary recapping the
main advantages of the proposed pulse shaping schemes.
1.2. Notations
Lower-case
bold, as in
, denotes
vectors and * denotes a complex conjugation.
Term
represents the
probabilistic expectation,
denotes the
average over time,
is the
convolution operator, and
is Dirac's
delta function. Given a matrix
,
represents its
transpose,
its Hermite
conjugate, and
its vector
norm.
2. Technical Background
In this section,
we briefly review concepts that are related to cyclostationarity and are
relevant to this paper.
2.1. Wide-Sense Cyclostationarity
Let
be a
complex-valued zero-mean signal. The signal,
, is said to be wide-sense (second-order)
cyclostationary or exhibit wide-sense cyclostationarity (WSCS) [5] with cycle
frequency,
, if and only if the Fourier transform of its time
dependent autocorrelation function,
, called the cyclic autocorrelation function (CAF),
(1)
is not zero for some values of lag parameter
. In (1),
is the
observation time interval. On the other hand, the signal,
, is said to exhibit conjugate WSCS with cycle
frequency,
, if and only if the Fourier transform of its
conjugate time dependent autocorrelation function,
, called the conjugate CAF,
(2)
is not zero for some values of lag parameter
.
Another
essential way of characterizing WSCS and conjugate WSCS stems from the cyclic
nature of the power spectrum density of a cyclostationary signal. This is
represented by the Fourier transform of CAF, known as spectral correlation
density (SCD) and is given by
(3)
where
(4)
is the complex
envelope of the spectral component of
at frequency
with
approximate bandwidth
. Similarly,
(5)
Accordingly, the cycle frequencies,
, correspond to the frequency shifts for which the
spectral correlation expressed by (3) is nonzero. Similarly, the cycle
frequencies,
, correspond to the frequency shifts for which the
conjugate spectral correlation expressed by (5) is nonzero.
Also note that for
, the CAF,
, reduces to the classical autocorrelation function of
. For single carrier modulated signals, the cycle
frequencies
are equal to
the baud rate and harmonics thereof. Meanwhile, cycle frequencies
are equal to
twice the carrier frequency, possibly plus or minus the baud rate and harmonics
thereof. Following this, conjugate cyclostationarity can be observed in
carrier-modulated signals [6]. However, the conjugate CAF,
, reduces to zero for single carrier modulated
baseband signals when balanced modulation, for example, quadrature amplitude
modulation (QAM), is used.
2.2. CW Filtering
It is well
known that optimum filters for extracting a signal from a stationary received
signal are time-invariant and given by Wiener filters. Similarly, optimum
filters for extracting a signal from a received signal that exhibits
cyclostationarity with multiple cycle frequencies are multiply-periodic
time-variant filters which are shown to be equivalent to frequency shift linear
time-invariant filters and are known as CW filters [12]. The general
input-output relation of the CW filter for a complex-valued input signal,
, is given by
(6)
where
and
are
frequency-shifted versions of
and
, and
is the output
signal. Terms
and
are the number
of the cycle frequencies
and
, respectively. According to (6), the CW filter
jointly filters the input signal and its conjugate to produce the output
signal. This corresponds to a linear-conjugate-linear (LCL) filter which is
optimum for complex-valued signals [23]. Besides, according to (6), the CW
filter implicitly utilizes nonconjugate cyclostationarity and conjugate
cyclostationarity through
nonconjugate
linear time-invariant (LTI) filters of impulse-response,
, and
conjugate LTI
filters of impulse response,
, respectively.
Taking the Fourier transforms of both sides of (6), we
obtain
(7)
From (6) and (7), the input signal and its conjugate
are, respectively, subjected to a number of frequency-shifting operations by
amount
and
, then these are followed by LTI filtering operation
with impulse response functions
and
and transfer
functions
and
. Subsequently, a summing operation of the outputs of
all LTI filters is performed. As a result, for a cyclostationary input signal,
, the CW filter is equipped with the necessary
operations to take advantage of the spectral structure of
owing to the
nonzero correlation between
and
, and
and
(cf. (3) and
(5)). An illustration of the general input-output relation of the CW filter is
depicted in Figure 1.
Figure 1: Illustration of the general input-output
relation for a CW filter.
3. Description of Assumed Spectrum Sharing Scenario
