We propose a joint channel estimation and signal detection technique for the uplink non-orthogonal multiple access using an unsupervised clustering approach. We apply the Gaussian mixture model to cluster received signals and accordingly optimize the decision regions to enhance the symbol error rate (SER). We show that when the received powers of the users are sufficiently different, the proposed clustering-based approach with no channel state information (CSI) at the receiver achieves an SER performance similar to that of the conventional maximum likelihood detector with full CSI. Since the accuracy of the utilized clustering algorithm depends on the number of the data points available at the receiver, the proposed technique delivers a tradeoff between the accuracy and block length.
As a means to support the access of massive machine-type communication devices, grant-free access and non-orthogonal multiple access (NOMA) have received great deal of attention in recent years. In the grant-free transmission, each device transmits information without the granting process so that the basestation needs to identify the active devices among all potential devices. This process, called an active user detection (AUD), is a challenging problem in the NOMA-based systems since it is difficult to identify active devices from the superimposed received signal. An aim of this paper is to p…
Both faster than Nyquist (FTN) signaling and non-orthogonal multiple access (NOMA) are promising next generation wireless communications techniques as a benefit of their capability of improving the system's spectral efficiency. This paper considers an uplink system that combines the advantages of FTN and NOMA. Consequently, an improved spectral efficiency is achieved by deliberately introducing both inter-symbol interference (ISI) and inter-user interference (IUI). More specifically, we propose a grant-free transmission scheme to reduce the signaling overhead and transmission latency of the co…
Grant-free non-orthogonal multiple access (NOMA) is considered as one of the supporting technology for massive connectivity for future networks. In the grant-free NOMA systems with a massive number of users, user activity detection is of great importance. Existing multi-user detection (MUD) techniques rely on complicated update steps which may cause latency in signal detection. In this paper, we propose a generative neural network-based MUD (GenMUD) framework to utilize low-complexity neural networks, which are trained to reconstruct signals in a small fixed number of steps. By exploiting the …
For massive machine-type communications, centralized control may incur a prohibitively high overhead. Grant-free non-orthogonal multiple access (NOMA) provides possible solutions, yet poses new challenges for efficient receiver design. In this paper, we develop a joint user identification, channel estimation, and signal detection (JUICESD) algorithm. We divide the whole detection scheme into two modules: slot-wise multi-user detection (SMD) and combined signal and channel estimation (CSCE). SMD is designed to decouple the transmissions of different users by leveraging the approximate message p…
Uplink (UL) dominated sporadic transmission and stringent latency requirement of massive machine type communication (mMTC) forces researchers to abandon complicated grant-acknowledgment based legacy networks. UL grant-free non-orthogonal multiple access (NOMA) provides an array of features which can be harnessed to efficiently solve the problem of massive random connectivity and latency. Because of the inherent sparsity in user activity pattern in mMTC, the trend of existing literature specifically revolves around compressive sensing based multi user detection (CS-MUD) and Bayesian framework p…
In this paper, we consider the problem of activity detection in grant-free code-domain non-orthogonal multiple access (NOMA). We focus on performing activity detection via subspace methods under a setup where the data and pilot spreading signatures are of different lengths, and consider a realistic frame-structure similar to existing mobile networks. We investigate the impact of channel correlation on the activity detection performance; first, we consider the case where the channel exhibits high correlation in time and frequency and show how it can heavily deteriorate the performance. To tackl…
Massive machine-type communications (mMTC) is one of the main three focus areas in the 5th generation (5G) of mobile standards to enable connectivity of a massive number of internet of things (IoT) devices with little or no human intervention. In conventional human-type communications (HTC), due to the limited number of available radio resources and orthogonal/non-overlapping nature of existing resource allocation techniques, users need to compete for connectivity through a random access (RA) process, which may turn into a performance bottleneck in mMTC. In this context, non-orthogonal multipl…
Massive machine-type communications (mMTC) is a crucial scenario to support booming Internet of Things (IoTs) applications. In mMTC, although a large number of devices are registered to an access point (AP), very few of them are active with uplink short packet transmission at the same time, which requires novel design of protocols and receivers to enable efficient data transmission and accurate multi-user detection (MUD). Aiming at this problem, grant-free non-orthogonal multiple access (GF-NOMA) protocol is proposed. In GF-NOMA, active devices can directly transmit their preambles and data sy…
