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Zhiguo Ding

Publications and source records attributed to Zhiguo Ding.

At least 199 records · Page 11Linked to original sources
arXiv2021

IRS-Assisted Massive MIMO-NOMA Networks: Exploiting Wave Polarization

A dual-polarized intelligent reflecting surface (IRS) can contribute to a better multiplexing of interfering wireless users. In this paper, we use this feature to improve the performance of dual-polarized massive multiple-input multiple-output (MIMO) with non-orthogonal multiple access (NOMA) under imperfect successive interference cancellation (SIC). By considering the downlink of a multi-cluster scenario, the IRSs assist the base station (BS) to multiplex subsets of users in the polarization domain. Our novel strategy alleviates the impact of imperfect SIC and enables users to exploit polarization diversity with near-zero inter-subset interference. To this end, the IRSs are optimized to mitigate transmissions originated at the BS from the interfering polarization. The formulated optimization is transformed into quadratic constrained quadratic sub-problems, which makes it possible to obtain the optimal solution via interior-points methods. We also derive analytically a closed-form expression for the users' ergodic rates by considering large numbers of reflecting elements. This is followed by representative simulation examples and comprehensive discussions. The results show that when the IRSs are large enough, the proposed scheme always outperforms conventional massive MIMO-NOMA and MIMO-OMA systems even if SIC error propagation is present. It is also confirmed that dual-polarized IRSs can make cross-polar transmissions beneficial to the users, allowing them to improve their performance through diversity.

eess.SP↗
arXiv2021

The Interplay of Reconfigurable Intelligent Surfaces and Mobile Edge Computing in Future Wireless Networks: A Win-Win Strategy to 6G

Reconfigurable intelligent surface (RIS)-empowered communication is being considered as an enabling technology for sixth generation (6G) wireless networks. The key idea of RIS-assisted communication is to enhance the capacity, coverage, energy efficiency, physical layer security, and many other aspects of modern wireless networks. At the same time, mobile edge computing (MEC) has already shown its huge potential by extending the computation, communication, and caching capabilities of a standalone cloud server to the network edge. In this article, we first provide an overview of how MEC and RIS can benefit each other. We envision that the integration of MEC and RIS will bring an unprecedented transformation to the future evolution of wireless networks. We provide a system-level perspective on the MEC-aided RIS (and RIS-assisted MEC) that will evolve wireless network towards 6G. We also outline some of the fundamental challenges that pertain to the implementation of MEC-aided RIS (and RIS-assisted MEC) networks. Finally, the key research trends in the RIS-assisted MEC are discussed.

cs.NI↗
arXiv2021

No-Pain No-Gain: DRL Assisted Optimization in Energy-Constrained CR-NOMA Networks

This paper applies machine learning to optimize the transmission policy of cognitive radio inspired non-orthogonal multiple access (CR-NOMA) networks, where time-division multiple access (TDMA) is used to serve multiple primary users and an energy-constrained secondary user is admitted to the primary users' time slots via NOMA. During each time slot, the secondary user performs the two tasks: data transmission and energy harvesting based on the signals received from the primary users. The goal of the paper is to maximize the secondary user's long-term throughput, by optimizing its transmit power and the time-sharing coefficient for its two tasks. The long-term throughput maximization problem is challenging due to the need for making decisions that yield long-term gains but might result in short-term losses. For example, when in a given time slot, a primary user with large channel gains transmits, intuition suggests that the secondary user should not carry out data transmission due to the strong interference from the primary user but perform energy harvesting only, which results in zero data rate for this time slot but yields potential long-term benefits. In this paper, a deep reinforcement learning (DRL) approach is applied to emulate this intuition, where the deep deterministic policy gradient (DDPG) algorithm is employed together with convex optimization. Our simulation results demonstrate that the proposed DRL assisted NOMA transmission scheme can yield significant performance gains over two benchmark schemes.

cs.IT↗
arXiv2021

NOMA for Next-generation Massive IoT: Performance Potential and Technology Directions

Broader applications of the Internet of Things (IoT) are expected in the forthcoming 6G system, although massive IoT is already a key scenario in 5G, predominantly relying on physical layer solutions inherited from 4G LTE and primarily using orthogonal multiple access (OMA). In 6G IoT, supporting a massive number of connections will be required for diverse services of the vertical sectors, prompting fundamental studies on how to improve the spectral efficiency of the system. One of the key enabling technologies is non-orthogonal multiple access (NOMA). This paper consists of two parts. In the first part, finite block length theory and the diversity order of multi-user systems will be used to show the significant potential of NOMA compared to traditional OMA. The supremacy of NOMA over OMA is particularly pronounced for asynchronous contention-based systems relying on imperfect link adaptation, which are commonly assumed for massive IoT systems. To approach these performance bounds, in the second part of the paper, several promising technology directions are proposed for 6G massive IoT, including linear spreading, joint spreading & modulation, multi-user channel coding in the context of various techniques for practical uncoordinated transmissions, cell-free operations, etc., from the perspective of NOMA.