In this
section, we introduce the assumed spectrum sharing scenario. This is
illustrated in Figure 2. The signal model and the basic structure for the
receiver used are described in the following.
Figure 2: Illustration of the baseband signal model of
two spectrally overlapping asynchronous signals having different symbol rates
and a carrier frequency offset.
3.1. Signal Model
The assumed
signal model consists of one wideband single-carrier modulated signal, one
narrowband signal and noise. The complex envelope of the received baseband
signal,
, is given by
(8)
At the right side of (8), the first term corresponds
to the wideband signal with a baud rate of
, the second term corresponds to the narrowband signal
with a baud rate of
, and the last term,
, represents complex white circular Gaussian noise.
Terms
and
are the carrier
frequency offset and the symbol timing offset between the wideband and
narrowband signals, respectively. In addition,
,
and
,
are the time
response of the transmit pulse shaping filters and the channel impulse
responses for the wideband and narrowband signals, respectively. The
transmitted symbols for the wideband and narrowband signals,
and
, are modulated using balanced QAM.
In the signal model above, we assume that only the
wideband signal is cyclostationary, that the narrowband signal is stationary,
that its parameters are basically unknown to the wideband signal, and that a CW
filter is utilized at the receiver for non-parametric suppression of NBI. Then
to improve the quality of extraction of the wideband signal using the CW filter
described in the previous section, the design of the pulse shaping filter,
, is studied. In the next section, we first present in
detail the basic structure that is assumed for the CW receiver.
3.2. Basic Receiver Structure
The basic
structure of the CW receiver used is shown in Figure 3. Prior to entering the
CW filter, a matched filter is used as a static filter to enhance the SNR.
Then, the CW filter serves as a dynamic adaptive filter to minimize the
time-averaged mean squared error (TA-MSE) between its output and the reference
target signal. Since balanced QAM is used for the wideband signal, only
nonconjugate branches are of interest to the CW filter; and having one
interferer the number of branches is limited to three, where each branch
corresponds to one cycle frequency,
, for the
wideband signal. Let us denote the target signal as
and the oversampled received signal as
, where
(
) is the
sampling rate. This receiver is denoted as CW1. The receiver, CW1, jointly
adjusts the coefficients,
, of the LTI
filters corresponding to nonconjugate branches such that the TA-MSE between the
summation of the outputs of the LTI filters and the target signal,
, is minimized
as follows:
Figure 3: The receiver structure CW1: a matched filter followed by a CW filter that
extracts the wideband signal by exploiting the cyclostationarity of the
wideband signal.
(9)
where
and
and
are given
by
(10)
where the LTI
filters corresponding to all cycle frequencies,
, are fractionally spaced filters of finite impulse
response (FIR) of order
.
4. Pulse Shape Design
Before
transmission a signal is traditionally pulse shaped to limit its occupied
bandwidth while still satisfying the Nyquist criterion of zero ISI to reduce
self-interference [24]. One of the basic pulses used is the sinc pulse which
occupies a minimal amount of bandwidth equal to the Nyquist (i.e., information)
bandwidth. The Nyquist bandwidth is given by
for the
wideband signal with a symbol rate of
. However, sinc pulses are noncausal and susceptible
to timing jitter; thus, other pulses that occupy more bandwidth than the
Nyquist bandwidth are usually employed in practice. The difference between the
occupied bandwidth and the Nyquist bandwidth, normalized by the Nyquist
bandwidth, is known as the excess bandwidth and measured in percentage. For
example, a pulse that occupies twice the Nyquist bandwidth has an excess
bandwidth of 100
. Although existing pulse shaping schemes are designed
to satisfy the Nyquist criterion of zero ISI, they do not take into account the
immunity of the pulse-shaped signal against in-band interference. The optimal
pulse shaping that takes advantage of the spectral structure owing to
cyclostationarity to suppress in-band interference corresponds to the search
for a solution to the joint optimization problem for minimizing the following
TA-MSE:
(11)
where
is the impulse
response of the transmit pulse shaping filter for the wideband signal and
