Non-orthogonal Multiple Access Cluster Research Articles

Computation offloading in NOMA-MEC-enabled aerial-vehicular networks exploiting mmWave capabilities

In recent years, there has been a significant interest in ubiquitous coverage, high data rate connectivity, and mobile edge computing (MEC) as crucial services within the future sixth-generation (6G) wireless networks. These services are regarded as essential components, exemplifying the advancements anticipated in 6G technology. Nevertheless, the successful implementation of these services in MEC-enabled vehicular networks significantly relies on the availability of robust network coverage and telecommunication framework. Unfortunately, in far-flung and isolated regions, such framework is often lacking, posing significant challenges in achieving uninterrupted connectivity, comprehensive coverage, and efficient computation offloading. Targeting the aforementioned horizon, in this paper, an uplink non-orthogonal multiple access (NOMA)-MEC-enabled aerial-vehicular network operating at millimeter wave (mmWave) is proposed in which the ground vehicles are provided edge computing services by an aerial autonomous vehicle, i.e., a high-altitude platform (HAP). We present a system model in which a HAP equipped with MEC servers offers computation offloading capabilities to a vehicular network. Our main objective is to minimize the transaction time of a NOMA cluster offloading its data to MEC servers located at the HAP. We devise a dual-layer optimization scheme for optimizing the transmission power and computational resource allocation by using the Lagrange multipliers method and then attain convergence by implementing a sub-gradient approach. We further extend our work by proposing a data-aware NOMA clustering scheme. The simulation results demonstrate the efficacy of our proposed approach, showing a notable reduction in the transaction time in comparison to the baseline scheme. The optimal power allocation enhances the data rates which subsequently reduces the transmission time, and the optimal cores assignment effectively minimizes the computation time. Additionally, the data-aware NOMA clustering scheme shows promising results by enhancing the system effective throughput and the spectral efficiency in comparison to the conventional NOMA clustering.

Low‐complexity joint equalization and CFO compensation in uplink SC‐FDMA NOMA system under different power allocation strategies

AbstractIn current wireless systems, the claim for rapid data services has become unavoidable in broadband communication. Single carrier frequency division multiple access (SC‐FDMA) has remained a multiple access (MA) technique with low peak‐to‐average power ratio (PAPR) in 4G systems. Non‐orthogonal multiple access (NOMA) is a complimentary MA technique in the fifth generation (5G) new radio with the capability of using similar frequency elements for multiuser communication within a single cellular system. In SC‐FDMA NOMA systems the carrier frequency offsets (CFO) destroy the orthogonal behavior in multiple carriers during transmission leading to inter‐carrier interference (ICI) and multiple access interference (MAI). Furthermore, the power allocated for each user in the NOMA cluster exhibits a noticeable part in enhancing the performance of the system. In this article, we propose a joint low‐complexity linear regularized zero forcing (JLC‐LRZF) for SC‐FDMA NOMA system and investigate its performance using discrete Fourier transform (DFT) and discrete cosine transform (DCT). The proposed JLC‐LRZF equalization algorithm is capable of performing equalization and CFO compensation with low‐complexity with banded‐matrix approximation (BMA). Additionally, we investigate the effectiveness of SC‐FDMA NOMA system in achieving improved performance with different values of CFO and power allocation policies in uniform random multipath channels.

NOMA-based collaborative beam hopping frequency allocation mechanism for future LEO satellite systems

Low Earth orbit (LEO) satellite systems provide terrestrial users with services that are not limited by geographical location. However, the conflict between existing allocation schemes and the business variability between beams is becoming increasingly prominent. Beam hopping technology allows for a more flexible and versatile approach to satellite resource allocation. This paper proposes a beam hopping pattern optimization scheme that jointly considers the interference threshold distance and beam service priority, reducing the inter-beam co-channel interference (CCI). In the cluster area, a non-orthogonal multiple access (NOMA)-based collaborative beam hopping (NCBH) scheme is proposed to minimize the cell-edge user (CEU) interference. Since there is a difference in channel gain between the CEU and cellcenter user (CCU), this scheme forms a NOMA cluster to perform power domain multiplexing and formulates a NOMA cluster pairing strategy according to the user location to reduce the CCI of the CEU. After NOMA cluster pairing, the optimal carrier frequency of the NOMA cluster is selected by a reinforcement learning algorithm. The simulation results verify the excellent performance of the proposed NCBH scheme regarding the user's received power, transmission rate, and outage probability.