Grant-free non-orthogonal multiple access (NOMA) scheme is considered as a promising candidate for the enabling of massive connectivity and reduced signalling overhead for Internet of Things (IoT) applications in massive machine-type communication (mMTC) networks. Exploiting the inherent nature of sporadic transmissions in the grant-free NOMA systems, compressed sensing based multiuser detection (CS-MUD) has been deemed as a powerful solution to user activity detection (UAD) and data detection (DD). In this paper, block coordinate descend (BCD) method is employed in CS-MUD to reduce the comput…
Non-orthogonal multiple access (NOMA) is recognized as a promising radio access technique for the next generation wireless systems. We consider a practical downlink NOMA system with imperfect successive interference cancellation and derive bounds on the power allocation factors for a given number of users in each cluster. We propose a minimum signal-to-interference-plus-noise ratio difference criterion between two successive NOMA users in a cluster of users to achieve higher rates than an equivalent orthogonal multiple access (OMA) system. We then propose adaptive multi-user clustering and pow…
The flourishing low-Earth orbit (LEO) constellation communication network provides a promising solution for seamless coverage services to Internet-of-Things (IoT) terminals. However, confronted with massive connectivity and rapid variation of terrestrial-satellite link (TSL), the traditional grant-free random-access schemes always fail to match this scenario. In this paper, a new non-orthogonal multiple-access (NOMA) transmission protocol that incorporates orthogonal time frequency space (OTFS) modulation is proposed to solve these problems. Furthermore, we propose a two-stages joint active us…
Non-orthogonal multiple access (NOMA) and mmWave are two complementary technologies that can support the capacity demand that arises in 5G and beyond networks. The increasing number of users are served simultaneously while providing a solution for the scarcity of the bandwidth. In this paper we present a method for clustering the users in a mmWave-NOMA system with the objective of maximizing the sum-rate. An unsupervised machine learning technique, namely, hierarchical clustering is utilized which does the automatic identification of the optimal number of clusters. The simulations prove that t…
Recently, grant-free transmission paradigm has been introduced for massive Internet of Things (IoT) networks to save both time and bandwidth and transmit the message with low latency. In order to accurately decode the message of each device at the base station (BS), first, the active devices at each transmission frame must be identified. In this work, first we investigate the problem of activity detection as a threshold comparing problem. We show the convexity of the activity detection method through analyzing its probability of error which makes it possible to find the optimal threshold for m…
With the blooming of Internet-of-Things (IoT), we are witnessing an explosion in the number of IoT terminals, triggering an unprecedented demand for ubiquitous wireless access globally. In this context, the emerging low-Earth-orbit satellites (LEO-SATs) have been regarded as a promising enabler to complement terrestrial wireless networks in providing ubiquitous connectivity and bridging the ever-growing digital divide in the expected next-generation wireless communications. Nevertheless, the harsh conditions posed by LEO-SATs have imposed significant challenges to the current multiple access (…
Terahertz (THz) band communication has been widely studied to meet the future demand for ultra-high capacity. In addition, multi-input multi-output (MIMO) technique and non-orthogonal multiple access (NOMA) technique with multi-antenna also enable the network to carry more users and provide multiplexing gain. In this paper, we study the maximization of energy efficiency (EE) problem in THz-NOMA-MIMO systems for the first time. And the original optimization problem is divided into user clustering, hybrid precoding and power optimization. Based on channel correlation characteristics, a fast conv…
The superior spectral efficiency (SE) and user fairness feature of non-orthogonal multiple access (NOMA) systems are achieved by exploiting user clustering (UC) more efficiently. However, a random UC certainly results in a suboptimal solution while an exhaustive search method comes at the cost of high complexity, especially for systems of medium-to-large size. To address this problem, we develop two efficient unsupervised machine learning (ML) based UC algorithms, namely k-means++ and improved k-means++, to effectively cluster users into disjoint clusters in cell-free massive multiple-input mu…
Non-orthogonal multiple access (NOMA) allows multiple users to share a time-frequency resource block by using different power levels. An important challenge associated with NOMA is the selection of users that share a resource block. This is referred to as clustering, which generally exploits the channel disparity (i.e. distinctness) among the users. We discuss clustering and the related resource allocation challenges (e.g. power allocation) associated with NOMA and highlight open problems that require further investigation. We review the related literature on exploiting channel disparity for c…
This paper investigates the massive connectivity of low Earth orbit (LEO) satellite-based Internet-of-Things (IoT) for seamless global coverage. We propose to integrate the grant-free non-orthogonal multiple access (GF-NOMA) paradigm with the emerging orthogonal time frequency space (OTFS) modulation to accommodate the massive IoT access, and mitigate the long round-trip latency and severe Doppler effect of terrestrial-satellite links (TSLs). On this basis, we put forward a two-stage successive active terminal identification (ATI) and channel estimation (CE) scheme as well as a low-complexity …
