Abstract: The wireless industry is currently undergoing a major transition from second generation to third generation wireless technologies and the increasing demands for communication services require higher transmission rates that further stimulates the demand on wideband technologies depicted in the form of Code Division Multiple Access (CDMA) on one hand. Also, as the privacy is a prime issue in modern communications then the carriers orthogonality is a fundamental concept for a sustainable development of the communications sector. This study attempts to assess wireless communications channels and propose techniques to improve the performance of modern wireless communications. Hence from a strategic perspective, an analytical study into the comparison of performance of Group Orthogonal Multi Carrier Code Division Multiple Access (GO-MC-CDMA) and multicarrier code division multiple access signal in frequency selective fading channel, the channel bandwidth is the main theme of this study; from which the problems that may affect the communications link are high lighted and measures to counterbalance and alleviate multi path fading are proposed and investigated. Such measures are: Space diversity combining techniques and interference cancellation and detection are considered in this study. As a result of a comparison between two schemes in this study it can be stipulated that sub carriers grouping does reduce Multi-User-Interference (MUI) between frequency groups thus enhance the performance of MC-CDMA system in the mission of meeting newly emerging wideband communications services, such as video conference add others.
INTRODUCTION
A comparison study of group orthogonal multicarrier code division multiple access and multicarrier code division multiple access signal in multipath fading channels is held between these schemes. OFDM is an important scheme to frequency selective fading (Qatawneh, 1997, 2003; Qatawneh and Dababneh, 2007), however, it has several disadvantages such as difficulty in sub carrier synchronization and sensitivity to frequency offset and nonlinear amplification which result from the fact that it is composed of a number of sub carriers with their overlapping power spectra and exhibits a non-constant nature in its envelope. However, the combination of OFDM signaling and CDMA scheme has one major advantage that it can lower the symbol rate in each subcarrier so that a longer symbol duration makes it easier to quasi-synchronize the transmissions. The multi carrier CDMA schemes are categorized mainly into two groups: One spreads the original data stream using a given spreading code and then modulates a different sub carrier with each chip (in a sense that the spreading operation is in the frequency domain) and other spreads the Serial-to-Parallel (S/P) converted data streams using a given spreading code and then modulates a different subcarrier with each of the data stream (the spreading operation in this is in the time domain); similar to a normal Direct Sequence Code Division Multiple Access (DS-CDMA) scheme (Dababneh and Qatawneh, 2013; Hara and Prasad, 1997; Cai et al., 2004). In order to exploit the maximum possible channel diversity while being able to accommodate dynamic load changes, a Group Orthogonal Multi Carrier Code Division Multiple Access (GO-MC-CDMA) scheme is developed. This scheme does not require complex code assignment operations. The set of subcarriers is partitioned into groups and the users who are assigned sub carriers of the same group are separated using spreading codes. Furthermore, it can be seen that grouping the subcarriers together will help the user to achieve full multi path diversity which is essential for the mitigation of the multi path effects. Also the users in each group are immune to interference from other groups, hence explains the name of this scheme, as group orthogonal MC-CDMA.
SYSTEM MODEL
The comparison of, a Group Orthogonal Multi Carrier Code Division Multiple Access (GO-MC-CDMA) scheme (Dababneh and Qatawneh, 2013) and group orthogonal MC-CDMA (Dababneh and Qatawneh, 2013). is developed and Also the users in each group are immune to interference from other groups.
In this section a complete modeling of the system is presented. A symbol-spread case is considered, where each active user transmits only one symbol over a block of Nc chips, the symbol period is T = NcTc. The entire available bandwidth is utilized with Nc sub carriers that are spaced by 1/T apart. If fi denotes the ith column of the Fast Fourier Transform (FFT) matrix FNc, then fi* is the ith digital sub carrier. The Nc subcarriers are partitioned into Ng groups with each group having Q = Nc/Ng subcarriers. A user chooses a specific group of subcarriers to transmit its information bearing symbols and Q users share Q subcarriers per group which ensures no spectral efficiency loss (Katariya et al., 2011). The system model of GO-MC-CDMA (Dababneh and Qatawneh, 2013) is illustrated in the block diagram of Fig. 1.
