Uplink Vs. Downlink NOMA in Cellular Networks: Challenges and Research Directions

Tabassum, Hina; Ali, Md. Shipon; Hossain, Ekram; Hossain, Md. Jahangir; Kim, Dong In

doi:10.1109/vtcspring.2017.8108691

Cited by 85 publications

(59 citation statements)

References 13 publications

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“…a 1 P BS and a 2 P BS denote the allocated powers to the strong and weak users where 0 < a 1 < a 2 < 1 and a 1 + a 2 = 1. Note that, unlike uplink, inter-cell interference seen at different users is different in downlink; I (1) inter and I…”

Section: Sic Is Very Likely or Iii) Assumptionmentioning

confidence: 99%

“…Performance of non-orthogonal multiple access (NOMA) in both uplink and downlink depends on the successive intra-cell interference cancellation (SIC) which relies on the ranking of the users in each NOMA cluster [1]. In particular, downlink intra-cell interference received at a given user in NOMA depends on the power allocation factors of users in the cluster.…”

Section: Introductionmentioning

confidence: 99%

“…For example, users with stronger links have smaller power allocations and vice versa. On the other hand, in uplink NOMA, to apply SIC, BS successively decodes and cancels the messages of strong channel users, prior to decoding the signals of weak channel users [1]. Therefore, the intra-cell interference encountered by any user depends on the instantaneous received signal powers (which includes short-term fading) of users in the NOMA cluster.…”

Section: Introductionmentioning

confidence: 99%

“…The link quality can be evaluated by different metrics. These metrics should include effects of path-loss (and therefore link distance), fading, and/or inter-cell interference 1 [2]. However, acquiring complete channel state information (CSI) with fading and inter-cell interference increases system complexity.…”

Section: Introductionmentioning

confidence: 99%

“…In order to maximize the rate region of the uplink NOMA systems, in [10], decoding order of the information signal at the BS is the inverse of the distances. In [2], the authors derive the outage 1 Note that uplink inter-cell interference at the desired BS is same for different users in a NOMA cluster. Therefore, signal power-based ranking and signal-to-intercell-interference-ratio (SINR)-based ranking yield the same result.…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

Accuracy of Distance-Based Ranking of Users in the Analysis of NOMA Systems

Salehi

Tabassum

Hossain

2019

IEEE Trans. Commun.

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We characterize the accuracy of analyzing the performance of a non-orthogonal multiple access (NOMA) system where users are ranked according to their distances instead of instantaneous channel gains, i.e., product of their distance-based path-loss and fading channel gains. Distance-based ranking of users is analytically tractable and can lead to important insights. However, it may not be appropriate in a multipath fading environment where a near user suffers from severe fading while a far user experiences weak fading. Since the ranking of users (and in turn interferers) in a NOMA system has a direct impact on coverage probability analysis, impact of the traditional distance-based ranking, as opposed to instantaneous signal power-based ranking, needs to be understood. This will enable us to identify scenarios where distance-based ranking, which is easier to implement compared to instantaneous signal power-based ranking, is acceptable for system performance analysis. To this end, in this paper, we derive the probability of the event when distance-based ranking yields the same results as instantaneous signal power-based ranking, which is referred to as the accuracy probability. We characterize the probability of accuracy considering Nakagami-m fading channels and three different spatial distribution models of user locations in NOMA, namely, Poisson Point Process (PPP), Matern Cluster Process (MCP), and Thomas Cluster Process (TCP). For all these models of users' locations, we assume that the spatial locations of the base stations (BSs) follow a homogeneous PPP. We show that the accuracy probability decreases with the increasing number of users and increases with the path-loss exponent. In addition, through examples, we illustrate the impact of accuracy probability on uplink and downlink coverage probability. Closed-form expressions are presented for Rayleigh fading environment. Effects of fading severity and users' pairing on the accuracy probability are also investigated.

