The 802.11g PHY defined in standard is known as the Extended Rate PHY (ERP), operating in the 2.4 GHz ISM band. Four operational modes is as followed:
a) ERP-DSSS/CCK – This mode builds on the payload data (PSDU) rates of 1, 2, 5.5, and 11 M bit/s that use DSSS (DBPSK and DQPSK), CCK and optional PBCC modulation, and the PLCP Header operates on data rate 1 M bit/s DBPSK for Long SYNC, 2 M bit/s DQPSK for Short SYNC. Figure 2.1 shows the format for the interoperable PPDU that is the same with 802.11b PPDU format, and the details of components such as spreading code, scrambler, CRC implementation, and modulation refer to 802.11b standard.
Long/Short SYNC SFD SIGNAL SERVICE LENGTH CRC
PLCP Preamble PLCP Header PSDU
PPDU
1 Mbit/s DBPSK 2 Mbit/s DQPSK 5.5 or 11 Mbit/s CCK
Figure 2.1 ERP-DSSS/CCK PPDU format
b) ERP-OFDM – This mode builds on the payload data rates of 6, 9, 12, 18 24, 36, 48, and 54 M bit/s, based on different modulations (PSK and QAM) and coding rate, by means of OFDM technique. Except PLCP Preamble, SIGNAL field with data rate 6 M bit/s and DATA are packaged (OFDM) symbol by symbol. The only difference from 802.11a is the operating ISM band (802.11a is in 5 GHz).
Figure 2.2 is the PPDU format.
RATE Reserved LENGTH Parity Tail SERVICE
2 Long Symbols SIGNAL
One OFDM Symbol DATA
Variable Number of OFDM Symbols
PPDU
Figure 2.2 ERO-OFDM PPDU format
c) ERO-PBCC – This mode builds on the payload data (PSDU) rates of 22 and 33 M bit/s and it is a single-carrier modulation scheme that encodes the payload using 256-state packet binary convolutional code. The PPDU format follows mode a).
d) DSSS-OFDM – This mode is a hybrid modulation combining a DSSS preamble and header with an OFDM long preamble, signal field and payload transmission.
In the boundary between DSSS and OFDM parts, it is single carrier to multicarrier transition definition. The payload data rates are the same with those of b). The PPDU format is as followed,
Long/Short SYNC SFD SIGNAL SERVICE LENGTH CRC
PLCP Preamble PLCP Header PSDU
PPDU
Figure 2.3 DSSS-OFDM PPDU format
An ERP BSS is capable of operating in any combination of available ERP modes and Non-ERP modes. For example, if options are enabled, a BSS could operate in an ERP-OFDM-only mode, a mixed mode of ERP-OFDM and ERP-DSSS/CCK, or a mixed mode of ERP-DSSS/CCK and Non-ERP. Notice that since the first two modes are required to implement and considered as main operating modes and the others are optional, the discussion of platform will be located on the first two modes hereinafter.
Figure 2.4 is the transmitter block diagram. After the parameters of operation mode, data rate and data length are decided, following these blocks one by one will generate the transmitted signals, and the MUX that depends on operation mode will select the signal that be sent to air by antenna after up-conversioning the baseband signals to operating channel frequency.
PLCP
Figure 2.4 transmitter block diagrams
2.2 Channel models
For wireless communication system, because air is the medium for transmission, the wireless channel models are more complicated than wired ones. Many irresistible atmosphere factors have to be put into consideration. From the transmitter end to receiver end, that baseband signals are masked within transmit spectrum mask that
is defined in standards, that signal power decreases with the distance between transmitter and receiver, that the signals are convolved with multipath, which means signals are affected significantly by their delay version, that signals are added with AWGN, and that carrier frequency offset is multiplied to signals with time index, are explained particularly as below:
a) Transmit spectrum mask:
It is well-known to use raised cosine spectrum as the shaping filter that fits the transmit spectrum mask in standard. The raised cosine frequency characteristic is given as The roll-off factor is the percentage of the bandwidth occupied by signal beyond the Nyquist frequency ( 1
T ) to the Nyquist frequency. For example, when β=0.5, the excess bandwidth is 50 percent of 1
T. The corresponding impulse
rc( )
x t , having the raised cosine spectrum and is normalized, is
2 2 2 2
If sample timing is correct, all samples will avoid inter-symbol interference (ISI) due to raised cosine function; if not, mistiming errors in sampling result in a series of ISI components that converges to a finite value.
b) Path loss:
Path loss is the difference (usually measured in dB) between the transmitted power and the received power. It represents signal level attenuation caused by free-space loss, refraction, reflection, aperture-medium coupling loss, and absorption. At the receiver, it is necessary to implement a variable gain amplifier (VGA) to enhance signal power and a controller, called automatic gain control (AGC), to estimate proper path loss parameter and justify the VGA gain.
