Showing papers on "Spectral efficiency published in 2018"

On the Total Energy Efficiency of Cell-Free Massive MIMO

Abstract: We consider the cell-free massive multiple-input multiple-output (MIMO) downlink, where a very large number of distributed multiple-antenna access points (APs) serve many single-antenna users in the same time-frequency resource. A simple (distributed) conjugate beamforming scheme is applied at each AP via the use of local channel state information (CSI). This CSI is acquired through time-division duplex operation and the reception of uplink training signals transmitted by the users. We derive a closed-form expression for the spectral efficiency taking into account the effects of channel estimation errors and power control. This closed-form result enables us to analyze the effects of backhaul power consumption, the number of APs, and the number of antennas per AP on the total energy efficiency, as well as, to design an optimal power allocation algorithm. The optimal power allocation algorithm aims at maximizing the total energy efficiency, subject to a per-user spectral efficiency constraint and a per-AP power constraint. Compared with the equal power control, our proposed power allocation scheme can double the total energy efficiency. Furthermore, we propose AP selections schemes, in which each user chooses a subset of APs, to reduce the power consumption caused by the backhaul links. With our proposed AP selection schemes, the total energy efficiency increases significantly, especially for large numbers of APs. Moreover, under a requirement of good quality-of-service for all users, cell-free massive MIMO outperforms the colocated counterpart in terms of energy efficiency.

Deep Learning for an Effective Nonorthogonal Multiple Access Scheme

Abstract: Nonorthogonal multiple access (NOMA) has been considered as an essential multiple access technique for enhancing system capacity and spectral efficiency in future communication scenarios. However, the existing NOMA systems have a fundamental limit: high computational complexity and a sharply changing wireless channel make exploiting the characteristics of the channel and deriving the ideal allocation methods very difficult tasks. To break this fundamental limit, in this paper, we propose a novel and effective deep learning (DL)-aided NOMA system, in which several NOMA users with random deployment are served by one base station. Since DL is advantageous in that it allows training the input signals and detecting sharply changing channel conditions, we exploit it to address wireless NOMA channels in an end-to-end manner. Specifically, it is employed in the proposed NOMA system to learn a completely unknown channel environment. A long short-term memory (LSTM) network based on DL is incorporated into a typical NOMA system, enabling the proposed scheme to detect the channel characteristics automatically. In the proposed strategy, the LSTM is first trained by simulated data under different channel conditions via offline learning, and then the corresponding output data can be obtained based on the current input data used during the online learning process. In general, we build, train and test the proposed cooperative framework to realize automatic encoding, decoding and channel detection in an additive white Gaussian noise channel. Furthermore, we regard one conventional user activity and data detection scheme as an unknown nonlinear mapping operation and use LSTM to approximate it to evaluate the data detection capacity of DL based on NOMA. Simulation results demonstrate that the proposed scheme is robust and efficient compared with conventional approaches. In addition, the accuracy of the LSTM -aided NOMA scheme is studied by introducing the well-known tenfold cross-validation procedure.

Modulation and Multiple Access for 5G Networks

Abstract: Fifth generation (5G) wireless networks face various challenges in order to support large-scale heterogeneous traffic and users, therefore new modulation and multiple access (MA) schemes are being developed to meet the changing demands. As this research space is ever increasing, it becomes more important to analyze the various approaches, therefore, in this paper we present a comprehensive overview of the most promising modulation and MA schemes for 5G networks. Unlike other surreys of 5G networks, this paper focuses on multiplexing techniques, including modulation techniques in orthogonal MA (OMA) and various types of non-OMA (NOMA) techniques. Specifically, we first introduce different types of modulation schemes, potential for OMA, and compare their performance in terms of spectral efficiency, out-of-band leakage, and bit-error rate. We then pay close attention to various types of NOMA candidates, including power-domain NOMA, code-domain NOMA, and NOMA multiplexing in multiple domains. From this exploration, we can identify the opportunities and challenges that will have the most significant impacts on modulation and MA designs for 5G networks.

