Orthogonal time–frequency space (OTFS) is being pursued in recent times as a suitable wireless transmission technology for use in high-mobility scenarios. In this article, we propose nonorthogonal multiple access (NOMA) based OTFS which may be called NOMA-OTFS system and evaluate its performance from a system-level and link-level perspective. The challenge lies in the fact that while OTFS transmission technology is known for its resilience to high-mobility conditions, while NOMA is known to yield high spectral efficiency (SE) in low-mobility scenarios in comparison to orthogonal multiple access (OMA). We present a minimum mean square error (MMSE)-successive interference cancellation based receiver for NOMA-OTFS, for which we derive expression for symbol-wise postprocessing SINR in order to evaluate system sum SE. We develop power allocation schemes to maximize the sum SE in the high-mobility version of NOMA. We further design a realizable codeword-level SIC (CWIC) receiver using low-density parity check (LDPC) codes along with MMSE equalization for evaluating link-level performance of such practical NOMA-OTFS system. The system-level and link-level performance of the proposed NOMA-OTFS system are compared against benchmark OMA-OTFS, OMA-orthogonal frequency division multiplexing (OMA-OFDM) and NOMA-OFDM schemes. From system-level performance evaluation, we observe interestingly that NOMA-OTFS provides higher system sum SE than OMA-OTFS. When compared to NOMA-OFDM, we find that outage SE of NOMA-OTFS is improved at the cost of decrease in mean SE. The link-level results additionally show that the developed CWIC-based NOMA-OTFS receiver performs significantly better than NOMA-OFDM in terms of block error rate, goodput, and throughout.

Nonorthogonal Multiple Access With Orthogonal Time–Frequency Space Signal Transmission

The Internet-of-Things (IoT) system is a novel networking technology that connects smart communication devices through Internet-enabled infrastructure to enhance wireless communications. The explosive growth of IoT devices connectivity has increased energy consumption drastically that raises economic and physical environment concerns. To meet the challenges posed by high energy consumption, energy efficiency has become an urgent need for IoT networks recently. This article examines resource allocation and formulates the joint optimization problem for power allocation and user selection subject to the maximum transmit power and different Quality-of-Service (QoS) requirements, to achieve an improved energy efficiency performance in IoT networks under channel uncertainty. Furthermore, the formulated optimization problem is mixed-integer nonlinear programming (MINLP) with no practical solutions. Due to the nonconvexity and NP-hardness of the MINLP problem, the primal optimization problem is transformed into a convex problem and solved optimally for power allocation and user selection, by applying the Lagrangian dual decomposition method and the Kuhn–Munkres algorithm, respectively. An efficient joint iterative algorithm is proposed to maximize energy efficiency performance with guaranteed convergence within few numbers of iterations. The numerical results validate the robustness of the proposed algorithm and significantly show its superior performance as compared with the baseline algorithms.

Energy-Efficient Joint Power Allocation and User Selection Algorithm for Data Transmission in Internet-of-Things Networks

201 DOI: 10.37398/JSR.2021.650126 Abstract: The escalating demand for wireless data traffic has prompted the need to explore the area of spectrum suitable for meeting the expected requirement. Sub 6 GHz is highly occupied so the researchers are moving towards mm-wave where a spectrum range from 30-300 GHz is available. Channel modeling and hybrid beam-forming has become integral part to realize a system in mmwave frequency band. In this paper we trace the advances in hybrid beam-forming for mm-wave Massive MIMO communication in the context of hybrid beam-forming architectures, and pre-coding techniques in different channel environment. We have also compared the spectral efficiency of different pre-coding techniques employing different antenna array size at the Base Station.

/pdf/a-survey-on-hybrid-beamforming-in-mmwave-massive-mimo-system-4dcj9bvw47.pdf

A Survey on Hybrid Beamforming in MmWave Massive MIMO System

This paper investigates optimal power distribution which guarantees Quality of Service (QoS) for Weighted Sum-Rate Maximization (WSRM) in downlink Non-Orthogonal Multiple Access (NOMA) networks. For a two-user WSRM problem, closed form solution is derived. Based on this result, a novel power allocation algorithm for a multi-user scenario is presented in this paper. The proposed algorithm has the following advantages: solution exists under all user weight-ratio scenarios irrespective of the convexity of the optimization problem; successful Successive Interference Cancellation (SIC) decoding is guaranteed; has low complexity; provides optimal solution. Extensive simulation results are provided to evaluate the performance of the proposed algorithm under different user weight-ratio scenarios.

A Novel Low Complexity Power Allocation Algorithm for Downlink NOMA Networks

A new power allocation algorithm is proposed based on the Glicksberg game for cellular downlink non-orthogonal multiple access (NOMA) networks. First, a price-based user's utility function is proposed, and shown that it is effective and restrictive. Secondly, the Hessian matrix is used to derive an expression for power price based on the restricted transmission power and number of the served users in the cell. Then, the existence of a unique Nash equilibrium is proven and the optimum solution that maximises the utility function is presented. Finally, simulation results show that the proposed power allocation mechanism outperforms existing algorithms in terms of sum data rate and average data rate of the users.

Game-theoretic power allocation algorithm for downlink NOMA cellular system

This letter investigates user selection and power allocation among users for an orthogonal frequency division multiplexing-based nonorthogonal multiple access scheme. We have proposed a low-complexity method for user selection by removing users who do not satisfy the derived condition. A closed form solution for optimal power allocation to the chosen users is derived by maximizing the weighted sum rate of the users. Results show that the proposed method achieves a performance similar to the optimal scheme employing exhaustive user search but with much lower complexity.

Low Complexity User Selection With Optimal Power Allocation in Downlink NOMA

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Low Complexity User Selection With Optimal Power Allocation in Downlink NOMA