FADING CHANNEL MODEL
The tapped delay line is shown in Fig. 2. The time variant tap weights {hp(n)} are zero mean complex valued stationary Gaussian random process and they correspond to the L different delays τ = pTm, p = 1,2,…L. For all practical purposes, the tapped delay line model for the channel can be truncated at L = [TmW]+1 taps (Dababneh and Qatawneh, 2013), where, Tm is a total multipath delay spread and W is signal bandwidth. Then, the noisy received signal can be expressed in the form (Dababneh and Qatawneh, 2013; Cai et al., 2004; Naveen et al., 2010; Katariya et al., 2011) (Eq. 1):
| (1) |
SELECTION DIVERSITY
The major diversity combining techniques are selection diversity, maximal ratio combining and equal gain combining. Selection Diversity (SD), shown in Fig. 3, is the simplest of these methods.
| Fig. 1: | System model of GO-MC-CDMA (Dababneh and Qatawneh, 2013) |
| Fig. 2: |
Tapped delay line model of frequency
selective channel (Dababneh and Qatawneh, 2013) |
| Fig. 3: |
Block diagram of a two-branch selection
diversity system for equal noise powers |
| Fig. 4: |
First stage of Multistage Parallel Interference
Cancellation (MPIC) detector. (Dababneh and Qatawneh, 2013) |
From a collection of antennas, the branch that receives the signal with the largest signal-to-noise ratio at any time is selected and connected to the demodulator. As one would expect, the larger the number of available branches, the higher the probability of having a larger Signal to Noise Ratio (SNR) at the output (Chung and Phoong, 2011).
MULTISTAGE PARALLEL INTERFERENCE CANCELLATION (MPIC)
The multistage interference cancellation receivers have multiple stages of interference cancellation. This technique can be combined with the concept of parallel interference cancellation. At each stage of MPIC, any receiver can be used but the accuracy of the first stage or previous stage affects the performance of the whole receiver (Proakis, 1998; Dietze, 2001). A conventional receiver is considered as a first stage to estimate the channel gain and data symbol. The estimates for each user are used to eliminate the interference of the other user’s signal by subtracting the interferer from the desired signal. The interference cancellation depends on the accuracy of the estimates at the previous stage. Since the inaccurate estimates lead to imperfect interference cancellation in real system, several stages can be used or a more powerful estimate technique such as a channel coding scheme can be utilized to overcome this imperfection. In addition, an improved MPIC scheme with partial cancellation at each stage is introduced to mitigate bias in the decision statistics of MPIC (Sim, 2000). The MPIC decision metric for S-stage parallel cancellation scheme is represented as (Eq. 2-4):
| (2) |
Where:
| (3) |
| (4) |
where, rk is the S stage signal of the mth user after cancellation and τm represents the estimated time delay of mth user (Dababneh and Qatawneh, 2013; Cai et al., 2004). The first stage of Multistage Parallel Interference Cancellation (MPIC) is shown in Fig. 4.
| Fig. 5: |
First stage of a Multistage Successive
Interference Cancellation (MSIC) detector. (Dababneh and Qatawneh, 2013) |
On proceeding subsequent stages, the effect of bias is minimal. The proposed method to reduce the influence of bias is to adopt a partial-cancellation factor F(s) as follows (Eq. 5):
| (5) |
This factor is assigned a value at every stage in the range (0…1) (Katariya et al., 2011).
MULTISTAGE SUCCESSIVE INTERFERENCE CANCELLATION (MSIC)
Successive Interference Cancellation (SIC) detector is distinct from PIC detector, it takes a serial approach to cancel interference, as shown in Fig. 5. The first operation in the Successive Interference Cancellation (SIC) detector consists of sorting the user’s signals out in a descending order according to their powers which are estimated from the output of a conventional detector. The first stage in this detector is to regenerate the transmitted signal of the strongest user (in terms of powers and assuming knowledge of the spreading code). This regenerated signal provides an estimate of the MAI caused by the strongest user b1(t) which is then subtracted from the total received signal r(t), yielding a partially cleaned version of the received signal r1(t). If the user estimate is accurate, the remaining users see less MAI in the next stages. Thus, this new version of the received signal can be used to detect the next strongest user in the system. This process is repeated until all users are detected (Hourani, 2005; Rivera, 2009; Hochwald and Marzetta, 2000).
Note that; in each stage the estimate of the users is obtained by making a decision at the output of the conventional detector. The benefit of sorting the signals out in a descending order is because the strongest user can give the most accurate estimate and consequently the removal of this signal will provide the most benefit to the remaining users (Andrews, 2005; Chung and Phoong, 2011; Marzetta and Hochwald, 1999; Qatawneh, 2005).
| Fig. 6: | BER performance of GO-MC-CDMA and MC-CDMA systems |
COMPARISON OF BER PERFORMANCE OF GO-MC-CDMA AND MC-CDMA SYSTEMS IN RAYLEIGH FADING CHANNELS
Figure 6 illustrates the Bit Error Rate (BER) performance versus Signal to Noise Ratio (SNR) for GO-MC-CDMA and MC-CDMA systems in two paths Rayleigh fading channel, fading channel variance in urban region is -6 dB. The GO-MC-CDMA system gives better BER performance, as compared with MC-CDMA system.