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Section: Sic Is Very Likely or Iii) Assumptionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Accuracy of Distance-Based Ranking of Users in the Analysis of NOMA Systems

Salehi

Tabassum

Hossain

2019

IEEE Trans. Commun.

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Cross‐layer 1 and 5 user grouping/power allocation/subcarrier allocations for downlink OFDMA/NOMA video communications

Tseng

Tsai

Suo

2019

Int J Communication

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Wang et al proposed cross-layer resource allocation for orthogonal frequency division multiple access (OFDMA) video transmission systems. Unlike Wang et al, we add non-orthogonal multiple access (NOMA) to the downlink OFDMA video transmission system and propose power allocation for users on each subcarrier (cluster) to minimize sum of video mean square error (MSE) to increase the peak signal-to-noise ratio (PSNR), the video quality. For OFDMA/NOMA video communication systems, we propose cross-layer user clustering to reassign the subcarriers based on sum video distortion minimization and derive the optimal power allocation among NOMA users on the same subcarrier to minimize the sum video distortion. Numerical results show that the proposed scheme outperforms the previous OFDMA cross-layer scheme by Wang et al by 2.2 to 4.5 dB in PSNR and previous OFDMA NOMA physical layer scheme by Ali et al by 2 to 4.4 dB in PSNR, when SNR = 15 dB, and the number of users is 6 to 12.KEYWORDS non-orthogonal multiple access, orthogonal frequency division multiple access, power allocation, user pairing

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Fusion of artificial intelligence and game theory for resource allocation in non‐orthogonal multiple access‐assisted device‐to‐device cooperative communication

Rathod

Gupta

Jadav

et al. 2023

Int J Communication

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SummaryDevice‐to‐device (D2D) communication offers a low‐cost paradigm where two devices in close proximity can communicate without needing a base station (BS). It significantly improves radio resource allocation, channel gain, communication latency, and energy efficiency and offers cooperative communication to enhance the weak user's network coverage. The cellular mobile users (CMUs) share the spectral resources (e.g., power, channel, and spectrum) with D2D mobile users (DMUs), improving spectral efficiency. However, the reuse of radio resources causes various interferences, such as intercell and intracell interference, that degrade the performance of overall D2D communication. To overcome the aforementioned issues, this paper presents a fusion of AI and coalition game for secure resource allocation in non‐orthogonal multiple access (NOMA)‐based cooperative D2D communication. Here, NOMA uses the successive interference cancellation (SIC) technique to reduce the severe impact of interference from the D2D systems. Further, we utilized a coalition game theoretic model that efficiently and securely allocates the resources between CMUs and DMUs. However, in the coalition game, all DMUs participate in obtaining resources from CMUs, which increases the computational overhead of the overall system. For that, we employ artificial intelligence (AI) classifiers that bifurcate the DMUs based on their channel quality parameters, such as reference signal received power (RSRP), received signal strength indicator (RSSI), signal‐to‐noise ratio (SNR), and channel quality indicator (CQI). It only forwards the DMUs that have better channel quality parameters into the coalition game, thus reducing the computational overhead of the overall D2D communication. The performance of the proposed scheme is evaluated using various statistical metrics, for example, precision score, accuracy, recall, F1 score, overall sum rate, and secrecy capacity, where an accuracy of 99.38% is achieved while selecting DMUs for D2D communication.

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Uplink Vs. Downlink NOMA in Cellular Networks: Challenges and Research Directions

Cited by 85 publications

References 13 publications

Accuracy of Distance-Based Ranking of Users in the Analysis of NOMA Systems

Accuracy of Distance-Based Ranking of Users in the Analysis of NOMA Systems

Cross‐layer 1 and 5 user grouping/power allocation/subcarrier allocations for downlink OFDMA/NOMA video communications

Fusion of artificial intelligence and game theory for resource allocation in non‐orthogonal multiple access‐assisted device‐to‐device cooperative communication

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