cs.IT↗
arXiv2021

DRL-Assisted Resource Allocation for NOMA-MEC Offloading with Hybrid SIC

Multi-access edge computing (MEC) and non-orthogonal multiple access (NOMA) have been regarded as promising technologies to improve computation capability and offloading efficiency of the mobile devices in the sixth generation (6G) mobile system. This paper mainly focuses on the hybrid NOMA-MEC system, where multiple users are first grouped into pairs, and users in each pair offload their tasks simultaneously by NOMA, and then a dedicated time duration is scheduled to the more delay-tolerable user for uploading the remaining data by orthogonal multiple access (OMA). For the conventional NOMA uplink transmission, successive interference cancellation (SIC) is applied to decode the superposed signals successively according to the channel state information (CSI) or the quality of service (QoS) requirement. In this work, we integrate the hybrid SIC scheme which dynamically adapts the SIC decoding order among all NOMA groups. To solve the user grouping problem, a deep reinforcement learning (DRL) based algorithm is proposed to obtain a close-to-optimal user grouping policy. Moreover, we optimally minimize the offloading energy consumption by obtaining the closed-form solution to the resource allocation problem. Simulation results show that the proposed algorithm converges fast, and the NOMA-MEC scheme outperforms the existing orthogonal multiple access (OMA) scheme.

cs.IT↗
arXiv2021

Connecting two types of representations of a permutation of $\F_q$

In this paper, we connect two types of representations of a permutation $σ$ of the finite field $\F_q$. One type is algebraic, in which the permutation is represented as the composition of degree-one polynomials and $k$ copies of $x^{q-2}$, for some prescribed value of $k$. The other type is combinatorial, in which the permutation is represented as the composition of a degree-one rational function followed by the product of $k$ $2$-cycles on $\bP^1(\F_q):=\F_q\cup\{\infty\}$, where each $2$-cycle moves $\infty$. We show that, after modding out by obvious equivalences amongst the algebraic representations, then for each $k$ there is a bijection between the algebraic representations of $σ$ and the combinatorial representations of $σ$. We also prove analogous results for permutations of $\bP^1(\F_q)$. One consequence is a new characterization of the notion of Carlitz rank of a permutation on $\F_q$, which we use elsewhere to provide an explicit formula for the Carlitz rank. Another consequence involves a classical theorem of Carlitz, which says that if $q>2$ then the group of permutations of $\F_q$ is generated by the permutations induced by degree-one polynomials and $x^{q-2}$. Our bijection provides a new perspective from which the two proofs of this result in the literature can be seen to arise naturally, without requiring the clever tricks that previously appeared to be needed in order to discover those proofs.

math.NT↗
arXiv2021

Tangent-Chebyshev rational maps and Redei functions

Recently Lima and Campello de Souza introduced a new class of rational functions over odd-order finite fields, and explained their potential usefulness in cryptography. We show that these new functions are conjugate to the classical family of Redei rational functions, so that the properties of the new functions follow from properties of Redei functions. We also prove new properties of these functions, and introduce analogous functions in characteristic 2, while also introducing a new version of trigonometry over finite fields of even order, which is of independent interest.

cs.CR↗
arXiv2021

The relative Riemann-Hurwitz formula

For any nonconstant f,g in C(x) such that the numerator H(x,y) of f(x)-g(y) is irreducible, we compute the genus of the normalization of the curve H(x,y)=0. We also prove an analogous formula in arbitrary characteristic when f and g have no common wildly ramified branch points, and generalize to (possibly reducible) fiber products of nonconstant morphisms of curves f:A-->D and g:B-->D.

math.AG↗
arXiv2021

A new family of exceptional rational functions

For each odd prime power q, we construct an infinite sequence of rational functions f(X) in F_q(X), each of which is exceptional, which means that for infinitely many n the map c-->f(c) induces a bijection of P^1(F_{q^n}). Moreover, each of our functions f(X) is indecomposable, which means that it cannot be written as the composition of lower-degree rational functions in F_q(X). In case q is not a power of 3, these are the first known examples of indecomposable exceptional rational functions f(X) over F_q which have non-solvable monodromy groups and have arbitrarily large degree. These are also the first known examples of wildly ramified indecomposable exceptional rational functions f(X), other than linear changes of polynomials.

math.NT↗
arXiv2021

Joint Transmit Precoding and Reflect Beamforming Design for IRS-Assisted MIMO Cognitive Radio Systems