This topic was discussed deeply in [4].
c) Multipath:
Because there are obstacles and reflectors in the wireless propagation channel, the transmitted signal arrivals at the receiver from various directions over a multiplicity of paths. Such a phenomenon is called multipath. It is an unpredictable set of reflections and/or direct waves each with its own degree of attenuation and delay. Multipath is usually described by two sorts:
1) Line-of-sight (LOS): the direct connection between the transmitter (TX) and the receiver (RX).
2) Non-line-of-sight (NLOS): the path arriving after reflection from reflectors.
LOS NLOS
Tx NLOS Rx
Figure 2.5 LOS and NLOS
Multipath will cause amplitude and phase fluctuations, and time delay in the received signals. When the waves of multipath signals are out of phase, reduction of the signal strength at the receiver can occur. One such type of reduction is called the multipath fading; the phenomenon is known as "Rayleigh fading" or "fast fading." A representation of Rayleigh fading and a measured received power-delay profile are shown in Figure 2.6. Besides, multiple reflections of the transmitted signal may arrive at the receiver at different times;
this can result in inter-symbol interference that the receiver cannot sort out.
This time dispersion of the channel is called multipath delay spread that is an important parameter to access the performance capabilities of wireless systems.
A common measure of multipath delay spread is the root mean square (RMS) delay spread. For a reliable communication without using adaptive equalization or other anti-multipath techniques, the transmitted data rate should be much smaller than the inverse of the RMS delay spread (called coherence bandwidth).
And, this paper is going to consult some well-known wireless indoor models—
SPW, IEEE 802.11g and JTC multipath models— and provide solutions to system suffered from severe multipath fading mainly.
Figure 2.6 measured power-delay profile of Rayleigh fading
d) IQ mismatch:
For phase and frequency modulation scheme, a homodyne receiver must incorporate quadrature mixing. The errors in nominally 90 degrees phase shift, and mismatches between the amplitudes of the I and Q signals corrupt the downconverted signal constellation, thereby raising the bit error rate. Figure 2.7(a) shows that both of I and Q contribute gain and phase error, and Figure 2.7(b) is an example of gain and phase error for QPSK. The details of compensation mechanism have been handled by [5].
LPF 90
LPF I
Q phase and gain error
ideal ideal
Q Q
I I
(a) (b) Figure 2.7 IQ mismatch
e) Carrier frequency offset (CFO)
Ideally, the receiver carrier frequency should exactly match the transmit carrier frequency. However, it is inappropriate in practical application, and the inconsistency between transmitter and receiver oscillators causes CFO, which, in general, is measured in ppm (parts per million). The effect of frequency offset in time domain is equivalent to phase rotation with time, and is compensated by numerically controlled oscillator (NCO) whose parameter is estimated by automatic frequency control (AFC), which is designed in [4] and [6].
All mentioned channel factors that occur over transmission in Figure 2.8 would be bound into our platform parameters. However, this modeling includes bandpass system, thus making difficulty and ambiguity in program simulation. A baseband equivalent model is now derived and is defined in Figure 2.9, where the signal modeling is therefore formulated as
( ) ( ) ( ) ( ) ( )
j ( )t( )
IQ mismatch Path IQ mismatch
Loss
Multipath Shaping
Figure 2.8 channel models
Shaping
Figure 2.9 baseband equivalent channel models
As the target described in the beginning, our focus will be located on the estimation of and the equalization of data in chapter 3. We start our research on multipath effect and AWGN noise as most papers did. After T
( ) h t
s-spaced sampling, the
discrete-time received signal is the linear convolution of transmitted signal x k
[ ]
andis the order of discrete-time multipath model).
2.3 Receiver
For dual-mode 802.11g transmitter, it is directly perceived through the senses that integrate 802.11a and 802.11b receivers with a multiplexer as shown in Figure 2.10. Obviously, there are many modules with the same function, including ADC,
Timing
Figure 2.10 separate receiver block diagrams
AGC, Timing SYNC, AFC, Equalizer, and Descrambler. These module blocks are necessary for any type of wireless communication system, which inspiring us to consider a possibility of universal receiver. Because the blocks before FFT operate in time domain no matter DSSS or OFDM system, it is easy to reach the goal of sharing only by means of adding control signals to distinguish different transmission modes.
