In grant-free sparse code multiple access (SCMA) systems, each active user transmits data using randomly selected SCMA codebook along with its associated preamble. When multiple users select the same codebook, i.e., l...
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In grant-free sparse code multiple access (SCMA) systems, each active user transmits data using randomly selected SCMA codebook along with its associated preamble. When multiple users select the same codebook, i.e., leading to codebook collisions, the detection of channel-modulated codebooks is still possible through collision-aware multi-user detection (CA-MUD) using their associated preambles. However, traditional CA-MUDs are designed with unique configurations tailored to each of the extensive codebook activity scenarios, thereby significantly enhancing the detection complexity and limiting the practical implementation of GF-SCMA systems. In this paper, our objective is to propose a deep learning (DL)-based CA-MUD capable of efficiently handling diverse codebook activities with a single detector, even in the presence of codebook collisions. Toward this end, we propose a multi-task learning-based DL architecture for CA-MUD that can tolerate codebook collisions, without resorting to distinct CA-MUD processes for individual collision scenarios. A key innovation in our approach is an input pre-processing method for efficient CA-MUD training that generates a channel-modulated codebook vector at the receiving end, enhancing the learning process. Simulation results demonstrate that our proposed approach enables a single CA-MUD network to manage various codebook activity scenarios, including 2-fold codebook collision, within a limited number of active users, while ensuring robustness against channel estimation errors.
With the rising needs of low-end and low-cost internet of things communication devices, accessing more devices under limited spectrum resources has become a great research. The sparse characteristics of sparsecode mu...
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With the rising needs of low-end and low-cost internet of things communication devices, accessing more devices under limited spectrum resources has become a great research. The sparse characteristics of sparse code multiple access (SCMA) and the anti-interference performance of its codebook make it one of the research hotspots of non-orthogonal multipleaccess technology. To consider uplink random access, the uplink-OFDMA random access (UORA) in the next-generation Wi-Fi protocols has great potential to be combined with SCMA. This article proposes a random access scheme based on highly reliable SCMA-UORA. This solution is divided into codebook selection and arbitration screening stages. Experimental simulations show that in massive random access scenario, compared with UORA, the solution proposed has a throughput gain of about 95%similar to 178% when the number of terminals participating in the competition is greater than 55;compared with the current cutting-edge UORA, the throughput gain is about 7%similar to 32%.
In 5G vehicle-to-everything (V2X) systems, the scarcity of spectrum resources and the inefficiency of resource allocation make vehicle-to-vehicle (V2V) communications that require stringent latency and high reliabilit...
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In 5G vehicle-to-everything (V2X) systems, the scarcity of spectrum resources and the inefficiency of resource allocation make vehicle-to-vehicle (V2V) communications that require stringent latency and high reliability still a challenge. Existing relevant literatures either focus on vehicle-to-infrastructure (V2I) communications, or consider scenarios where the vehicle roles (transmitter or receiver) are fixed in V2V communications, or study the resource allocation within a single cell. What's more, considering the high-speed movement of vehicles across the coverage regions of multiple cells, the above resource allocation problem becomes even more challenging. Toward this end, we consider in this paper a multi-cell 5G V2X system where V2V links and V2I links coexist and the vehicle roles are not fixed, and propose a sparse code multiple access-based centralized resource allocation scheme, so as to address the above challenges. In view of the fact that our formulated maximizing packet reception ratio problem is a combinatorial optimization problem and is NP-hard, we design a three-stage heuristic yet joint alternating optimization approach to obtain a suboptimal solution. Extensive numerical results demonstrate the superior performances of the proposed scheme in multiple perspectives.
In this paper, the uplink sparse code multiple access over universal filtered multicarrier (SCMA-UFMC) is studied. In SCMA-UFMC, each sub-band of UFMC is occupied by multiple users through SCMA. Note that the even-com...
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In this paper, the uplink sparse code multiple access over universal filtered multicarrier (SCMA-UFMC) is studied. In SCMA-UFMC, each sub-band of UFMC is occupied by multiple users through SCMA. Note that the even-component of frequency domain (FD) received signal suffers from neither inter-sub-band interference nor inter-sub-carrier interference while the odd-component suffers from both. The message passing algorithm (MPA) is first employed to perform multiuser detection by utilizing only the even-component. Next, to improve the performance, the odd-component is further utilized. In this improvement, reliable estimates obtained by MPA over even-component are reconstructed and cancelled from odd-component, and then only a very small number of most-unreliable user data are refined by maximum likelihood method. Moreover, the union bound of the average symbol error probability (ASEP) of maximum likelihood detection using only even-component is derived, from which it is shown that ASEP is sub-band-independent. Finally, simulation results are given to demonstrate the performance of the proposed scheme and the effectiveness of the analytical ASEP result.
In this paper, the uplink sparse code multiple access over universal filtered multicarrier (SCMA-UFMC) in rapidly time varying channels is studied. In SCMA-UFMC, each sub-band of UFMC is occupied by multiple users thr...
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ISBN:
(纸本)9781728172545
In this paper, the uplink sparse code multiple access over universal filtered multicarrier (SCMA-UFMC) in rapidly time varying channels is studied. In SCMA-UFMC, each sub-band of UFMC is occupied by multiple users through SCMA. It is observed that the inter-band-interference can be neglected and both the inter-carrier interference and inter-user-interference are small from the equivalent frequency-domain (FD) channel of even component of received signal. Based on this observation, message passing algorithm is first employed to perform multiuser detection (MUD) by utilizing only even-component of received signal. Next, to improve the performance, a two-stage detection is further presented, where the unreliable estimates from the first-stage detection using even-component are refined by utilizing additional odd component of received signal. Finally, simulation results are given to demonstrate the performance of the proposed methods.