Cognitive radio (CR) is an effective solution to improve the spectral efficiency (SE) of wireless communications by allowing the secondary users (SUs) to share spectrum with primary users (PUs). Meanwhile, intelligent reflecting surface (IRS) has been recently proposed as a promising approach to enhance SE and energy efficiency (EE) of wireless communication systems through intelligently reconfiguring the channel environment. In this paper, we consider an IRS-assisted downlink CR system, in which a secondary access point (SAP) communicates with multiple SUs without affecting multiple PUs in the primary network and all nodes are equipped with multiple antennas. Our design objective is to maximize the achievable weighted sum rate (WSR) of SUs subject to the total transmit power constraint at the SAP and the interference constraints at PUs, by jointly optimizing the transmit precoding at the SAP and the reflecting coefficients at the IRS. To deal with the complex objective function, the problem is reformulated by employing the well-known weighted minimum mean-square error (WMMSE) method and an alternating optimization (AO)-based algorithm is proposed. Furthermore, a special scenario with only one PU is considered and AO algorithm is adopted again. It is worth mentioning that the proposed algorithm has a much lower computational complexity than the above algorithm without the performance loss. Finally, some numerical simulations have been provided to demonstrate that the proposed algorithm outperforms other benchmark schemes.

cs.IT↗
arXiv2021

On the Application of BAC-NOMA to 6G umMTC

This letter studies the application of backscatter communications (BackCom) assisted non-orthogonal multiple access (BAC-NOMA) to the envisioned sixth-generation (6G) ultra-massive machine type communications (umMTC). In particular, the proposed BAC-NOMA transmission scheme can realize simultaneous energy and spectrum cooperation between uplink and downlink users, which is important to support massive connectivity and stringent energy constraints in umMTC. Furthermore, a resource allocation problem for maximizing the uplink throughput and suppressing the interference between downlink and uplink transmission is formulated as an optimization problem and the corresponding optimal resource allocation policy is obtained. Computer simulations are provided to demonstrate the superior performance of BAC-NOMA.

cs.IT↗
arXiv2021

Non-Orthogonal Multiple Access for UAV-Aided Heterogeneous Networks: A Stochastic Geometry Model

In this work, we explore the potential benefits of deploying unmanned aerial vehicles (UAVs) as aerial base stations (ABSs) with sub-6GHz band and small cells terrestrial base stations (TBSs) with millimeter wave (mmWave) band in a hybrid heterogeneous networks (HetNets). A flexible non-orthogonal multiple access (NOMA) based user association policy is proposed. By using the tools from stochastic geometry, new analytical expressions for association probability, coverage probability and spectrum efficiency are derived for characterizing the performance of UAV-aided HetNets under the realistic Air-to-Ground (A2G) channels and the Ground-to-Ground (G2G) channels with a LoS ball blockage model. Finally, we provide insights on the proposed hybrid HetNets by numerical results. We confirm that i) the proposed NOMA enabled HetNets is capable of achieving superior performance compared with the OMA enabled ABSs by setting power allocation factors and targeted signal-to-interference-plus-noise ratio (SINR) threshold properly; ii) there is a tradeoff between the association probabilities and the spectrum efficiency in the NOMA enabled ABSs tier; iii) the coverage probability and spectrum efficiency of the NOMA enabled ABSs tier is largely affected by the imperfect successive interference cancellation (ipSIC) coefficient, power allocation factors and SINR threshold; iv) compared with only sub-6GHz ABSs, mmWave enabled TBSs are capable of enhancing the spectrum efficiency of the HetNets when the mmWave line-of-sight (LoS) link is available.

cs.IT↗
arXiv2021

Complementary Waveforms for Range-Doppler Sidelobe Suppression Based on a Null Space Approach

While Doppler resilient complementary waveforms have previously been considered to suppress range sidelobes within a Doppler interval of interest in radar systems, their capability of Doppler resilience has not been fully utilized. In this paper, a new construction of Doppler resilient complementary waveforms based on a null space is proposed. With this new construction, one can flexibly include a specified Doppler interval of interest or even an overall Doppler interval into a term which results in range sidelobes. We can force this term to zero, which can be solved to obtain a null space. From the null space, the characteristic vector to control the transmission of basic Golay waveforms, and the coefficients of the receiver filter for Golay complementary waveform can be extracted. Besides, based on the derived null space, two challenging non-convex optimization problems are formulated and solved for maximizing the signal-to-noise ratio (SNR). Moreover, the coefficients of the receiver filter and the characteristic vector can be applied to fully polarimetric radar systems to achieve nearly perfect Doppler resilient performance, and hence fully suppress the inter-antenna interferences.

cs.IT↗
arXiv2021

Exploiting Deep Learning for Secure Transmission in an Underlay Cognitive Radio Network