Analysis of Individual User Data Rate in a TDMA-RIS-NOMA Downlink System: Beyond the Limitation of Conventional NOMA

Non-orthogonal multiple access (NOMA) is playing a pivotal role in 5G technology and has the potential to be useful in future developments beyond 5G. Although the effectiveness of NOMA has largely been explored in the sum throughput maximization, the identification of individual user data rate (IDR) still remained an unexplored area. Previously, it has been shown that reconfigurable intelligent surfaces (RIS) can lead to an overall improvement in the data rate by enhancing the effective channel gain of the downlink NOMA system. When time division multiple access (TDMA) is clubbed with multiple RISs in a distributed RIS-assisted NOMA (TDMA-RIS-NOMA) downlink system, a point-to-point communication model is created between access point-to-RIS-to-user device. Due to this point-to-point communication model, optimization of the phase shifts provided by meta-atoms of each RIS is facilitated. The optimized phase shifts of meta-atoms maximize the equivalent channel gain between the access point to the user. In this scenario, the channel becomes saturated and signal-to-interference plus noise ratio (SINR) becomes a function of power coefficients only. In this study, the power coefficients are calculated to maximize the SINR of each user belonging to a NOMA cluster using a geometric progression-based power allocation method such that IDR reaches its upper bound. These observations are also verified using the recently published magic matrix-based power allocation method. There are two observations from this study: (i) the IDR is better in the case of the TDMA-RIS-NOMA downlink system than using downlink NOMA alone and (ii) irrespective of the number of meta-atoms and total cluster power, the upper bound of IDR cannot be increased beyond a certain limit for all users except the highest channel gain user. Because of the restricted upper bound for IDR, we suggest that the RIS-assisted downlink TDMA-NOMA system is more suitable for IoT applications, where minimum IDR can also suffice

Game Theory Based Delta-OMA Scheme for VLC Networks

This paper proposes a delta-orthogonal multiple access (D-OMA) scheme-based visible light communications (VLC) network to enhance spectral efficiency and massive connectivity in the indoor environment. The D-OMA scheme is an advanced version of the non-orthogonal multiple access (NOMA) scheme. D-OMA allows the partial overlapping of the in-band NOMA clusters to achieve the benefits of a massive in-band NOMA scheme with low power consumption and less complexity. In this work, the massive in-band NOMA scheme is used as a special case of the proposed D-OMA scheme. Game theory is employed for the user grouping mechanism, which enhances the sum rate of the proposed network. Closed-form expressions for the bit error rate (BER) and outage probability of the proposed network are derived. Further, downlink transmission power optimization is performed using Karush-Kuhn Tucker (KKT) conditions to improve the outage performance of the proposed D-OMA VLC network. The presented numerical results show the effect of optical filter gain and field of view (FoV) in indoor communication. Further, it is noted that the BER performance of the D-OMA scheme outperforms the massive in-band NOMA scheme due to the cluster sizes which control the interference in the D-OMA scheme. Moreover, the sum rate of the proposed network is significantly improved using the preference relation algorithm (PRA) compared to the random NOMA scheme.

Secrecy Driven Federated Learning via Cooperative Jamming: An Approach of Latency Minimization

Federated learning (FL) provides a promising framework for enabling distributed machine learning based services without revealing users’ private data. In the scenario of wireless FL, to counter the eavesdropping attack when the parameter-server (PS, which is co-located with a base station, BS) sends the model-data to the wireless devices, we propose a secrecy driven FL via cooperative jamming, in which wireless devices cooperatively provide jamming to the eavesdropper to enhance the PS’s secure throughput based on the measure of physical layer security. We formulate a joint optimization of the PS’s downloading-transmission duration, all wireless devices’ uploading-transmission duration as a non-orthogonal multiple access cluster, each device’s local processing-rate and transmit powers for its uploading NOMA-transmission and jamming to the eavesdropper, with the objective of minimizing the overall latency for each round of FL iteration. Despite the non-convexity of the joint optimization problem, a layered algorithm is proposed to solve it. Taking into account the special feature of the optimal jamming solution, we further propose a benefit-sharing scheme, which is based on the principle of Nash bargaining solution, such that all wireless devices can benefit from reducing the FL latency via cooperative jamming in a fairness manner. Numerical results are provided to validate the effectiveness of our proposed algorithms as well as the performance advantage of our proposed secrecy driven FL via cooperative jamming. Experimental results based on the real data-sets and training models demonstrate that our scheme can reduce the latency by more than 35% compared to the case without using the jamming.