is the impulse
response of the CW filter at the receiver. The problem of obtaining in
closed-form the solution to the above joint optimization is open. One heuristic
method to this problem is to find a near-optimal solution through an iterative
alternating search process between the optimal
for a fixed
and the optimal
for a fixed
[19, 20].
Nevertheless, this solution involves intensive computation due to large matrix
inversion at every iteration until convergence. In addition, and more
importantly, this solution turns out to be dependent of the channel impulse
response of the NBI and the SNR value, which is not practical for our spectrum
sharing scenario with unknown NBI.
4.1. Existing Raised Cosine Pulse Shaping
Another
possible heuristic solution to the joint optimization problem that requires
less complexity consists of minimizing
(11) through solely optimizing
. Thus,
is fixed. Then,
for the purpose of obtaining a reduced TA-MSE, a higher amount of
cyclostationarity is induced to
by extending
its excess bandwidth while still keeping the zero ISI criterion satisfied.
Raised cosine pulses, however, are typically obtained for an excess bandwidth
up to
(i.e., roll-off
factor,
, less than 1.0). For excess bandwidths beyond
, raised cosine pulses derived in [21, 22] can be
deployed. In the following, we describe the frequency responses of
existing raised cosine pulses for excess bandwidths less than and beyond
:
(i)
raised cosine
pulses with excess bandwidth less than
:
(12)
where
and
is the roll-off
factor of the pulse shaping filter, factor
controls the
amount of excess bandwidth;
(ii)
raised cosine
pulses with excess bandwidth beyond
[21]:
(13)
where
and
.
The square root
version of existing raised cosine pulses, denoted as SQRC, is given by
and illustrated
in Figure 4 when the excess bandwidth is
and
.
Figure 4: Examples of existing raised cosine pulse
shaping schemes.
From the perspective of nonparametric interference
suppression using cyclostationarity, one main drawback of the aforementioned
existing pulse shaping schemes remains in the manner by which the power is
distributed over their frequency response. In fact, most of the power is
concentrated around the center carrier frequency within the Nyquist bandwidth,
which results in the frequency components outside the Nyquist bandwidth having
relatively low power (cf. Figure 4). As will be clarified later in the simulation
results, this incurs a very limited interference suppression capability for the
CW filter against interference lying within the Nyquist bandwidth of the
wideband signal.
4.2. Proposed Pulse Shaping
For the
aforementioned existing pulse shaping schemes, although the excess bandwidth
can be increased, this might not always be efficient as it is for the case of
interference lying within the Nyquist bandwidth of the wideband signal. Our
concern, therefore, is to improve the interference suppression capability of CW
filtering while making use of pulse shaping with the minimal amount of excess
bandwidth. Here, inspired by ideas from both near-optimal and existing pulse
shaping schemes, we propose a design for pulse shaping,
, based on the following two criteria:
(1)
reduce
self-interference owing to ISI;
(2)
improve
suppression capability against external interference lying within the Nyquist
bandwidth of the wideband signal.
Keeping the
above two criteria in mind, two pulse shaping schemes are proposed for both the
cases of unknown and known CFOs.
4.2.1. Unknown CFO Case
For this case, it is not possible to avoid NBI; therefore,
the immunity of the wideband signal against NBI must be increased irrespective
of the CFO. For this purpose, it is important to design a pulse shaping filter
that has a frequency response in which the power is distributed almost
uniformly over all the frequency components. As a solution, we propose a
time-domain shrunk raised cosine (TSRC) pulse shaping for an excess bandwidth
beyond
. The frequency response of TSRC pulses is obtained by
shrinking the time response, equivalently stretching the frequency response, of
the existing raised cosine pulses for excess bandwidth less than
. To construct such a pulse for an excess bandwidth
with
(
is a nonzero
positive integer), we substitute in (12)
by
and
by
. Based on this, the frequency response of a
time-domain
shrunk raised
cosine pulse with excess bandwidth
with
is given by
(14)
where
. In the following, the square root version of these
pulses is called time-domain shrunk square root raised cosine, denoted as
