The cellular network has evolved all the way from 1G to 4G or LTE network. The 5G network is still under research and is expected to roll out by the year 2020. Some of the improvements the network seeks to have are based on the significant reduction of the end-to-end latency (Kishiyama, Benjebbour and Ishii 475). The innovations in the industry have led to a great need for high data rate applications due to the use of IoT and the mobile internet. For instance, the 5G network is expected to provide speeds of up to ten to twenty times the peak data rate in 4G networks (Riazul Islam, Avazov and Dobre). The latency that is attributed to the end-to-end round-trip delay is expected to reduce to about 1 millisecond. When compared to the 4G network, it rates at about one-fifth of the LTE latency (Kishiyama, Saito and Benjebbour 477). The cellular network is founded on the radio access technology which simulates a radio access network. The RAN uses channels in providing the mobile terminals with a connection to the core network. The system capacity needs to be improved by designing and implementing suitable multiple access techniques. These techniques can be stated under two different approaches as orthogonal multiple access and non-orthogonal multiple access (Haci, Wang and Zhu 5). The orthogonal technique has different basis functions that enable the receiver to separate, in entirety, the wanted signals from the unwanted signals. It is easier explained that when different users send their message signals, these signals tend to be orthogonal to each other (Saito, Benjebbour and Kishiyama 772). Some of the common schemes implemented under this approach include the Time Division Multiple Access and the Orthogonal Frequency Division Multiple Access. The TDMA allows several users to share the same frequency channel by sharing the assigned time slots (Adachi, Ding and Poor 550). The OFDMA is a multiple access scheme that allows the different sub-carrier frequencies to serve the subscribers in an orthogonal manner.
The non-orthogonal multiple access approach, on the other hand, is known to allow multiple users within the same cell to access one frequency channel at the same time. There are a number of merits that come from doing so such as improving the spectral efficiency, the higher cell-edge throughput, relaxed channel feedback and the low transmission latency (Madihian, Gitlin and Sang 570). The approach ensures that only the received signal strength is required and that no scheduling requests from the user to the base station are required. There are two techniques that employ the NOMA approach namely, the power domain and the code domain NOMA. The non-orthogonal multiple access (NOMA) tends to exploit the power domain multiplexing. It performs superposition coding at transmission and successive interference cancellation at reception (Wunder, Jung and Kasparick 102). Research studies show that a pair of users can be served by NOMA when their channel gains are considerably different. The power allocation strategies play a pivotal role in capacity enhancement. The cancellation order at every receiver is always to decode the weaker users before decoding its own data. Any network improvement seeks to achieve a greater system efficiency (Vakilian, Wild and Schaich 225). The LTE researchers have reviewed the NOMA as a promising multiple access scheme for the future radio access. The users with better channel conditions decode the messages for the users with poor connections to the base station. Strong users to weak user’s communications can be implemented by the UWB and the BT (Poor, Tsiropoulos and Dobre).
The cellular networks’ performance is largely limited by interference. Interference is human-designed and it can be separated from noise as it is caused by gadgets or devices within the same network. With the increase accessibility to mobile devices due to their affordability, there is more interference within the cellular network. Some methods have been devised to reduce interference, for instance, the designers of the base station tend to achieve a minimum required transmission power rate so that the same low power can be transmitted or received by the different gadgets within a cell (Dong, Dong and Feng 3). As a result, there is less interference caused to other devices in the network (Creative World 9). The use of NOMA is a progressive move from the time, frequency and code domains. In the current technologies, the receiver uses rake receiver to detect and minimize interference. The use of NOMA approach has led researchers to attempt enhancements on the performance of other technologies in the cellular network family. These networks are such as the multiple-input multiple-output networks, cooperative communication networks, light communications as well as the relay communication networks. Some of the common schemes under NOMA are as shown below,
Figure 1 A simple classification of NOMA techniques
There are two basic techniques that play an important role in the comprehension of the class of NOMA, specifically the power domain NOMA. The superposition coding is a technique of simultaneously communicating information to several receivers by a single source. The SC allows the transmitter to send information initiated my multiple users at the same time. This is achieved by setting up the transmitter to encode information relevant to each user. The superposition coding transmitter needs to have two point-to-point encoders that map their respective inputs to complex-valued sequences of the two-user signal (Nikopour and Baligh).