Figure 7 shows another comparison between GO-MC-CDMA and MC-CDMA systems corresponding to the number of active users at SNR = 18 dB. The GO-MC-CDMA gives a good result when the group size is small. The bit error rate increases when the number of active users per group is increased while the MC-CDMA gives a fixed error rate, when the number of active users is increased.
| Fig. 7: |
BER performance of GO-MC-CDMA and MC-CDMA
systems vs. different No. of active users |
| Fig. 8: |
BER performance of GO-MC-CDMA system
vs. No. of active users, using different types of data detection techniques |
If the load is not full linking in GO-MC-CDMA system, the bit error rate also decreases.
Figure 8 shows the Bit Error Rate (BER) versus Signal to Noise Ratio (SNR) of GO-MC-CDMA system versus number of active users using different type data detectors techniques. The three stages PIC detector gives a better BER performance while SIC detector is reducing the error rate at SNR values (7-11) dB.
| Fig. 9: | BER performance of GO-MC-CDMA for different
diversity combining techniques |
For high number of active users, SIC detector is efficient because the number of stages is equal to the number of active users but the time delay between the users is very high. PIC detector also has a good result when the number of active users is increased and it becomes more complex for design.
COMPARISON OF BER PERFORMANCE OF GO-MC-CDMA USING DIFFERENT NUMBER COMBINING TECHNIQUES
Figure 9 shows the advantage of using different diversity combining techniques to improve bit error rate in GO-MC-CDMA system. The SD and EGC combining improve the bit error rate slightly as compared with non combining system. MRC technique gives better BER performance as compared with SD and EGC combining diversity techniques, but it is more complex in the design.
Figure 10 shows the effect of using MRC combining with different number of branches. As the number of branches is increased, the bit error rate decreases and the complexity of system becomes expensive.
COMPARISON OF THE EFFECT OF NEAR-FAR PROBLEM ON THE PERFORMANCE OF GO-MC-CDMA SYSTEM.
Figure 11 shows the effect of near-far problem in GO-MC-CDMA system with Minimum Mean Square Error (MMSE) detection, where the power of first user is less than all other users power by 3 dB. The bit error rate difference is small compared with non effect problem (0 dB).
| Fig. 10: |
BER performance of GO-MC-CDMA using different
No. of branches for Maximum Ratio Combining (MRC) technique |
| Fig. 11: | Effect of near-far problem on the performance
of GO-MC-CDMA system with minimum mean square error detection |
This means that the MMSE is an efficient detector to overcome this problem.
Figure 12 and 13 show the effect of near-far problem in GO-MC-CDMA system using Successive Interference Cancelation (SIC) and three stages of Parallel Interference Cancellation (PIC) detectors.
For the PIC detector gives error rate performance as the same SIC detector error rate performance at all SNR values.
| Fig. 12: |
Effect of near-far problem on the performance
of GO-MC-CDMA system with SIC detection |
| Fig. 13: |
Effect of near-far problem on the performance
of GO-MC-CDMA system with PIC detection |
CONCLUSION
In this study, the result of comparison of the performance of Group Orthogonal Multi Carrier Code Division Multiple Access (GO-MC-CDMA) and multicarrier code division multiple access signal in frequency selective fading channel has been investigated. The first comparison of BER performance of GO-MC-CDMA and MC-CDMA systems was in Rayleigh fading channels.
Also the results shows another comparison between GO-MC-CDMA and MC-CDMA systems corresponding to the number of active users at SNR = 18 dB. The GO-MC-CDMA gives a good result when the group size is small. The bit error rate increases when the number of active users per group is increased while the MC-CDMA gives a fixed error rate. Another comparison of BER performance of GO-MC-CDMA using different number combining techniques as selection diversity, maximal ratio combining and equal gain combining. Selection Diversity (SD). Finally the BER Comparison of the effect of near-far problem on the performance of GO-MC-CDMA system using Successive Interference Cancelation (SIC) and three stages of Parallel Interference Cancellation (PIC) detectors. For the PIC detector gives error rate performance as the same SIC detector error rate performance at all SNR values.