TSSQRC, and their frequency response is given by
. For
, the obtained square root pulses are called
time-domain half shrunk square root raised cosine (HSSQRC) pulses. The proposed
HSSQRC pulse shaping is illustrated in Figure 5 for an excess bandwidth of
.
Figure 5: An example of proposed pulse shaping for the
case of unknown carrier frequency offset.
Regarding the first criterion, it is easy to verify
that the TSRC pulses described by (14) satisfy the Nyquist criterion of zero
ISI. Regarding the second criterion, TSRC pulse shaping has a lower power
concentration compared to the existing raised cosine pulses with the same
amount of excess bandwidth. An additional benefit remains in that the power of
the frequency components correlated with those within the Nyquist bandwidth is
not low anymore; therefore, robustness against interference lying within the
Nyquist bandwidth can be expected to increase compared to existing pulse
shaping schemes.
4.2.2. Known CFO Case
For this case, the knowledge of the CFO can be
utilized to minimize interference from the narrowband signal to the wideband
signal and concentrate the transmit power of the wideband signal on spectrum
parts that are noncorrupted by the narrowband signal. To make this possible,
after increasing the excess bandwidth as in TSRC pulse shaping, we null out
(notch) the part of the spectrum inside which the narrowband signal falls. Such
a pulse shaping is called notched TSRC (NTSRC).
In the following, we assume that the narrowband signal
occupies a bandwidth less than one Nyquist zone (
) of the
wideband signal. This is reasonable because
. One smooth construction of NTSRC pulse shaping is
obtained by
, where one Nyquist zone of the frequency response of
the TSRC pulse shaping is nulled out by subtracting the frequency response of a
raised cosine pulse having center frequency
, a Nyquist bandwidth,
, and an excess bandwidth of
, where
. For
, the frequency response of NTSRC pulse shaping is
given by
(15)
where
. In the following, the square root version of these
pulses is called notched time-domain shrunk square root raised cosine, denoted
as NTSSQRC, and their frequency response is given by
. For
, the obtained square root pulses are called notched
time-domain half shrunk square root raised cosine (NHSSQRC) pulses. The
proposed NHSSQRC pulse shaping is illustrated in Figure 6 for an excess
bandwidth of
.
Figure 6: Examples of proposed pulse shaping for the
case of known carrier frequency offset.
Regarding the first criterion, it is easy to verify
that the NTSRC pulse shaping described by (15) does not satisfy the Nyquist
criterion of zero ISI. Nevertheless, owing to the properly induced
cyclostationarity prior to spectral notching, ISI compensation is feasible by
using the CW filter at the receiver. Regarding the second criterion, besides
the benefits of the TSRC pulse shaping, for NTSRC pulse shaping, thanks to
spectral notching, efficient power allocation is possible as the signal power
is not wasted on corrupted spectrum.
5. Extended Receiver Structures
5.1. Receiver for Narrowband Signal
In a spectrum
sharing environment where the narrowband signal is also of interest, it is also
important to reveal whether the proposed pulse shaping for the wideband signal
is beneficial to the narrowband signal as well. Here, we describe receivers for
the narrowband signal for several cases of different coordination levels
between the narrowband and wideband signals: (1) unknown and known CFOs; and (2)
unknown and known cycle frequencies of the wideband signal.
(i)
The case of an unknown CFO: for this case, TSSQRC
is utilized for the wideband signal as proposed. For the receiver of the
narrowband signal, we consider the two cases below.(a)The case where the cycle frequencies of the
wideband signal are unknown to the receiver of the narrowband signal. For
this case, the narrowband signal has no information on the characteristics of
the wideband signal, and the in-band interference caused by the wideband signal
cannot be removed from the narrowband signal. Signal extraction can only be
carried out using the matched filter for the narrowband signal, hereafter
denoted as MF2.(b)The case where the cycle frequencies of the
wideband signal are known to the receiver of the narrowband signal. For
this case, the cycle frequencies of the wideband signal are known to the
receiver of the narrowband signal. Having this knowledge, the receiver
structure, CW2, illustrated in Figure 7 can be deployed. The
receiver, CW2, for the narrowband signal is intentionally not