The AMPS terminal can transmit at six to eight diverse power levels while increased in steps of 4dB. The message from the Base Station controls the power level of the dynamic terminal. The power in this case stays the same during the conversion. The DTX where the power varies depends upon the speech activity (Al-Imari, Imran and Tafaxolli 385).
Table 1 Summary of interference management techniques reviewed
The cellular network has had a great problem trying to eliminate the latency in the systems it operates. The latency is projected to reduce to 1 millisecond in the 5G network. There is a lot of interference during reception for the multiple access by subscribers. The drawback caused by the interference is that it decreases the sensitivity at the receiver end. The lower the sensitivity, the more the system puts high demands on the linearity in the Radio Frequency and in the base band receiver blocks. There are no setup techniques or schemes to enable the interference cancellation in the current networks. To determine the most reliable approach towards the interference cancellation and maintain or improve the performance of the cellular network.
The cellular networks’ performance is largely limited by interference. Interference is human-designed and it can be separated from noise as it is caused by gadgets or devices within the same networkInvalid source specified.. To determine the techniques that can be implemented to ensure the interference cancellation at the receiver end.
This research seeks to determine the interference factors and develop the class of techniques that may demodulate and decode the desired information. These techniques can use this information along with channel estimates to cancel received interference from the received signal. The research seeks to find a solution to the interference and ensures the cancellation of the same albeit lowering the system performance. Another key focus is on the throughput enhancement by performing interference cancellation.
It is important to perform the given investigation since; the researchers have been looking for ways to minimize interference in the power domain by testing the power used at transmission. The investigation aims at arriving at a solution that yields interference cancellation without degrading the cellular network performance (Su, Yu and Kim 7). The investigation results will enable the researchers to make better recommendations to the RFC for the 5G design and LTE network improvements.
The investigation of the operation on the current networks is done on the TDMA, FDMA, and CDMA. The three techniques are reviewed to determine their role in the self-interference or the co-channel interference (A, Saito and Kishiyama 773). A new technique is proposed as the coding and modulation of NOMA to ensure that the interference from cell to cell rates are cancelled as predicted by the theory and can be actualized in the real world. The coding and modulation is achieved by the pulse amplitude modulation technique. The technique uses the PAM together with gray labelling and turbo codes as applied to NOMA. The MATLAB Simulink R2017a software is used as the simulation implementation tool.
To perform the investigation, the researcher uses the MATLAB Simulink to perform tests and create models:
The model is designed and noises and interference are introduced in its vicinity. The system that performs the interference cancellation employs an adaptive filter. The system comprises of a primary signal that has both the desired signal as well as the undesired noise and the reference signal. The reference signal usually has a measured copy of the noise. The adaptive filter is able to suppress the interference in cases where the primary signal and the measured noise in the reference signal are correlated (Umehara and Y 325).
The algorithm is controlled by a parameter and new coefficients can be obtained as,
To attain convergence,
A downlink test signal was used in the system. When the signal was passed through a low pass signal,
The frequency response when tested at different sample rates and quantized differently,
Another test was carried out to show he similarities between the interference signal and its replica at double the sample rate.
Another test was carried out to show the effect of interference in the signal. The Butterworth low pass filter was used in the interference creation block and later the signal was adjusted with a mean delay to obtain the following signal output,
To show the convergence of the LMS coefficient when a large sample size is used,
The algorithm in the simulator at this point was calculated to,
Testing for interference power against the desired power to determine how much power should be designed as the transmission power for the base Station transmitter,
The interference signal is steadily suppressed after the cancellation block has been switched on. The standard deviation of the thermal noise is represented by the red line on the results (Knopp and Humblet). It is the desired signal. The sample step size used in this test is T=0.0001 seconds.
Conclusion
In a nutshell, the proposal demonstrates the implementation of NOMA as the solution to the throughput performance flaws of the former systems. The interference cancellation is achieved using an interference cancellation block in the cellular system network (Wang, Wang and Lu 3). The cancellation is achieved by implementing an adaptive filter which can be a low pass filter or a band pass filter depending on the measure of the noise signal (Viswanath and Tse).