This paper studies the joint channel estimation and signal detection for the uplink power-domain non-orthogonal multiple access. The proposed technique performs both detection and estimation without the need of pilot symbols by using a clustering technique. We apply rotational-invariant coding to assist signal detection at the receiver without sending pilot symbols. We utilize Gaussian mixture model (GMM) to automatically cluster the received signals without supervision and optimize decision boundaries to improve the bit error rate (BER) performance. Simulation results show that the proposed s…
Integrating unmanned aerial vehicles (UAV) to non-orthogonal multiple access (NOMA) visible light communications (VLC) exposes many potentials over VLC and NOMA-VLC systems. In this circumstance, user grouping is of importance to reduce the NOMA decoding complexity when the number of users is large; however, this issue has not been considered in the existing study. In this paper, we aim to maximize the weighted sum-rate of all the users by jointly optimizing UAV placement, user grouping, and power allocation in downlink NOMA-VLC systems. We first consider an efficient user clustering strategy,…
The proliferating number of devices with short payloads as well as low power budget has already driven researchers away from classical grant-based access schemes that are notorious for their large signalling overhead as well as power-consuming retransmissions. Instead, light-weight random access protocols have been re-investigated and their throughput has been improved in orders of magnitude with sophisticated yet still low-complex transceiver algorithms. In fact, grant-free access has been identified as a key medium access control technique for providing massive connectivity in machine type c…
This paper considers uplink multiple access (MA) transmissions, where the MA technique is adaptively selected between Non Orthogonal Multiple Access (NOMA) and Orthogonal Multiple Access (OMA). Two types of users, namely Internet of Things (IoT) and enhanced mobile broadband (eMBB) coexist with different metrics to be optimized, energy efficiency (EE) for IoT and spectral efficiency (SE) for eMBB. The corresponding multi-objective power allocation problems aiming at maximizing a weighted sum of EE and SE are solved for both NOMA and OMA. Based on the identification of the best MA strategy, a c…
Efficient Resource Allocation in 5G Massive MIMO-NOMA Networks: Comparative Analysis of SINR-Aware Power Allocation and Spatial Correlation-Based Clustering
This paper proposes a millimeter wave-NOMA (mmWave-NOMA) system that takes into account the end-user signal processing capabilities, an important practical consideration. The implementation of NOMA in the downlink (DL) direction requires successive interference cancellation (SIC) to be performed at the user terminals, which comes at the cost of additional complexity. In NOMA, the weakest user only has to decode its own signal, while the strongest user has to decode the signals of all other users in the SIC procedure. Hence, the additional implementation complexity required of the user to perfo…
We propose a joint channel estimation and signal detection approach for the uplink non-orthogonal multiple access (NOMA) using unsupervised machine learning. We apply a Gaussian mixture model (GMM) to cluster the received signals, and accordingly optimize the decision regions to enhance the symbol error rate (SER) performance. We show that, when the received powers of the users are sufficiently different, the proposed clustering-based approach achieves an SER performance on a par with that of the conventional maximum-likelihood detector (MLD) with full channel state information (CSI). We study…
Cooperative and cognitive non-orthogonal multiple access (CCR-NOMA) has been recognized as a promising technique to overcome issues of spectrum scarcity and support massive connectivity envisioned in next-generation wireless networks. In this paper, we investigate the deployment of an unmanned aerial vehicle (UAV) as a relay that fairly serves a large number of secondary users in a hot-spot region. The UAV deployment algorithm must jointly account for user clustering, channel assignment, and resource allocation sub-problems. We propose a solution methodology that obtains user clustering and ch…
Tailor-made for massive connectivity and sporadic access, grant-free random access has become a promising candidate access protocol for massive machine-type communications (mMTC). Compared with conventional grant-based protocols, grant-free random access skips the exchange of scheduling information to reduce the signaling overhead, and facilitates sharing of access resources to enhance access efficiency. However, some challenges remain to be addressed in the receiver design, such as unknown identity of active users and multi-user interference (MUI) on shared access resources. In this work, we …
In this work, we consider a downlink NOMA network with multiple single-antenna users and multi-antenna UAVs. In particular, the users are spatially located in several clusters by following the Poisson Cluster Process and each cluster is served by a hovering UAV with NOMA. For practical considerations, we assume that only imperfect CSI of each user is available at the UAVs. Based on this model, the problem of joint user clustering and robust beamforming design is formulated to minimize the sum transmission power, and meanwhile, guarantee the QoS requirements of users. Due to the integer variabl…