equipped with a matched filter to allow for large bandwidth reception that also
includes the wideband signal. Its CW filter part utilizes the cycle frequencies
of the wideband signal so that the spectral structure for the wideband signal
is utilized to remove from the narrowband signal the interference owing to the
wideband signal.
(ii)
The case of a
known CFO: for this case, since NTSSQRC is utilized, the interference from the
wideband signal to the narrowband signal is minimal. Therefore, the extraction
of the narrowband signal can be carried out by simply using the matched filter, MF2.
Figure 7: The receiver structure CW2: A CW filter that extracts the narrowband signal by
taking advantage of the cyclostationarity of the wideband signal.
5.2. Receiver for Frequency-Selective Channels
Over
frequency-selective channels, multipath delay yields additional channel ISI.
For both proposed and existing pulse shaping schemes, channel ISI causes
frequency selectivity of the channel that destroys the spectral structure owing
to the cyclostationarity induced by the transmit pulse shaping filter of the
wideband signal. Therefore, channel ISI results in reducing the NBI suppression
capability of the CW receiver. In order to restore the destroyed spectral
structure, the CW filter needs to be combined with an equalization scheme to cope
with channel ISI. Here, we combine the CW filter with a decision feedback (DF)
filter. This combined receiver is denoted as CW1/DF and its
structure is depicted in Figure 8. It is noteworthy that the merit of the
receiver, CW1/DF, is that
nonparametric interference suppression and channel ISI equalization can be
performed jointly with no information on the NBI. In the receiver, CW1/DF, the filter
weights for the feedforward part consisting of the CW1 receiver and
the filter weights for the feedback part are computed jointly by minimizing the
TA-MSE of (16)
Figure 8: The receiver structure CW1/DF: a CW1 receiver
combined with a decision feedback filter.
(16)
In (16),
contains the
weights for both the feedforward CW and the decision feedback filters. Here,
the decision statistic vector,
, is given by
(17)
where the
feedback filter is a baud-spaced FIR filter of order
.
5.3. Receiver with Multiple Antennas
When multiple
antennas are employed at the receiver, both the spectral and spatial structures
of the received signal can be utilized to extract the target signal. This can
be achieved by cycle frequency shifting the signals received at all antennas.
Thus, the number of branches, that is, LTI filters, for a receiver with
antennas
becomes
times the case
of a receiver with one single antenna. This receiver is denoted as CW1,N (
). The
optimization of the weights for all branches is jointly performed for CW1,N as follows:
(18)
where
and
are given for
each receive antenna
similarly to
(9).
6. Performance Evaluations
6.1. Computer Simulation Setup
The bit-error
rate (BER) performance of the wideband and narrowband signals is evaluated for
the assumed spectrum sharing scenario. The channel models used are AWGN, a
frequency-flat Rayleigh fading channel with one single path, and a
frequency-selective Rayleigh fading channel with four baud-spaced paths, where
the average power ratio between any two successive paths is
dB. The channel for each path is modeled as quasistatic
Rayleigh fading, as we assumed that the channel stays invariant for the whole
frame but changes from a frame to another. Basically, the number of antennas
at the receiver
is one. If
is more than
one, this will be mentioned. Simulation parameters are depicted in Table 1. For
the narrowband signal, we use a fixed SQRC pulse shaping with an excess
bandwidth of
(SQRC20). For
the wideband signal, proposed HSSQRC and NHSSQRC pulse shaping schemes are used
and compared to existing SQRC pulse shaping schemes, in several channel
environments and interference conditions. Throughout all the simulation
results, the average received power is normalized to be equal for all proposed
HSSQRC, NHSSQRC, and existing SQRC pulse shaping schemes. Also, for NHSSQRC
pulse shaping, the factor
(cf. (15)) is
set to
.
Table 1: Simulation parameters.
6.2. AWGN Channel Case
BER versus
for the
wideband signal: W/o NBI
In Figure 9, without NBI, the receiver, CW1, shows almost the same performance for both existing
and proposed pulse shaping schemes regardless of the amount of excess
bandwidth. This is because the average received power was normalized to be the
same for all pulse shaping schemes.
Figure 9: BER versus