Learning-Based User Clustering in NOMA-Aided MIMO Networks With Spatially Correlated Channels

This paper considers the integration of non-orthogonal multiple access (NOMA) into massive multi-input multi-output (MIMO) systems for downlink transmission. We consider the joint design of user clustering, transmit beamforming, and power allocation to minimize the total transmit power while meeting the signal-to-interference-and-noise ratio targets. We decompose this challenging mixed-integer programming problem into three separate subproblems to solve. We propose a low-complexity learning-based user clustering algorithm, which is a modified version of mean shift clustering with a new channel correlation based clustering metric. The proposed clustering algorithm determines the clusters to trade-off between spatial dimension and power dimension offered by respective MIMO and NOMA for user multiplexing. We then design zero-forcing transmit beamformers to eliminate inter-cluster interference and optimize power allocation to minimize the total transmit power. We provide two case studies for both co-located and distributed massive MIMO systems in spatially highly correlated prorogation environments. Simulation results show that our proposed algorithm forms NOMA clusters based on the available degrees of freedom in the system to effectively use both spatial and power dimensions, which results in a substantial performance improvement over MIMO-only methods or other existing clustering methods in such environments.

Relay Selection and Power Allocation for Energy Efficiency Maximization in Hybrid Satellite-UAV Networks With CoMP-NOMA Transmission

Non-orthogonal multiple access (NOMA) and coordinated multi-point (CoMP) are two fundamental techniques considered for the fifth generation (5 G) of wireless communications. In this paper, a hybrid satellite-unmanned aerial vehicle (UAV) relay network (HSURN) is proposed where the UAV relays (URs) employ CoMP transmission to serve the terrestrial users (UEs). Furthermore, all UEs associated with the CoMP-URs form a single NOMA cluster. For this model, an optimization problem is formulated subject to the minimum quality of services (QoSs) requirements of the UEs, transmission power budgets and, successive interference cancellation (SIC), to select URs and allocate their transmission powers for the energy efficiency (EE) maximization. With this insight, first, a computationally efficient sub-optimal UR selection scheme is proposed. Then, the powers are allocated to the selected URs via the Lagrange multipliers optimization (LMO) method. Due to the non-convex nature of the considered problem, it is relatively difficult to be solved. Hence, a metaheuristic teaching-learning-based optimization (TLBO) algorithm is employed to achieve an efficient solution. Simulation results are provided to verify the effectiveness of the proposed sub-optimal relay selection scheme and the TLBO-based power allocation method compared to the LMO conventional method. Besides, the obtained results also reveal that the CoMP-NOMA transmission in the proposed scenario significantly improves the spectral efficiency (SE) and outage probability (OP) of the system compared to non-comp NOMA transmission case.

Non-Orthogonal Multiple Access Assisted Federated Learning via Wireless Power Transfer: A Cost-Efficient Approach

Federated learning (FL) has been considered as a promising paradigm for enabling distributed training/learning in many machine-learning services without revealing users’ local data. Driven by the growing interests in exploiting FL in wireless networks, this paper studies the Non-orthogonal Multiple Access (NOMA) assisted FL in which a group of end-devices (EDs) form a NOMA cluster to send their locally trained models to the cellular base station (BS) for model aggregation. In particular, we consider that the BS adopts wireless power transfer (WPT) to power the EDs (for their data transmission and local training) in each round of FL iteration, and formulate a joint optimization of the BS’s WPT for different EDs, the EDs’ NOMA-transmission for sending the local models to the BS, the BS’s broadcasting of the aggregated model to all EDs, the processing-rates of the BS and EDs, as well as the training-accuracy of the FL, with the objective of minimizing the system-wise cost accounting for the total energy consumption as well as the FL convergence latency. In spite of the strict non-convexity of the joint optimization problem, we analytically characterize the BS’s and all EDs’ optimal processing-rates, based on which we propose a layered algorithm for finding the optimal solutions for the joint optimization problem via exploiting monotonic optimization. Numerical results validate that our algorithm can achieve the optimal solution as LINGO’s global-solver (i.e., a commercial optimization package) while significantly reducing the computation-time. Moreover, the results also demonstrate that our NOMA assisted FL can reduce the system cost compared to the benchmark FL scheme with the fixed local training-accuracy by more than 70% and the conventional frequency division multiple access (FDMA) based FL by 78%.