This paper investigates a machine learning-based power allocation design for secure transmission in a cognitive radio (CR) network. In particular, a neural network (NN)-based approach is proposed to maximize the secrecy rate of the secondary receiver under the constraints of total transmit power of secondary transmitter, and the interference leakage to the primary receiver, within which three different regularization schemes are developed. The key advantage of the proposed algorithm over conventional approaches is the capability to solve the power allocation problem with both perfect and imperfect channel state information. In a conventional setting, two completely different optimization frameworks have to be designed, namely the robust and non-robust designs. Furthermore, conventional algorithms are often based on iterative techniques, and hence, they require a considerable number of iterations, rendering them less suitable in future wireless networks where there are very stringent delay constraints. To meet the unprecedented requirements of future ultra-reliable low-latency networks, we propose an NN-based approach that can determine the power allocation in a CR network with significantly reduced computational time and complexity. As this trained NN only requires a small number of linear operations to yield the required power allocations, the approach can also be extended to different delay sensitive applications and services in future wireless networks. When evaluate the proposed method versus conventional approaches, using a suitable test set, the proposed approach can achieve more than 94% of the secrecy rate performance with less than 1% computation time and more than 93% satisfaction of interference leakage constraints. These results are obtained with significant reduction in computational time, which we believe that it is suitable for future real-time wireless applications.

cs.IT↗
arXiv2020

Grant-Free Random Access in Machine-Type Communication: Approaches and Challenges

Massive machine-type communication (MTC) is expected to play a key role in supporting Internet of Things (IoT) applications such as smart cities, smart factory, and connected vehicles through cellular networks. MTC is characterized by a large number of MTC devices and their sparse activities, which are difficult to be supported by conventional approaches and motivate the design of new access technologies. In particular, in the 5th generation (5G), grant-free or 2-step random access schemes are introduced for MTC to be more efficient by reducing signaling overhead. In this article, we first introduce grant-free random access and discuss how it can be modified with massive multiple-input multiple-output (MIMO) to exploit a high spatial multiplexing gain. We then explain preamble designs that can improve the performance and variations based on the notion of non-orthogonal multiple access (NOMA). Finally, design challenges of grant-free random access towards next generation cellular systems are presented.

cs.IT↗
arXiv2020

Covert Communication in Intelligent Reflecting Surface-Assisted NOMA Systems: Design, Analysis, and Optimization

In this paper, we investigate covert communication in an intelligent reflecting surface (IRS)-assisted non-orthogonal multiple access (NOMA) system, where a legitimate transmitter (Alice) applies NOMA for downlink and uplink transmissions with a covert user (Bob) and a public user (Roy) aided by an IRS. Specifically, we propose new IRS-assisted downlink and uplink NOMA schemes to hide the existence of Bob's covert transmission from a warden (Willie), which cost-effectively exploit the phase-shift uncertainty of the IRS and the non-orthogonal signal transmission of Roy as the cover medium without requiring additional uncertainty sources. Assuming the worst-case covert communication scenario where Willie can optimally adjust the detection threshold for his detector, we derive an analytical expression for the minimum average detection error probability of Willie achieved by each of the proposed schemes. To further enhance the covert communication performance, we propose to maximize the covert rates of Bob by jointly optimizing the transmit power and the IRS reflect beamforming, subject to given requirements on the covertness against Willie and the quality-of-service (QoS) at Roy. Simulation results demonstrate the covertness advantage of the proposed schemes and confirm the accuracy of the derived analytical results. Interestingly, it is found that covert communication is impossible without using IRS or NOMA for the considered setup while the proposed schemes can always guarantee positive covert rates.

cs.IT↗
arXiv2020

Multiple Transmit Power Levels based NOMA for Massive Machine-type Communications

This paper proposes a tractable solution for integrating non-orthogonal multiple access (NOMA) into massive machine-type communications (mMTC) to increase the uplink connectivity. Multiple transmit power levels are provided at the user end to enable open-loop power control, which is absent from the traditional uplink NOMA with the fixed transmit power. The basics of this solution are firstly presented to analytically show the inherent performance gain in terms of the average arrival rate (AAR). Then, a practical framework based on a novel power map is proposed to associate a set of well-designed transmit power levels with each geographical region for handling the no instantaneous channel state information problem. Based on this framework, the semi-grant-free (semi-GF) transmission with two practical protocols is introduced to enhance the connectivity, which has higher AAR than both the conventional grand-based and GF transmissions. When the number of active GF devices in mMTC far exceeds the available resource blocks, the corresponding AAR tends to zero. To solve this problem, user barring techniques are employed into the semi-GF transmission to stable the traffic flow and thus increase the AAR. Lastly, promising research directions are discussed for improving the proposed networks.

cs.IT↗