for the
wideband signal: AWGN channel and w/o NBI.
BER versus
for the
wideband signal:
In Figure 10, with NBI and
, the receiver, CW1, is used to extract the wideband signal. The BER
performance of the wideband signal is largely degraded for existing SQRC20
pulse shaping since it contains a limited amount of cyclostationarity. On the
other hand, our proposed HSSQRC120 pulse shaping yields much better BER
performance than the existing SQRC120 pulse shaping scheme. This is because
less noise enhancement occurs at the CW filter when the HSSQRC and NHSSQRC
pulse shaping schemes are used, since the power of the frequency components of
the wideband signal separated by one cycle frequency (
) from its
corrupted Nyquist bandwidth is higher with the HSSQRC and NHSSQRC pulses than
with the existing SQRC pulses (cf. Figures 4, 5, and 6).
Figure 10: BER versus

for the
wideband signal: AWGN channel and

.
Besides, when the CFO is known to the wideband signal,
thus NHSSQRC pulse shaping is used, better performance is achieved compared to
HSSQRC pulse shaping. This is because for NHSSQRC pulse shaping, the signal
power is not wasted on the corrupted spectrum and is mainly allocated to
noncorrupted spectrum parts of the wideband signal (cf. Figure 6).
BER versus EBW for the
wideband signal:
and
dB
In Figure 11, the receiver, CW1, shows better interference suppression with proposed
HSSQRC and NHSSQRC pulses even for less excess bandwidth (EBW) compared to
existing SQRC pulse shaping, for example, HSSQRC with the EBW of
versus SQRC
with the EBW of
. This is because less noise enhancement occurs at the
CW filter when proposed pulse shaping is used. On the other hand, an increase
in the EBW to beyond
does not
improve the BER performance for the proposed pulse shaping in Figure 11. This
is because the amount of cyclostatinarity induced by the proposed pulse shaping
for the EBW of almost
is already
sufficient for suppressing one interferer. A further increase in the EBW simply
results in occupying a larger bandwidth, leading to lower power concentration,
which degrades the BER performance for the receiver. To exploit the increase in
EBW to beyond
, the number of branches for receiver, CW1, can be increased to more than three; however, the
use of more branches comes at the price of more tap weights to estimate and a
more complex receiver structure although the BER improvement should be limited
with only one interferer.
Figure 11: BER versus EBW for the
wideband signal: AWGN channel,

and

dB.
BER versus
for the
wideband signal:
dB
In Figure 12, for a relatively large
, the receiver, CW1, performs sufficiently well with SQRC pulses having a
minimal amount of excess bandwidth (e.g., SQRC20). This is because for a
relatively large
, the matched filter before the CW filter at the
receiver, CW1, also has a minimal amount of excess bandwidth and
consequently can help the CW filter in suppressing interference lying on or
outside the boundaries of the bandwidth occupied by the wideband signal. On the
other hand, for zero and a small
, that is, interference lying within the Nyquist
bandwidth of the wideband signal, the receiver, CW1, exhibits better performance using the proposed
HSSQRC and NHSSQRC pulse shaping schemes. This is because, for a small
, the matched filter for existing SQRC pulse shaping
cannot suppress the interference. In addition, the CW filter better utilizes
the spectral structure owing to cyclostationarity for interference suppression
with proposed HSSQRC and NHSSQRC pulse shaping compared with existing SQRC
pulse shaping. Another important feature is that the BER of the receiver, CW1, is kept almost the same irrespective of
for the HSSQRC
and NHSSQRC pulse shaping schemes. This is brought about by the almost-flat
shape of their frequency response (cf. Figures 5 and 6).
Figure 12: BER versus

for the
wideband signal: AWGN channel and

dB.
BER versus
for the
narrowband signal:
In Figure 13, the BER of the narrowband signal is
plotted as a function of
for
. For the narrowband signal, its matched filter, MF2, or the receiver, CW2, is used as the receiver. For both receivers, HSSQRC
and NHSSQRC pulse shaping schemes yield better performance than existing SQRC
pulse shaping scheme. When the cycle frequencies of the wideband signal are
known to the receiver of the narrowband signal, the narrowband signal can use
the receiver, CW2, to take advantage of the spectral structure due to
the cyclostationarity of the wideband signal to remove its interference from
the narrowband signal. For this case as well, the BER performance of the
narrowband signal can be improved by using HSSQRC pulse shaping rather than
using SQRC pulse shaping. Moreover, when NHSSQRC pulse shaping is used for the
wideband signal, the BER performance for the narrowband signal is significantly
improved as it receives almost no interference from the wideband signal.
Figure 13: BER versus