This paper investigates the benefits of integrating reconfigurable intelligent surface (RIS) on minimizing the average sum age of information (AoI) in uplink non-orthogonal multiple access-based Internet-of-Things (IoT) networks. In this setup, an optimization problem is formulated to optimize the RIS configuration, the transmit power per IoT device and the clustering policy of IoT devices. The formulated problem is a mixed-integer non-convex one, and in order to solve it we obtain first the RIS configuration by adopting a semi-definite relaxation (SDR) approach. Afterwards, the joint power al…
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 cance…
This paper investigates the coexistence of non-orthogonal multiple access (NOMA) and full-duplex (FD) to improve both spectral efficiency (SE) and user fairness. In such a scenario, NOMA based on the successive interference cancellation technique is simultaneously applied to both uplink (UL) and downlink (DL) transmissions in an FD system. We consider the problem of jointly optimizing user association (UA) and power control to maximize the overall SE, subject to user-specific quality-of-service and total transmit power constraints. To be spectrally-efficient, we introduce the tensor model to o…
Future wireless networks need to support massive machine type communication (mMTC) where a massive number of devices accesses the network and massive MIMO is a promising enabling technology. Massive access schemes have been studied for co-located massive MIMO arrays. In this paper, we investigate the activity detection in grant-free random access for mMTC in cell-free massive MIMO networks using distributed arrays. Each active device transmits a non-orthogonal pilot sequence to the access points (APs) and the APs send the received signals to a central processing unit (CPU) for joint activity d…
This paper investigates the benefits of integrating multiple reconfigurable intelligent surfaces (RISs) in enhancing the timeliness performance of uplink Internet-of-Things (IoT) network, where IoT devices (IoTDs) upload their time-stamped status update information to a base station (BS) using non-orthogonal multiple access (NOMA). Accounting to the potential unreliable wireless channels due to the impurities of the propagation environments, such as deep fading, blockages, etc., multiple RISs are deployed in the considered IoT network to mitigate the propagation-induced impairments, to enhance…
False-CSI Attacks in Power-Domain NOMA for 6G: A Threat Taxonomy and System-Level Impacts
Young Talents Lyceum of Baku State University（巴库国立大学青年才俊中学）；Computer Engineering Department at the University of Bahrain（巴林大学计算机工程系）；University of Michigan–Flint（密歇根大学弗林特分校）
In this paper, we investigate the resource allocation for uplink non-orthogonal multiple access (NOMA) enabled low-power wide-area (LPWA) networks to support the massive connectivity of users/nodes. Here, LPWA nodes communicate with a central gateway through resource blocks like channels, transmission times, bandwidths, etc. The nodes sharing the same resource blocks suffer from intra-cluster interference and possibly inter-cluster interference, which makes current LPWA networks unable to support the massive connectivity. Using the minimum transmission rate metric to highlight the interference…
A high success rate of grant-free random access scheme is proposed to support massive access for machine-to-machine communications in massive multipleinput multiple-output systems. This scheme allows active user equipments (UEs) to transmit their modulated uplink messages along with super pilots consisting of multiple sub-pilots to a base station (BS). Then, the BS performs channel state information (CSI) estimation and uplink message decoding by utilizing a proposed graph combined clustering independent component analysis (GCICA) decoding algorithm, and then employs the estimated CSIs to dete…
Massive machine-type communication (mMTC) is a newly introduced service category in 5G wireless communication systems to support a variety of Internet-of-Things (IoT) applications. In recovering sparsely represented multi-user vectors, compressed sensing based multi-user detection (CS-MUD) can be used. CS-MUD is a feasible solution to the grant-free uplink non-orthogonal multiple access (NOMA) environments. In CS-MUD, active user detection (AUD) and channel estimation (CE) should be performed before data detection. In this paper, we propose the expectation propagation based joint AUD and CE (E…
West Virginia University（西弗吉尼亚大学）；Air Force Institute of Technology（空军理工学院）
Accurate platform localization is an integral component of most robotic systems. As these robotic systems become more ubiquitous, it is necessary to develop robust state estimation algorithms that are able to withstand novel and non-cooperative environments. When dealing with novel and non-cooperative environments, little is known a priori about the measurement error uncertainty, thus, there is a requirement that the uncertainty models of the localization algorithm be adaptive. Within this paper, we propose the batch covariance estimation technique, which enables robust state estimation throug…
This work presents a novel framework for random access in crowded scenarios of multiple-input multiple-output(MIMO) systems. A multi-antenna base station (BS) and multiple single-antenna users are considered in these systems. A huge portion of the system resources is dedicated as orthogonal pilots for accurate channel estimation which imposes a huge training overhead. This overhead can be highly mitigated by exploiting intrinsic angular domain sparsity of massive MIMO channels and the sporadic traffic of users, i.e., few number of users are active to sent or receive data in each coherence inte…