The work to be done in this research is as detailed in the work breakdown structure below,
|
Activities |
Milestones |
|
1. Research on NOMA |
21st May 2018 |
|
2. Interference Cancellation techniques |
31st May 2018 |
|
3. Research Proposal Write-up |
8th June 2018 |
|
4. MATLAB Simulation |
14th June 2018 |
|
5. Successive interference cancellation: Superposition coding and decoding |
22nd June 2018 |
|
6. Research Project completion & Documentation |
28th June 2018 |
|
7. Review and correction |
3rd July 2018 |
|
8. Presentation |
9th July 2018 |
References
Adachi, F, Z Ding and H V Poor. “The application of MIMO to non-orthogonal multiple access.” IEEE Trans. Wireless Communication (2016): 537-552. Print.
Al-Imari, M, et al. “Performance Evaluation of low density spreading multiple access.” Proceedings 8t International Wireless Communication Mobile Computing Conference. Ed. IEEE. IEEE, 2012. 383-388. Print.
Creative World 9. Abstract on Interference Cancellation for Cellular Systems. 2011. Online. 28 March 2018.
Dong, et al. “Impact of symbol misalignment on 5G non-orthogonal multiple access.” Wireless and Optical CommunicationConference (WOCC) (2016): 1-4. Online.
Haci, Huseyin, Jiangzhou Wang and Huiling Zhu. “A novel interterence cancellation technique for non-orthogonal multiple access (NOMA).” Global Communications Conference (GLOBECOM) (2015): 1-6. Print.
Kishiyama, Y, et al. “Evolution concept and candidate technologies for futrue steps of LTE-A.” Proceedings IEEE ICCS2012 (2012): 473-477. Online.
—. “Non-orthogonal multiple access (NOMA) for future radio access.” IEEE VTC, (2013): 34-37. Print.
Knopp, R and P.A Humblet. Information Capacity and Power control in a single cell multiuser communications. Seattle, USA: IEEE ICCS, 1995. Online.
Madihian, M, et al. “A Flexible downlink scheduling scheme in cellular packet data systems.” IEEE Trans. Wireless Communication (2006): 568-577. Online.
Nikopour, H and H Baligh. “Sparse code multiple access.” Proceeding, IEEE International Symposium Pers.Indoor Mobile radio Communication. 2013. 332-336.
Poor, V H, et al. “Capacity comparison between MIMO-NOMA and MIMO-OMA with multiple users in a cluster.” IEEE Selection Areas Communication (n.d.).
Riazul Islam, S M, et al. “Power-Domain Non-orthogonal multiple access (NOMA) in 5G systems:Potential and Challenges.” Communications Surveys & Tutorials, IEEE (2017): 721-742. Print.
Saito, Y and Y Kishiyama. “Concept and practical considerations of non-orthogonal multiple access (NOMA) for future radio access.” Proceeedings IEEE ISPACS2013. Ed. A Benjebbour. Naha, Japan, 2013. 770-774. Online.
Saito, Y, et al. “System level performance evaluation of downlink non-orthogonal multiple access (NOMA).” IEEE PIMRC, London (2013): 12-25. Online.
Su, Xin, et al. “Interference cancellation for non-orthogonal multiple access used in future wireless mobile networks.” EURASIP Journal on Wireless Communications and networking (2016): 1-9. online.
Umehara and Kishiyama Y. “Enhancing user fairness in non-orthogonal access with successive interference cancellation for cellular downlink.” Proceeding of IEEE ICCS (2012): 324-328. Online.
Vakilian, V, et al. “Universal filtered multi-carrier technique for wireless systems beyond LTE.” Proc. IEEE Globecom Broadband Wireless Access Workshop (2013): 223-228. Print.
Viswanath, P and D Tse. Fundamentals of wireless communication. Cambridge: Cambridge University Press, 2005. Print.
Wang, B, et al. “Comparsion study of non-orthogonal multiple access schemes for 5G.” Proceedings of IEEE International Symposium on BMSB (2015): 1-5. Online.
Wunder, G, et al. “5GNOW: Non-orthogonal, asynchronous waveforms for future mobile applications.” IEEE Communications magazines (2014): 97-105. Print.
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