for the
narrowband signal: AWGN channel and

.
6.3. Fading Channel Case
BER versus
for the
wideband signal: frequency-flat channel, one or two receive antennas, and
In Figures 14 and 15, for both the cases of one
receive antenna (
) and two
receive antennas (
), the average
BER performance of receivers CW1 and CW1,2 is improved
over the frequency-flat fading channel by using pulses with a larger excess
bandwidth. Also, for the same excess bandwidth of
, the use of HSSQRC120 and NHSSQRC120 pulse shaping
schemes results in performance improvement compared to that for SQRC120 pulse
shaping. The performance improvement, however, is decreased as
increases. This
is because the more spatial degrees of freedom we have for interference
suppression, the lower is the noise enhancement effect at the receiver.
Figure 14: BER versus

for the
wideband signal: frequency-flat fading channel, one receive antenna and

.
Figure 15: BER versus

for the
wideband signal: frequency-flat fading channel, two receive antennas (

) and

.
BER versus
for the
wideband signal: frequency-selective, one receive antenna and decision feedback
equalization,
, and
In Figure 16, the average BER versus the average
for the
wideband signal is evaluated over the frequency-selective Rayleigh fading
channel. The BER performance for the receiver, CW1, is largely degraded. This is because the receiver, CW1, fails to equalize the multipath channel when this
one is nonminimum phase. Besides, in a frequency-selective channel the
receiver, CW1, needs to equalize jointly the multipath channel and
remove NBI from the received signal. As a result, more degrees of freedom are
consumed compared to the case of a frequency-flat channel. Using receiver, CW1/DF, we obtain
a superior performance to that for receiver, CW1. Also, a substantial performance improvement is
obtained for using the proposed pulse shaping schemes than for using existing pulse
shaping schemes. Therefore, by using proposed pulse shaping schemes, the
receiver, CW1/DF,
effectively performs joint nonparametric interference and ISI equalization over
a frequency selective Rayleigh fading channel, which is disturbed by unknown
NBI.
Figure 16: BER versus

for the
wideband signal: frequency-selective fading channel, one receive antenna, and

.
7. Conclusion
In this paper,
we investigated a flexible spectrum sharing scenario where a wideband
single-carrier modulated signal is jammed by unknown NBI. A CW filter is
utilized to exploit the cyclostationarity property of the wideband signal for
nonparametric suppression of NBI. The impact of pulse shape design on the
interference suppression capability of the CW filter is elucidated. For NBI
with large CFO, that is, NBI lying outside the Nyquist bandwidth of the
wideband signal, we clarified that there is no advantage in modifying the pulse
shaping or increasing the excess bandwidth of the pulse shaping filter. For NBI
lying within the Nyquist bandwidth of the wideband signal, we proposed new
pulse shaping schemes for the wideband signal for both the cases of unknown and
known CFOs between the wideband signal and NBI. Through extensive simulation
results, we showed that the proposed pulse shaping schemes have the potential
to substantially improve the interference suppression capability of CW
filtering over both AWGN and Rayleigh fading channels. A large part of the
improvement achieved is due to the ability of proposed pulse shaping to take
into consideration the existence of interference within the Nyquist bandwidth
of the wideband signal by means of increasing their amount of cyclostationarity
within a limited amount of excess bandwidth while still minimizing
self-interference by reducing ISI. The simulation results also revealed that
the proposed pulse shaping performs well over frequency selective channels and
for receivers with multiple receive antennas, and is also beneficial to the
narrowband signal.
Acknowledgment
This paper was presented in part at the IEEE Vehicular Technology
Conference Fall and the IEEE International Symposium on Personal, Indoor, and Mobile
Radio Communications, both in September 2006.
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