In this paper, we study the application of index modulation (IM) to uplink sparse code multiple access (SCMA), and present a scheme called SCMA-IM. In the proposed SCMA-IM, the candidate resources of one user are part...
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ISBN:
(纸本)9781728173276
In this paper, we study the application of index modulation (IM) to uplink sparse code multiple access (SCMA), and present a scheme called SCMA-IM. In the proposed SCMA-IM, the candidate resources of one user are partitioned into two groups. All the resources in the first group are utilized to transmit signals, and only part of resources in the second are activated through IM to transmit signals. The signals transmitted in these resources are jointly designed according to the same codebook design method as SCMA. Moreover, an effective message passing algorithm is presented to perform the multiuser detection. Simulation results show that the proposed SCMA-IM can achieve better performance than conventional SCMA when the number of receive antenna is large.
sparse code multiple access (SCMA) is a promising technique for enabling massive connectivity and high spectrum efficiency in future machine-type communication networks. However, its performance crucially depends on w...
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sparse code multiple access (SCMA) is a promising technique for enabling massive connectivity and high spectrum efficiency in future machine-type communication networks. However, its performance crucially depends on well-designed multi-dimensional codebooks. In this paper, we propose a novel progressive codebook optimization scheme that can achieve near-optimal performance over downlink fading channels. By examining the pair-wise error probability (PEP), we first derive the symbol error rate (SER) performance of the sparsecodebook in downlink channels, which is considered as the design criterion for codebook optimization. Then, the benchmark constellation group at a single resource element is optimized with a sequential quadratic programming approach. Next, we propose a constellation group reconstruction process to assign the sub-constellations in each resource element (RE) progressively. For the current RE, the assignment of the sub-constellations is designed by minimizing the error performance of the product distance of the superimposed codewords in previous REs. The design process involves both permutation and labeling of the sub-constellations in the benchmark constellation group. Simulation results show that the proposed codebooks exhibit significant performance gains over state-of-the-art codebooks in the low signal-to-noise ratio (SNR) region over various downlink fading channels.
With the explosive proliferation of mobile devices, the scarcity of communication resources has emerged as a critical issue in the next generation (NG) communication systems. To overcome this, non-orthogonal multiple ...
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With the explosive proliferation of mobile devices, the scarcity of communication resources has emerged as a critical issue in the next generation (NG) communication systems. To overcome this, non-orthogonal multipleaccess (NOMA) has been shown to provide a beneficial spectral effi ciency gain, while supporting massive connectivity. sparse code multiple access (SCMA) is one of the NOMA schemes, but its application is hampered by its high-complexity multi-user detection. Fortunately, quantum search techniques were shown to substantially reduce the complexity of multi-user detectors (MUD). However, the quantum search-aided multiuser detection of SCMA is an open problem at the time of writing. Hence, we conceive a pair of quantum search-aided MUDs for SCMA, namely, a quantum-assisted message passing algorithm (Q-MPA)-based MUD and a quantum-assisted sphere decoder-based MPA (QSD-MPA) MUD.
sparse code multiple access (SCMA) is a promising technology to provide high throughput and overall improved system performance at affordable cost for next-generation passive optical networks (NG-PONs). Message passin...
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sparse code multiple access (SCMA) is a promising technology to provide high throughput and overall improved system performance at affordable cost for next-generation passive optical networks (NG-PONs). Message passing algorithm (MPA) based on a factor graph is usually used for low-complexity multi-user detection in SCMA. However, MPA requires accurate and effective channel estimation due to the interference between the user's signals on the same resource block and suffers uncertain convergence caused by the cycles in the factor graph. In this paper, a graph neural networks (GNN)-based detection method is proposed for SCMA-PON, which performs channel impairment compensation and signal detection in a joint manner. 25.5 Gb/s SCMA-OFDM system over 20/60 km single mode fiber link is simulated to demonstrate the feasibility with 8.5-G class optical devices. The simulation results show that GNN-based detection method outperforms MPA and is more robust to the nonlinear distortion for the same level of computational complexity.
The sparse code multiple access (SCMA) is a promising candidate for bandwidth-efficient next generation wireless communications, since it can support more users than the number of resource elements. On the same note, ...
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The sparse code multiple access (SCMA) is a promising candidate for bandwidth-efficient next generation wireless communications, since it can support more users than the number of resource elements. On the same note, faster-than-Nyquist (FTN) signaling can also be used to improve the spectral efficiency. Hence in this paper, we consider a combined uplink FTN-SCMA system in which the data symbols corresponding to a user are further packed using FTN signaling. As a result, a higher spectral efficiency is achieved at the cost of introducing intentional inter-symbol interference (ISI). To perform joint channel estimation and detection, we design a low complexity iterative receiver based on the factor graph framework. In addition, to reduce the signaling overhead and transmission latency of our SCMA system, we intrinsically amalgamate it with grant-free scheme. Consequently, the active and inactive users should be distinguished. To address this problem, we extend the aforementioned receiver and develop a new algorithm for jointly estimating the channel state information, detecting the user activity and for performs data detection. In order to further reduce the complexity, an energy minimization based approximation is employed for restricting the user state to Gaussian. Finally, a hybrid message passing algorithm is conceived. Our Simulation results show that the FTN-SCMA system relying on the proposed receiver design has a higher throughput than conventional SCMA scheme at a negligible performance loss.
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