A Novel User Grouping in Phase Rotation Based Downlink NOMA

Non-orthogonal multiple access (NOMA) is a promising candidate beyond 5G and 6G to improve spectral efficiency by sharing the same resource block with other users. However, as the number of users increases in a single NOMA cluster, not only the spectral efficiency but also the interference increases. Therefore, to ensure a trade-off between capacity and error performance in NOMA systems, this study introduces a novel downlink NOMA scheme using the phase rotation. In the system, four users can create a single NOMA cluster and are grouped into two subgroups by exploiting conventional NOMA. Within each subgroup, the symbols of two users, near user and far user, are rotated and multiplexed by the power domain. Subsequently, the final transmitted signal is obtained by multiplexing the in-phase and quadrature components of the first and second subgroups, respectively. By superposing signals from two independent subgroups, the number of successive interference cancellation (SIC) operations are reduced compared to the existing NOMA. Moreover, the analytical bit error rate (BER) for a four-user scenario is derived, and the optimal rotation angle and power allocation are proposed to minimize the BER performance. Numerical results demonstrate the improved performance of the proposed NOMA scheme over several existing schemes, such as conventional NOMA and orthogonal multiple access (OMA).

A cyclic frequency division non‐orthogonal multiple access system

SummaryIn this paper, we have developed a downlink power domain non‐orthogonal multiple access (NOMA) system based on cyclic frequency division, where interleaved frequency division multiple access (IFDMA) is cyclically combined with NOMA. The newly developed cyclic frequency division NOMA (CFD‐NOMA) system has the benefit of both NOMA and IFDMA. The concept of superposed multiuser principle for non‐orthogonal resource allocation is used in each NOMA cluster, and the users' data associated with different clusters are separated based on IFDMA. Extreme channel conditions are considered among the users in each cluster. Based on channel gain, the users are differentiated as strong and cell edge users. At the strong user terminal, successive interference cancelation (SIC) is applied to decode the strong user data with the aid of the cell edge user data found from a hard decision, whereas the cell edge user terminal detects its signal only through the hard decision. The near‐far effect of the users present in a cluster, the amount of difference among their channel gain, and transmission power play an important role in detecting the cell edge and the strong users. The CFD‐NOMA system inherits an effective use of multipath channel, thereby reaps an increased cell edge user performance in terms of bit error rate (BER).

Rate and Energy Efficiency Improvements of Massive MIMO-Based Stochastic Cellular Networks With NOMA

Non-orthogonal multiple access (NOMA) coupled with massive multiple-input multiple-output (MIMO) base stations hold immense potential in increasing the spectral and energy efficiencies while enabling massive access of future cellular networks. To this end, we investigate the rate performance of a system employing multi-user NOMA and massive MIMO base stations distributed under a Poisson process. We adopt a time-division-duplexing mode, and employ matched filter based precoding in the downlink of the cellular network. We investigate two power allocation scenarios for the individual users while keeping the overall power usage of a NOMA cluster constant: 1) pre-defined power allocation and 2) power allocation based on user-base station distance. Considering imperfect successive interference cancellation, pilot contamination, and error propagation for the two power allocation scenarios, we characterize the average rate of a NOMA user and the signal detection probability under asymptotic conditions for the number of antennas. Furthermore, we derive the moment generating function of the out-of-cell interference caused by pilot contamination. We show that NOMA improves the rate performance and by extension the energy efficiency under most system conditions. Moreover, the rate can be increased further through denser network deployments, while the user fairness is greatly impacted by the power allocation scheme.

Rayleigh Sönümlemeli Kanalda NOMA Üstünlük Koşulunun Belirlenmesi

Non-orthogonal Multiple Access (NOMA) is a new generation multiple access technique in which multiple users simultaneously share the same frequency band. In the implementation of NOMA, the choice of user pairs that will use the same frequency is a determining factor for the NOMA superiority condition due to Successive Interference Cancellation (SIC) mechanism on the receiver. However, performance of NOMA depends on SIC mechanism which relies on the order of the user in a NOMA cluster. In the literature, it has been shown that utilizing distance based order of the users for user pairing outperforms over the random pairing and an analytical boundary distance is derived for NOMA superiority condition for a path loss based channel model. In this study, the path loss based NOMA superiority condition respect to the Orthogonal Multiple Access (OMA) was investigated in terms of the spectral efficiencies for Rayleigh channel model in a cellular uplink and the results were compared with an analytical boundary value derived for a path loss based channel model in the literature. In addition, the effect of power ratio of the users on the NOMA superiority condition is investigated and accuracy of the derived analytical model is validated with numerical results for both channel models. The results reveal that the NOMA superiority condition based on distance changes depend on the assumed channel model, but assuming the channel as Rayleigh fading or path loss based channel does not make a significant difference. In addition, it is observed that the accuracy of the derived NOMA superiority condition changes with the power ratios for both channel models and the gap between numerical and analytical results is larger in Rayleigh channel compared to path loss based channel model.