However, equalization, generally, acts in time domain for DSSS system, and in frequency domain for OFDM system. In order to achieve the goal of unique equalizer, it is necessary to choose a domain to conduct interfered signal. Review the equalization of OFDM system; it needs only one divider to deal with convolved time domain signals in frequency domain according to known or estimated channel frequency response. For consideration of time domain solution, not only will
hardware cost with regard to OFDM system increase, but also signal is hard to make decision over original frequency response in time domain. Compared frequency domain solutions with often seen time domain ones, decision feedback equalizer (DFE) or adaptive method, operations with only one divider actually save a lot of hardware cost and computational complexity. Therefore, we proposed a equalizer based on receiver block diagrams as Figure 2.11, which takes OFDM system as the major and DSSS system as the minor, i.e., besides OFDM signal, DSSS signal would be passed through FFT. And to avoid additional IFFT that transform DSSS signal back to time domain, procedures of dispreading and demapping has to be done in frequency domain, too. In other words, we would get rid of common solution, FWT, and give a new frequency domain solution.
Timing
Figure 2.11 universal-directed receiver block diagrams
The challenge is that there is no mechanism that is designed against or to solve multipath effect in DSSS packet format; on the contrary, guard interval of OFDM system result in circular convolution so that deconvolution can be achieved by FFT.
( )
Although there have been already many frequency domain deconvolution techniques [7], they are still not suitable in our situation because multipath may be composed of severe selective fading and unstable poles instead of convergent filtering. Besides, these existing frequency domain method over time domain signal require 2 or more FFT blocks, which means more hardware cost, and since frequency responses
resulted from these methods contain aliasing due to non-circular convolution, we cannot design a frequency domain CCK demapper based on them. Another issue is the problem of traditional one-tap equalization, which noise would be enhanced largely on very deep channel frequency response. Unlike OFDM system where signal is modulated to fixed magnitude for each frequency, every possible DSSS codeword has its own different frequency response, and that makes such effect vary so significantly among DSSS symbols that the performance is unpredictable and bounded by transmitted sequences while it has actually been improved greatly in [8],
magnitudemagnitudemagnitude
f f
f
k( )
i
DFTN⎡⎣c n ⎤⎦
k( )
j
DFTN⎡⎣c n⎤⎦
N ( )
DFT ⎡⎣h n ⎤⎦
[9] and [10]. As a result, we are going to propose a novel frequency domain approach to overcome aliasing caused by FFT and deal with DSSS equalization and CCK demapping, and at the same time, the processes are completed by sharing OFDM equalization blocks. Note that it is well known and discussed broadly for OFDM channel estimation and equalization so the remaining of this thesis would focus on how to solve difficulties in DSSS mode under our receiver block diagrams and requirement.
Chapter 3
Channel Estimation & Equalization
According to proposed receiver block diagrams, we hope to seek frequency domain techniques to handle the originally time domain signal. These concepts are indeed considered and discussed a lot in recent years and combined with adaptive filters further. Frequency domain processes have primarily advantages compared to time-domain implementations. The first advantage is the potentially large savings in computational complexity because of block-based signal processing. The FFT is an efficient implementation of the DFT that provides this advantage. The second is that the DFT and the filter bank structures generate signals that are approximately orthogonal. In addition, this technique applied to DSSS signals in our approximately universal receiver reuses equalization modules of OFDM mode. Now we are going to show proposed relative schemes—channel estimation and equalization—that are very different from general adaptive methods [7].
3.1 Channel Estimation
The most common approach for coefficients estimation is usually adaptive algorithm that need not rely on specific data format and conditions. Least mean squares (LMS), recursive least squares (RLS), DFE, etc are famous and widely-used time domain adaptive methods to calculate the channel impulse responses over DSSS system. Even if the ideal coefficients may be not obtained by practical process for some conditions, that is, there exists no inverse, adaptive algorithm is able to approximate very closely. However, taking proposed receiver architecture into account, expected estimation scheme should be realized in frequency domain
instead of time domain, and that results in challenges indeed. One idea is just to transform the processes of adaptive algorithms applied in time domain to frequency domain, and it has been done based on RLS algorithm in [11] with mathematical deduction. Another is to make use of overlap-and-save and overlap-and-add technique with adaptive loops [7]. Though FFT is convenient to deal with and to reduce convolution over time domain, approaches mentioned above need additional operations and IFFT to eliminate aliasing attributed to non-circular convolution. Here are two different methods in essence, simpler and non-adaptive ways that exploit the characteristics of spreading codes resulting (pseudo) circular prefix and the concepts of fast linear convolution by means of Fourier transform. The first one, in fact, is to find the condition that satisfies circular property; the other is to use common FFT technique and is unconcerned with circular property. The comparison between these two schemes will be shown along with proposed equalizer in chapter 5. And no matter which one is better, each provides a possibility of frequency domain channel estimation over DSSS system.
