NOMA based resource allocation and mobility enhancement framework for IoT in next generation cellular networks

With the unprecedented technological advances witnessed in the last two decades, more devices are connected to the internet, forming what is called internet of things (IoT). IoT devices with heterogeneous characteristics and quality of experience (QoE) requirements may engage in dynamic spectrum market due to scarcity of radio resources. We propose a framework to efficiently quantify and supply radio resources to the IoT devices by developing intelligent systems. The primary goal of the paper is to study the characteristics of the next generation of cellular networks with non-orthogonal multiple access (NOMA) to enable connectivity to clustered IoT devices. First, we demonstrate how the distribution and QoE requirements of IoT devices impact the required number of radio resources in real time. Second, we prove that using an extended auction algorithm by implementing a series of complementary functions, enhance the radio resource utilization efficiency. The results show substantial reduction in the number of sub-carriers required when compared to conventional orthogonal multiple access (OMA) and the intelligent clustering is scalable and adaptable to the cellular environment. Ability to move spectrum usages from one cluster to other clusters after borrowing when a cluster has less user or move out of the boundary is another soft feature that contributes to the reported radio resource utilization efficiency. Moreover, the proposed framework provides IoT service providers cost estimation to control their spectrum acquisition to achieve required quality of service (QoS) with guaranteed bit rate (GBR) and non-guaranteed bit rate (Non-GBR)

Outage-constrained resource allocation in uplink NOMA for critical applications

In this work, we consider the resource allocation problem for uplink non-orthogonal multiple access (NOMA) networks whose users represent power-restricted but high priority devices, such as those used in sensor networks supporting health and public safety applications. Such systems require high reliability and robust resource allocation techniques are needed to ensure performance. We examine the impact on system and user performance due to residual cancellation errors resulting from imperfect successive interference cancellation (SIC) and apply the chance-constrained robust optimization approach to tackle this type of error. In particular, we derive an expression for the user outage probability as a function of SIC error variance. This result is used to formulate a robust joint resource allocation problem that minimizes user transmit power subject to rate and outage constraints of critical applications. As the proposed optimization problem is inherently non-convex and NP-hard, we apply the techniques of variable relaxation and complementary geometric programming to develop a computationally tractable two-step iterative algorithm based on successive convex approximation. Simulation results demonstrate that, even for high levels of SIC error, the proposed robust algorithm for NOMA outperforms the traditional orthogonal multiple access case in terms of user transmit power and overall system density, i.e., serving more users over fewer sub-carriers. The chance-constrained approach necessitates a power-robustness trade-off compared to non-robust NOMA but effectively enforces maximum user outage and can result in transmit power savings when users can accept a higher probability of outage

The Application of MIMO to Non-Orthogonal Multiple Access

This paper considers the application of multiple-input multiple-output (MIMO) techniques to non-orthogonal multiple access (NOMA) systems. A new design of precoding and detection matrices for MIMO-NOMA is proposed and its performance is analyzed for the case with a fixed set of power allocation coefficients. To further improve the performance gap between MIMO-NOMA and conventional orthogonal multiple access schemes, user pairing is applied to NOMA and its impact on the system performance is characterized. More sophisticated choices of power allocation coefficients are also proposed to meet various quality of service requirements. Finally computer simulation results are provided to facilitate the performance evaluation of MIMO-NOMA and also demonstrate the accuracy of the developed analytical results

Enabling Quality-Driven Scalable Video Transmission over Multi-User NOMA System

Recently, non-orthogonal multiple access (NOMA) has been proposed to achieve higher spectral efficiency over conventional orthogonal multiple access. Although it has the potential to meet increasing demands of video services, it is still challenging to provide high performance video streaming. In this research, we investigate, for the first time, a multi-user NOMA system design for video transmission. Various NOMA systems have been proposed for data transmission in terms of throughput or reliability. However, the perceived quality, or the quality-of-experience of users, is more critical for video transmission. Based on this observation, we design a quality-driven scalable video transmission framework with cross-layer support for multi-user NOMA. To enable low complexity multi-user NOMA operations, a novel user grouping strategy is proposed. The key features in the proposed framework include the integration of the quality model for encoded video with the physical layer model for NOMA transmission, and the formulation of multi-user NOMA-based video transmission as a quality-driven power allocation problem. As the problem is non-concave, a global optimal algorithm based on the hidden monotonic property and a suboptimal algorithm with polynomial time complexity are developed. Simulation results show that the proposed multi-user NOMA system outperforms existing schemes in various video delivery scenarios.Comment: 9 pages, 6 figures. This paper has already been accepted by IEEE INFOCOM 201