On the Ergodic Capacity of MIMO NOMA Systems

By Qi Sun, Shuangfeng Han, Chin-Lin I, Z. Pan. IEEE Wireless Communications Letters, 2015

467 citations recorded by the source corpus.

Subfields: Electrical and Electronic Engineering

View Paper: https://www.semanticscholar.org/paper/cf9151750af4d3aeedf328bdb2c2d1c47b6f76a1

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Citations in the corpus

On the Performance of Non-orthogonal Multiple Access Systems With Partial Channel Information (2016, methodology): “Recently, optimal power allocation based on average channel state information (CSI) has been considered in [15], by using the outage probability as the criterion, whereas the ergodic capacity of MIMO-NOMA systems with second order statistical (SOS) CSI at the transmitter has been studied in [16].”
A General Power Allocation Scheme to Guarantee Quality of Service in Downlink and Uplink NOMA Systems (2016, background): “Most existing work about NOMA focuses only on the fixed power allocation strategy, where the power allocation coefficients are predefined and are not a function of channel gains [5]–[8], [10], [11].”
A Survey of Rate-Optimal Power Domain NOMA With Enabling Technologies of Future Wireless Networks (2019, background): “On the other hand, if only statistical CSIT is available, then the design objective is to maximize the ergodic sum-rate [153], [166] rather than the actual sum-rate.”
Evolution of NOMA Toward Next Generation Multiple Access (NGMA) for 6G (2021, methodology): “Along this line, considering a two-user downlink MIMONOMA system with a given decoding order, the authors of [45] investigated the transmit covariance matrix optimization problem to maximize the ergodic capacity based on statistical channel state information (CSI).”
Power-Domain Non-Orthogonal Multiple Access (NOMA) in 5G Systems: Potentials and Challenges (2016, background): “schemes [35] can maximize ergodic capacity with a total transmit power constraint.”
Impact of User Pairing on 5G Nonorthogonal Multiple-Access Downlink Transmissions (2016, unknown): “The application of multiple-input–multipleoutput technologies to NOMA has been proposed in [10] and [11].”
A General MIMO Framework for NOMA Downlink and Uplink Transmission Based on Signal Alignment (2015, methodology): “In [14], a multiple-antenna base station used the NOMA approach to serve two multiple-antenna users simultaneously, where the problem of throughput maximization was formulated and two algorithms were proposed to solve the optimization problem.”
Rate-Splitting Multiple Access: Fundamentals, Survey, and Future Research Trends (2022, background): “This corresponds to a direct extension of single-antenna NOMA (SC–SIC) to the multi-antenna BC by ordering users according to their effective channel strengths (after linear precoding) and forcing users to successfully decode messages (and remove interference) [17], [18].”
Spectrum and Energy-Efficient Beamspace MIMO-NOMA for Millimeter-Wave Communications Using Lens Antenna Array (2017, methodology): “In [29], a non-convex power allocation problem was formulated for MIMO-NOMA systems, where only two users have been considered, and sub-optimal solutions were provided.”
Capacity Comparison Between MIMO-NOMA and MIMO-OMA With Multiple Users in a Cluster (2017, background): “In [11], the authors explore the two user power allocation problem of a NOMA scheme by maximizing the ergodic sum capacity of a MIMO channel under total transmit power, minimum rate requirement and partial CSI availability constraints.”
Nonorthogonal Multiple Access in Large-Scale Underlay Cognitive Radio Networks (2016, background): “in [5] investigated an ergodic capacity maximization problem for MIMO NOMA systems.”
Modulation and Multiple Access for 5G Networks (2017, background): “[71] to investigate power optimization to maximize the ergodic capacity.”
A Survey on Non-Orthogonal Multiple Access for 5G Networks: Research Challenges and Future Trends (2017, methodology): “has also been proved to be an effective technique [44]–[47].”