NON ORTHOGONAL MULTIPLE ACCESS FOR 5G COMMUNICATION SYSTEMS Megha Singh
M. Tech Scholar, BTIRT Sagar Mr. Vikash Panthi
Panthi Asstt. Prof., EC Deptt, BTIRT Sagar
Abstract - As the newest member of the multiple access family, non-orthogonal multiple access (NOMA) has been recently proposed for 3GPP Long Term Evolution (LTE) and imagined to be a core component of the 5th generation (5G) mobile network for its inherent ability of spectrum enhancement. NOMA provides multiple users with simultaneous frequency/code but separate power levels, which significantly increases the spectral performance over standard orthogonal multiple entries (OMA). It is also significant to mention that the OMA-based approaches cannot satisfy the rigorous emergent demands, which includes larger spectral performance, very low latency and large access to equipment with the increasing count of the users. The NOMA theory is the solution to increase the spectral quality, thus enabling a certain degree of interference in multiple accesses at receivers. Non-orthogonal multiple access (NOMA) is one of the capable contenders to achieve the vision of 5G wireless communications. Supporting a higher number of users than available orthogonal resources is the key feather of NOMA. In this article, the basic principle of NOMA has been reviewed and compared with other orthogonal multiple accesses (OMA).Due to massive connectivity and increasing demands of various services and data hungry applications, a full-scale implementation of the fifth generation (5G) wireless systems requires more effective radio access techniques. In this regard, non- orthogonal multiple access (NOMA) has recently gained ever-growing attention from both academia and industry. Compared to orthogonal multiple access (OMA) techniques, NOMA are superior in terms of spectral efficiency, energy efficiency and data transfer rate and is thus appropriate for 5G and beyond. In this article, we provide an overview of NOMA principles and applications. Specifically, the article discusses the fundamentals of NOMA with single and multiple antennas. NOMA is compared with OMA in terms data transfer rate, energy efficiency, spectral efficiency. Simulation is done in MATLAB and comparative graphical plots are obtained. It is found that NOMA performs better than OMA and thus it is suited for 5G requirements.
1 INTRODUCTION
Non-orthogonal Multiple Access (NOMA) is always considered the best candidate for Fifth-Generation (5G) wireless communication network as it demands mass connectivity, low latency and increased data rate. In the literature, Orthogonal Multiple Access (OMA) is compared with NOMA for the sum rate and capacity, where NOMA leads the OMA in terms of capacity and huge connectivity due to the freedom of non-orthogonality.
However, these comparisons are carried out rather for single antenna system or a limited number of multiple transmitting antennas. For multiple-input-multiple- output (MIMO) system, the capacity comparison is quite different for NOMA and OMA, especially where the number of users out-numbers the transmitting antenna. Non-Orthogonal Multiple Access (NOMA) has attracted the attention of the researchers since very long because of its
spectral efficiency and ability to handle mass connectivity by its non- orthogonality.
The concept of NOMA is very simple as it holds the capability for multi- user transmission allocating the same frequency, time or code resources to all the users simultaneously. Superposition algorithm is applied to merge the user’s data by allocating the different power levels to each user and the combined signal is transmitted in the same beam- forming scheme. In NOMA, users are grouped because of different channel condition at each user, typically the poor channel gain is assumed at the far user because its distance from the BS is larger, while the channel at the near user is assumed to be the better and these two users are grouped in the system. Far user is located at the edge of the cell, far from BS and the near user is usually located at
the centre of the cell, near to the BS. Far users are allocated with high transmission power because of the poor channel gains, and it needs to suppress the interferences occurred due to the presence of other user’s signal in the same transmission. At the receiver side, NOMA implies successive interference cancellation (SIC) technique to decode the signal. Usually, the user near to the BS will decode the high-power user’s data first and its interference is cancelled out using SIC. Therefore, in the power domain NOMA, it is not necessary to assign high power to the user near to the BS to achieve increased data rate. To perform SIC, accurate channel state information
(CSI) is compulsory to assume that there must not be any significant remaining interference at the user performing SIC.
Figure 1 shows the general architecture of NOMA. The most important part of this technology is the concept of SIC. This differs NOMA form normal orthogonal multiple access. As a remedy, non- orthogonal multiple access (NOMA) has recently been recognized as one of the key enabling technologies to fulfill these ambitious demands of beyond 5G networks. On the contrary of orthogonal multiple access (OMA), NOMA enables users to share the same resource blocks (RBs) at the same time and distinguishes users by their varying power levels.
