Non-Orthogonal Multiple Access (NOMA) for 5G and beyond

Non-Orthogonal Multiple Access

Non-Orthogonal Multiple Access (NOMA) refers to a method of multiple access in wireless communication where different devices are not separated in time or frequency. It has the potential to increase capacity in certain scenarios, although it was initially down- prioritized during the early stages of NR development.

Beyond the First Release of 5G

20.3 Non-orthogonal Multiple Access

NR primarily uses orthogonal multiple-access where different devices are separated in time and/or frequency. However, non-orthogonal access has the potential to increase capacity in some scenarios.

During the early stages of NR development, non-orthogonal multiple access (NOMA) was briefly studied but down-prioritized. Nevertheless, studies on NOMA are ongoing in release 15 and may become relevant for NR in later releases.

Non- Multiple Access Techniques in Emerging Wireless Systems Orthogonal

Non-orthogonal multiple access (NOMA) is one of the most promising radio access techniques in next-generation wireless communications. Compared to orthogonal frequency division multiple access (OFDMA), which is the current de facto standard orthogonal multiple access (OMA) technique, NOMA offers a set of desirable potential benefits, such as enhanced spectrum efficiency, reduced latency with  high reliability, and massive connectivity. The baseline idea of NOMA is to serve multiple users using the same resource in terms of time, frequency, and space.

The available NOMA techniques can broadly be divided into two major categories, i.e., power- domain NOMA and code-domain NOMA. Code- domain NOMA can further be classified into several multiple access techniques that rely on low-density spreading and sparse code multiple access. Other closely related multiple access schemes in this context are lattice- partition multiple access, multi-user shared access, and pattern-division multiple access.

Recent studies demonstrate that NOMA has the potential to be applied in various fifth generation (5G) communication scenarios, including Machine-to-Machine (M2M) communications and the Internet-of-

Things (IoT). Moreover, there are some existing evidence of performance improvement when NOMA is integrated with various effective wireless communications techniques, such as cooperative communications, multiple-input multiple-output (MIMO), beamforming, space- time coding, network coding, full-duplex, etc. Given all advancements and experimental outcomes, standardization of NOMA has been established for the next-generation American digital TV standard (ATSC 3.0) under the term layered-division multiplexing (LDM), and has been initiated for the third generation partnership project (3GPP) under the name multi-user superposition transmission (MUST).

Since the principle of NOMA allows multiple users to be superimposed on the same resource, this leads to interference for such systems. Consequently, existing resource management and interference mitigation techniques, especially for ultra-dense networks, need to be revisited due to the incorporation of additional interference this new technology brings. For the similar reason, beamforming and the resultant other problems (e.g., precoding) in massive-MIMO systems introduce additional challenges and need to be solved in order to achieve full utilization of these technologies. From the perspective of physical layer, existing channel coding, modulation and estimation related problems need to be revised as well. Cognitive, cooperative, and visible light communications all are conducive paradigms under NOMA systems compared to conventional systems. However, the resultant evolved problems due to the incorporation of this new technology need to be solved before acquiring benefits from these paradigms.

Although NOMA technique offers numerous advantages, the enhanced information sensing ability of more users via this technique, leads to higher security and privacy threat.

2. Advantages of NOMA in 5G:

Improved Spectral Efficiency: By allowing multiple users to share the same resources, NOMA improves spectral efficiency, making better use of available bandwidth.

Increased Capacity: NOMA supports more users simultaneously, which is critical for 5G networks that need to accommodate massive machine-type communications (mMTC) and enhanced mobile broadband (eMBB) scenarios.

Fairness: NOMA can enhance fairness by allocating more power to users with weaker channel conditions, ensuring that users far from the base station or in poorer conditions can still achieve acceptable performance.

Low Latency: NOMA reduces resource allocation overhead, which can result in lower latency for users, important for ultra-reliable low-latency communication (URLLC) in 5G.

3. Key Techniques in NOMA:

Successive Interference Cancellation (SIC): At the receiver end, stronger signals (intended for users with better channel conditions) are decoded first and subtracted from the superimposed signal. This process continues until the weakest signal is decoded.

Power Domain NOMA: Users are distinguished by their power levels, with higher power allocated to users with weaker channels and lower power to users with stronger channels.

Cooperative NOMA: A variant where stronger users help relay information to weaker users, enhancing overall system performance.

4. NOMA in Beyond 5G:

Integration with other technologies: NOMA will likely be combined with other advanced technologies like massive MIMO, millimeter-wave (mmWave) communication, and full-duplex communications to further enhance system capacity and performance.

Use in Hybrid Systems: Future wireless networks will likely use NOMA in conjunction with other access technologies to handle diverse service requirements, including IoT, autonomous vehicles, and augmented reality.

Enhanced Network Slicing: NOMA will support network slicing, allowing multiple virtual networks to coexist, each optimized for different service types.

5. Challenges:

Complexity of SIC: While NOMA offers many benefits, successive interference cancellation is computationally intensive, and its accuracy can degrade in poor channel conditions.

User Pairing: Efficient user pairing (which users should share the same resources) is crucial for optimal

NOMA performance. Poor pairing can negate the benefits of NOMA.

Security and Privacy: Since users share the same frequency bands, ensuring the privacy of each user's data is a challenge.

6. Applications:

eMBB: In scenarios where high data rates are required for many users, such as in crowded urban areas, NOMA can significantly increase capacity.

mMTC: NOMA can efficiently support massive IOT networks by accommodating a large number of low-power, low-data-rate devices.

V2X (Vehicle-to-Everything) Communication: As autonomous vehicles and connected cars become more prevalent, NOMA can help manage the high density of communications needed for vehicle-to-vehicle and vehicle-to-infrastructure links.

NOMA is poised to play a critical role in 5G and beyond, enabling highly efficient, scalable, and flexible wireless networks.