Antenna selection in nonorthogonal multiple access multiple‐input multiple‐output systems aided by machine learning

AbstractThis work proposes a transmitter antenna selection (TAS) method for multiple‐input multiple‐out (MIMO) nonorthogonal multiple access (NOMA) that is a promising multiple access technique for the fifth generation mobile communications systems. Specifically, we propose to activate the more suitable subset of base station antennas while allocating users into appropriate NOMA clusters such that the system operates in energy efficiency mode, selecting such appropriate antenna subset indexes that maximize the sum‐rate (SR) of the NOMA‐MIMO system. Once that the TAS based on exhaustive‐search is very complex to be implemented in real communication systems, we propose an effective TAS method based on machine learning while keeping very promising performance. A convolutional neural network‐based transmitter antenna selection (CNN‐TAS) method is proposed for efficiently select antennas aiming at maximizing the system SR. Hence, extensive numerical results demonstrate that the CNN‐TAS can suitably learn the problem, performing with very high accuracy choosing properly the antenna subset that maximizes the system spectral efficiency while reducing substantially the processing time of real‐time operations.

Magic-Matrix-Based Power Allocation for Downlink Nonorthogonal Multiple Access

In a wireless cellular system, resource allocation among active users is a challenging task. The cellular systems with nonorthogonal multiple access (NOMA) solve the problem of bandwidth and time allocation. All the active users in the same NOMA cluster are allowed to access the complete cluster bandwidth at the same time. However, power allocation in NOMA is a multiconstraint optimization problem. The complexity of power allocation increases with the increase in the number of users inside the cluster. This article presents a novel technique for power allocation in a NOMA downlink cluster, using the magic sum of the magic matrix. The sum throughput (SUMTP) and the min–max fairness index (MMFI) are calculated and compared with an existing method for the downlink NOMA system. The proposed method shows comparable SUMTP performance to the conventional optimized method while ensuring better MMFI. We observed an inverse association between SUMTP and MMFI. In addition, the execution time of the proposed method is much lesser than that of the conventional optimized method owing to lower number of flops required for magic-matrix-based power allocation.

Resource Allocation in Virtualized CoMP-NOMA HetNets: Multi-Connectivity for Joint Transmission

In this work, we design a generalized joint transmission coordinated multi-point (JT-CoMP)-non-orthogonal multiple access (NOMA) model for a virtualized multi-infrastructure network. In this model, all users benefit from multiple joint transmissions of CoMP thanks to the multi-connectivity opportunity provided by wireless network virtualization (WNV) in multi-infrastructure networks. The NOMA protocol in CoMP results in an unlimited NOMA clustering (UNC) scheme, where the order of each NOMA cluster is the maximum possible value. We show that UNC results in maximum successful interference cancellation (SIC) complexity at users. In this regard, we propose a limited NOMA clustering (LNC) scheme, where the SIC is performed to only a subset of users. We formulate the problem of joint power allocation and user association for the UNC and LNC schemes. Then, one globally and one locally optimal solution are proposed for each problem based on mixed-integer monotonic optimization and sequential programming, respectively. Numerical assessments reveal that WNV and LNC improves users sum-rate and reduces users SIC complexity by up to 35% and 46% compared to the non-virtualized CoMP-NOMA system and UNC model, respectively. Therefore, the proposed algorithms are suitable candidates for the implementation on open and intelligent radio access networks.

