On the Performance of Non-Orthogonal Multiple Access in 5G Systems with Randomly Deployed Users

By Zhiguo Ding, Zhengju Yang, P. Fan, H. Vincent Poor. IEEE Signal Processing Letters, 2014

1,913 citations recorded by the source corpus.

In this letter, the performance of non-orthogonal multiple access (NOMA) is investigated in a cellular downlink scenario with randomly deployed users. The developed analytical results show that NOMA can achieve superior performance in terms of ergodic sum rates; however, the outage performance of NOMA depends critically on the choices of the users' targeted data rates and allocated power. In particular, a wrong choice of the targeted data rates and allocated power can lead to a situation in which the user's outage probability is always one, i.e. the user's targeted quality of service will never be met.

Subfields: Electrical and Electronic Engineering

View Paper: https://www.semanticscholar.org/paper/e81f0fd3a3ecdfa6d874bd86b221827ddbc8d30c

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Citations in the corpus

A Survey on Non-Orthogonal Multiple Access for 5G Networks: Research Challenges and Future Trends (2017, background): “multiple access is realized by allocating different power levels to different users [5], [6], [23]–[25].”
Power and Channel Allocation for Non-Orthogonal Multiple Access in 5G Systems: Tractability and Computation (2016, methodology): “In [13], outage performance of NOMA has been evaluated.”
Cooperative Non-orthogonal Multiple Access With Simultaneous Wireless Information and Power Transfer (2015, methodology): “During the first phase, the BS sends two messages pi1xi1 + pi2xi2 to two selected users Ai and Bi based on NOMA [3], where pi1 and pi2 are the power allocation coefficients and xi1 and xi2 are the messages of Ai and Bi, respectively.”
Non-Orthogonal Multiple Access in Coordinated Direct and Relay Transmission (2015, methodology): “2 During the first phase, the BS transmits xN(t1) = √ Pb a1(t1) x1(t1) + √Pb a2(t1) x2(t1) according to the NOMA protocol described in [4], where x1(t1) and x2(t1) are data symbols for UE1 and UE2 with E[|x1(t1)|2]=E[|x2(t1)|2]=1.”
Uplink Nonorthogonal Multiple Access in 5G Systems (2016, methodology): “To analyze the performance of the NOMA scheme, the authors in [6] derive the expression of outage probability and achievable sum-rate for a fixed power allocation without discussing potential fairness issues.”
Impact of User Pairing on 5G Nonorthogonal Multiple-Access Downlink Transmissions (2016, methodology): “The design of NOMA for uplink transmissions has been proposed in [4], and the performance of NOMA with randomly deployed mobile stations has been characterized in [5].”
Deep Learning for an Effective Nonorthogonal Multiple Access Scheme (2018, methodology): “In [6], the performance of a downlink NOMA scheme with randomly deployed users was well investigated.”
Spectrum and Energy-Efficient Beamspace MIMO-NOMA for Millimeter-Wave Communications Using Lens Antenna Array (2017, background): “Particularly, NOMA has also been considered as a promising candidate for 5G to improve spectrum efficiency and connectivity density [16]–[23].”
Mobile Edge Computing via a UAV-Mounted Cloudlet: Optimization of Bit Allocation and Path Planning (2016, neutral): “We note that the latter is a promising multiple access technique for 5G networks which is currently being considered due to its potentially superior spectral efficiency [20], [21].”
A Minorization-Maximization Method for Optimizing Sum Rate in the Downlink of Non-Orthogonal Multiple Access Systems (2015, background): “For instance, the works in [2], [7] use the fact that for a single-input single-output (SISO) system, once the channels are arrange d i a particular order (increasing or decreasing), then a UEk decodes all those UEi signals, whose index i < k (increasing order) and i > k (decreasing order).”
Capacity Analysis of Cooperative Relaying Systems Using Non-Orthogonal Multiple Access (2015, methodology): “In the CRS using NOMA, the source transmits √ a1Pts1 + √ a2Pts2 to the relay and the destination during the first time slot, according to the NOMA protocol [4], where si denotes the i-th data symbol, E[|si|2]=1, Pt is the total transmit power, and ai is the power allocation coefficient.”
The Application of MIMO to Non-Orthogonal Multiple Access (2015, neutral): “The impact of path loss on the performance of NOMA has been characterized in [6] by assuming that users are randomly deployed in a cell, which has demonstrated that NOMA can outperform conventional orthogonal multiple access (OMA) schemes.”
Dynamic User Clustering and Power Allocation for Uplink and Downlink Non-Orthogonal Multiple Access (NOMA) Systems (2016, methodology): “In [6], closedform expressions for ergodic sum-rate and outage probability were derived for two-user NOMA systems considering static power allocation.”
On Optimal Power Allocation for Downlink Non-Orthogonal Multiple Access Systems (2017, background): “Indeed, the authors in [31] pointed out that the power of the weak user must be strictly larger than that of the strong user, otherwise the users’ outage probabilities will always be one.”
Massive Access for 5G and Beyond (2020, methodology): “In [133], a cognitive power allocation scheme was proposed for twouser PD-NOMA.”
Energy-Efficient Resource Allocation for Downlink Non-Orthogonal Multiple Access Network (2016, background): “The authors in [32] showed that the distances between BS and UTs will affect the performance of the NOMA system.”
Exploiting Full/Half-Duplex User Relaying in NOMA Systems (2018, methodology): “Regarding downlink NOMA scenarios, authors in [12] analyzed the outage behavior and ergodic rates of NOMA networks, where multiple NOMA users are spatial randomly deployed in a disc.”