Fig. 1 Architecture of NOMA 2 RELATED WORK
There exists a large body of works that addressed the resource allocation problems for OFDMA [2] and NOMA [17]
techniques in 5G. In OFDMA setup, the proposed resource allocation problems are consisting of subcarrier and power allocation. Meanwhile, in NOMA, one needs to optimize user pairing along with power and sub-carrier allocation [14] for both NOMA and OFDMA, network optimization is often posed using non- deterministic polynomial-time (NP) - hard problems. The authors in [16] studied the problem of analytically characterizing the optimal power allocation for NOMA, considering various objective functions and constraints. To reduce the computational complexity, a new user pairing and power allocation scheme is proposed in [8]. Meanwhile, the works in [9] have studied advanced approaches that combine NOMA with other emerging transmission techniques, such as full- duplex communications and multiple-
input, multipleoutput (MIMO) systems and heterogeneous systems. This idea of utilizing a hybrid of OMA and NOMA in 5G has been recently studied in [11] and [12]. In [5], considering three different regions in the cell based on the distance, the access technology is chosen according to the region of users without any optimization and it is predetermined for each region. In particular, in [11], the access technology selection is not dynamically optimized taking into account the instantaneous CSI. In [12], a heterogeneous network in which OMA and NOMA coexist is considered. In such a network, four generic pairing methods for NOMA with a heuristic pairing cost function are studied. When those methods cannot achieve a suitable performance level OMA will be used for that subcarrier.
3 PROPOSED WORK
In this article Non orthogonal multiple accesses has been proposed as a
candidate for future 5G communication system. Performance of OFDMA and NOMA techniques is analyzed to find out the best candidate for 5G. To understand the performance of NOMA in comparison with OFDMA, 2 users have taken into consideration.
Figure 2 shows the architecture of NOMA.
The architecture of NOMA includes transmitter, channel and receiver.
Downlink NOMA is under consideration here. Base station is worked as transmitter end and User equipment is worked as receiver. SIC receiver is the main part of NOMA network.
Fig. 2 Architecture of NOMA Here 2 users are taken under
consideration; signals are sent to both the users (i.e. user1 and user2) simultaneously from base station. SIC is applies for user 1 during the decoding of message signal. The concept of SIC make this technology different form OMA.
Figure 3 shows the architecture of OFDMA. The architecture of OFDMA includes receiver, channel and transmitter. At receiver end signal is processed before transmitting to the channel. Main job is to add guard interval in the signal before its transmission.
Fig. 3 Architecture of OFDMA 4 RESULT DISCUSSION
Results for this project work have been obtained on the basis of simulation done in MATLAB. Simulation is carried for OFDMA and NOMA simultaneously.
Performance of both the techniques is checked on the basis of energy efficiency, spectrum efficiency and data transfer rates. Figure 4 shows the data rates comparison between NOMA and OMA
(here OFDM is employed as OMA technique) multiplexing techniques. The plot obtained is about the data transfer rate of two simultaneous users with a common network for both techniques.
Two users are taken under consideration in a common network. The same process if applied for NOMA and OMA. A comparative 2D curve is plotted, x-axis of the plot shows data rate of user 1 in bps
and y-axis of the plot shows data rate of user 2 in bps. The red coloured curve is for NOMA and black curve is for OMA. On analyzing the curves it can be concluded that red curve is showing higher data transfer rate than black curve. Figure 5 shows the data rates of NOMA and OMA in some rural area. Total 30 trials were performed simultaneously for both the technique. Average sum of data rate is calculated in bps. Red curve is showing average sum of data rate for NOMA and blue curve is showing average sum of data rate for OMA. It is very clear from the plot that NOMA performs better in terms of data rate. And hence it can be concluded that NOMA is better option for 5G. Figure 6 shows comparison of energy efficiency and spectral efficiency between NOMA and OMA. It is clear from the figure that NOMA can yield higher spectral efficiency as well as energy efficiency compared to OMA. Moreover, NOMA can take advantage of user differences in the power domain to provide services for multiple users connected to the same resource. The power domain characteristics of NOMA can help support massive NOMA connections and meet a range of quality services.
Fig. 4 Comparison of data rates between NOMA and OFDMA
Fig. 5 Comparison of sum data rate between NOMA and OFDMA
Fig. 6: Comparison of EE v/s SE curve between NOMA and OFDMA 5 CONCLUSION
The work presented in this paper reported a thorough analysis of the optimal choice of the NOMA for 5G applications. The systematic discussion is useful to differentiate several multiple access techniques and especially it all started with the OMA. The OMA is analyzed in terms of data transfer rates, SE and EE, the need for MA techniques of 5G. The important findings are sufficient to enumerate the disadvantages of OMA and its short comings which are not favorable for the 5G. The research focuses on the NOMA in cellular networks, which in future 5G networks will be considered as a promising technology. This research presents the following three aspects:
(1) The precepts of NOMA are developed, including techniques such as SIC, NOMA knowledge theoretical research.
(2) The possible convergence of NOMA and the new technology and their
contribution to other advances in wireless broadcasting.
(3) Comparison between OMA and NOMA is done in terms of data transfer rate, spectral efficiency and energy efficiency.
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