3.1.1 Proposed Scheme #1
Guard interval of OFDM system is a cyclic extension of the symbol, repetition of tail part of the symbol so equalization can be achieved easily in frequency domain.
Well, where is the circular prefix during DSSS preamble?
If we do not considering the length of FFT window, two successive identical spreading sequences can meet our requirements; that is, the former is regarded as the circular prefix of the latter. Notice that the length of spreading code in this case is equivalent to the length of circular prefix, the maximum delay this format can suffer.
Figure 3.1 illustrates that though spreading sequences are linear convolved with multipath, we can conduct the latter sequence as circular convolved with multipath under condition of two successive identical spreading sequences,
FFT Window 1
Sk− Sk Sk
( )
h t
Figure 3.1 2 successive identical symbol lead to circular property
, where Si is some spreading sequence, Sk is the same with the previous Sk−1, and the curved arrow represents multipath effect h t
( )
. Hence, if the maximum delay of does not exceed the length of spreading code, the multipath channel frequency response, where Yi
( )
ω is received signals that is the results of transmitted signal convolved with multipath effect, and Si( )
ω is the frequency response of spreading sequence . Generally, in order to ensure detecting of packet and estimation of unideal factors, the modulation during preamble is usually simpler than that in data frame and, in other words, is with longer distance between code sets than modulation of data. As a result, this situation can occur frequently and easily during preamble of common DSSS system, and an estimation scheme can thus be developed based on such a simple concept.Si
There are still two improvements in algorithm itself: noise suppression of noise and enhancement of tolerance of multipath maximum delay. According to equation (3.2)
( ) ( ) ( )
PN( ) ( ) ( )
PN(
y t =x t ⊗h t ⊗S − =t h t ⊗⎡⎣x t ⊗S −t
)
⎤⎦ (3.2), we can employ the technique on transmitted signal as well as on correlation output with PN code, x t
( )
⊗SPN(
−t)
, to obtain channel frequency response. This concept is similar to the use of spreading sequence to raise SNR; that is, to reduce noise relatively. For limitation of multipath length, unlike initial consideration of one symbol as circular prefix, two or more symbols are taken into account, and the criterion depends on the specifications of platforms, standard requirements, or environments.Finally, a general process chart is carried out as following Figure 3.2.
2/more symbol of
Figure 3.2 consideration of multiple symbols
For example of IEEE 802.15.4 [12], the preamble field is composed of 32 binary zeroes, and each 4 zeroes of them will be spread by only one 32-chips long PN sequence. If the length of FFT window is 32, merely one spreading sequence will be included and if it is 64, two is consider. And with increase of FFT window, the tolerance of multipath maximum delay and the precision of estimation are stronger and sharper also.
This concept is actually simple, but it is restricted by defined preamble format, and it seems to have some difficulty in our choice, IEEE 802.11g ERP-DSSS mode.
The resources in proposed receiver for channel estimation are 64-point FFT that is equipped for OFDM system and 11-chips Barker sequence as the PN code for DSSS system. The number of FFT points decides the FFT window; the length of PN code, that of circular prefix. Under these constraints, the only problem is that the length of FFT is not multiple of the length of Barker sequence, and one (11 ) or two ( ) chips of the last symbol in FFT window must be cut off so the condition of circular prefix can no longer be achieved easily. However, because the characteristics of Barker codes are almost mutual irrelevant except totally matching between received signals and prepared barker correlator, the correlation output will be stable excluding the occurrence of correlation peak, seeing Figure 3.3.
3 32 1
× − =
11 6 64× − =2
stable parts
Figure 3.3 features of correlation over 11M Hz
Even though some correlation chips has to be cut, the remaining of stable parts resemble the stable parts in front of referenced FFT window, and those chips can still result in “pseudo” circular property. As a result, channel estimation has no need to adopt additional IFFT because of adaptive algorithms and can be accomplished by equation (3.1) again even if the preamble of 802.11g ERP-DSSS/CCK mode has no prepared format for frequency domain operation. The numbers of cut-off chips are
Even though some correlation chips has to be cut, the remaining of stable parts resemble the stable parts in front of referenced FFT window, and those chips can still result in “pseudo” circular property. As a result, channel estimation has no need to adopt additional IFFT because of adaptive algorithms and can be accomplished by equation (3.1) again even if the preamble of 802.11g ERP-DSSS/CCK mode has no prepared format for frequency domain operation. The numbers of cut-off chips are