Achievable Rate Characterization of NOMA-Aided Cell-Free Massive MIMO With Imperfect Successive Interference Cancellation

This paper investigates the throughput improvement of cell-free massive multiple-input multiple-output (MIMO) systems by non-orthogonal multiple access (NOMA) for future cellular networks under stochastic access point and user locations. In this context, the node locations are modeled with Poisson point processes. The time division duplexing mode is employed, and uplink channels are estimated locally using uplink pilots. Furthermore, unique pilot sequences are used between NOMA clusters, while pilot reuse occurs within each cluster to strike a balance between the training overhead and the number of clusters. Matched-filter-based precoding is utilized for downlink transmission. The aggregate received signal is analytically characterized by deriving the moment generating function and approximations via moment matching. Then, the asymptotic achievable rates of the NOMA users are derived, thereby quantifying the adverse impact of error propagation owing to imperfect successive interference cancellation. Special scenarios with prior downlink channel state information and log-distance power control are also considered. We show that NOMA greatly increases the achievable average rate, especially under low path loss exponents and dense networks, while user fairness may be boosted by the adoption of a log-distance transmit power control scheme with proper parameter selection (i.e. lower values for the power control parameter).

Cell-Free Massive MIMO System With an Adaptive Switching Algorithm Between Cooperative NOMA, Non-Cooperative NOMA, and OMA Modes

Non-orthogonal multiple access (NOMA) aided cell-free massive multiple-input multiple-output (CF mMIMO) systems have gained great attention over the past few years to be employed in the sixth generation of the wireless network. With distributed antennas over a large area, CF mMIMO systems have much better cell coverage and higher achievable sum-rate compared to the conventional cellular and small-cell networks. This paper will propose a novel cooperative NOMA-aided CF mMIMO system. The proposed scheme will increase the achievable sum-rate and improve the system reliability by creating additional data streams between users within the same NOMA cluster. Also, we will suggest an adaptive switching algorithm between non-cooperative NOMA, cooperative NOMA, and orthogonal multiple access (OMA) modes in order to maximize the power efficiency and achievable sum-rate. We will derive closed-form expressions for the achievable downlink data rates of the mentioned modes. Lastly, we will offer a special user clustering algorithm that needs no complex optimization and ensures the existence of reliable cooperative links between the users. The simulation results will prove the superiority of the proposed scheme over the conventional NOMA-based and OMA-based CF mMIMO systems.

Non-Orthogonal Random Access and Data Transmission Scheme for Machine-to-Machine Communications in Cellular Networks

In order to address the signalling overhead and resource allocation problems of Machine-to-Machine (M2M) communications with non-orthogonal multiple access (NOMA), we propose a hybrid non-orthogonal random access and data transmission (NORA-DT) scheme. A novel design of NORA-DT protocol for M2M communications in cellular networks is firstly proposed. A power back-off scheme is introduced to adjust machine-type communications device (MTCD)'s target arrived power, and a closed-form analytic formula for the relation of MTCD's transmission power is derived. Based on the transmission power relation, the devices are clustered into a set of NOMA clusters. In the hybrid NORA-DT protocol, the cluster center MTCD transmits a extended preamble on behalf of the MTCDs in the same NOMA cluster on the physical random access channel (PRACH) for connection request. Base station (BS) can perfectly detect the preamble collisions in advance and schedules physical uplink shared channel (PUSCH) only to the NOMA clusters without collision. Then the MTCDs in the same NOMA clusters transmit data packets right after preamble transmission on the PUSCH to reduce the signalling overhead. By finding the optimal power allocation, we propose a low-complexity energy efficiency maximization problem for NORA-DT scheme. Due to the relation of MTCD's transmission power, we transform the problem into the function of cluster center MTCD's transmission power and solve it by difference of convex (DC) programming under the maximum transmission power constraints and minimum rate requirements at the MTCDs. A computationally efficient adaptive resource allocation scheme is finally proposed to improve the system throughput and resource usage. The optimal resource allocation between PRACH and PUSCH for any number of MTCDs can be learned by BS in advance, which avoids frequent computation. The analytic model is validated by simulation results. We demonstrate that the proposed NORA-DT scheme can significantly improve the system throughput, resource efficiency and energy efficiency performance.

Matching theory based user-grouping for indoor non-orthogonal multiple access visible light communication heterogeneous networks

This Letter proposes a model of indoor visible light communication (VLC) heterogeneous networks entirely based on LEDs with different specifications and applies non-orthogonal multiple access (NOMA) to it because of the narrow modulation bandwidth of LEDs. Moreover, a user-grouping scheme that is based on matching theory is proposed to improve the network achievable sum rate. Simulation results indicate that when each NOMA cluster contains 6 users, the proposed scheme has a 49.54% sum-rate enhancement compared with the traditional user-grouping scheme. As the number of users in each NOMA cluster increases, the proposed scheme performs better at the cost of computational complexity.