Digital Beamforming-Based Massive MIMO Transceiver for 5G Millimeter-Wave Communications

Abstract: A 64-channel massive multiple-input multiple-output (MIMO) transceiver with a fully digital beamforming (DBF) architecture for fifth-generation millimeter-wave communications is presented in this paper. The DBF-based massive MIMO transceiver is operated at 28-GHz band with a 500-MHz signal bandwidth and the time division duplex mode. The antenna elements are arranged as a 2-D array, which has 16 columns (horizontal direction) and 4 rows (vertical direction) for a better beamforming resolution in the horizontal plane. To achieve half-wavelength element spacing in the horizontal direction, a new sectorial transceiver array design with a bent substrate-integrated waveguide is proposed. The measured results show that an excellent RF performance is achieved. The system performance is tested with the over-the-air technique to verify the feasibility of the proposed DBF-based massive MIMO transceiver for high data rate millimeter-wave communications. Using the beam-tracking technique and two streams of QAM-64 signals, the proposed millimeter-wave MIMO transceiver can achieve a steady 5.3-Gb/s throughput for a single user in fast mobile environments. In the multiple-user MIMO scenario, by delivering 20 noncoherent data streams to eight four-channel user terminals, it achieves a downlink peak data rate of 50.73 Gb/s with the spectral efficiency of 101.5 b/s/Hz.

5G Radio Network Design for Ultra-Reliable Low-Latency Communication

Abstract: 5G is currently being standardized and addresses, among other things, new URLLC services. These are characterized by the need to support reliable communication, where successful data transmission can be guaranteed within low latency bounds, like 1 ms, at a low failure rate. This article describes the functionality of both the NR and LTE radio interfaces to provide URLLC services. Achievable latency bounds are evaluated, and the expected spectral efficiency is demonstrated. It is shown that both NR and LTE can fulfill the ITU 5G requirements on URLLC; however, this comes at the cost of reduced spectral efficiency compared to mobile broadband services without latency or reliability constraints. Still, the impact on the overall network performance is expected to be moderate.

Deep Power Control: Transmit Power Control Scheme Based on Convolutional Neural Network

Abstract: In this letter, deep power control (DPC), which is the first transmit power control framework based on a convolutional neural network (CNN), is proposed. In DPC, the transmit power control strategy to maximize either spectral efficiency (SE) or energy efficiency (EE) is learned by means of a CNN. While conventional power control schemes require a considerable number of computations, in DPC, the transmit power of users can be determined using far fewer computations enabling real-time processing. We also propose a form of DPC that can be performed in a distributed manner with local channel state information, allowing the signaling overhead to be greatly reduced. Through simulations, we show that the DPC can achieve almost the same or even higher SE and EE than a conventional power control scheme, with a much lower computation time.

Propagation Models and Performance Evaluation for 5G Millimeter-Wave Bands

Abstract: Fifth-generation (5G) wireless networks are expected to operate at both microwave and millimeter-wave (mmWave) frequency bands, including frequencies in the range of 24 to 86 GHz. Radio propagation models are used to help engineers design, deploy, and compare candidate wireless technologies, and have a profound impact on the decisions of almost every aspect of wireless communications. This paper provides a comprehensive overview of the channel models that will likely be used in the design of 5G radio systems. We start with a discussion on the framework of channel models, which consists of classical models of path loss versus distance, large-scale, and small-scale fading models, and multiple-input multiple-output channel models. Then, key differences between mmWave and microwave channel models are presented, and two popular mmWave channel models are discussed: the 3rd Generation Partnership Project model, which is adopted by the International Telecommunication Union, and the NYUSIM model, which was developed from several years of field measurements in New York City. Examples on how to apply the channel models are then given for several diverse applications demonstrating the wide impact of the models and their parameter values, where the performance comparisons of the channel models are done with promising hybrid beamforming approaches, including leveraging coordinated multipoint transmission. These results show that the answers to channel performance metrics, such as spectrum efficiency, coverage, hardware/signal processing requirements, etc., are extremely sensitive to the choice of channel models.

A Tutorial on Nonorthogonal Multiple Access for 5G and Beyond

Abstract: Today’s wireless networks allocate radio resources to users based on the orthogonal multiple access (OMA) principle. However, as the number of users increases, OMA based approaches may not meet the stringent emerging requirements including very high spectral efficiency, very low latency, and massive device connectivity. Nonorthogonal multiple access (NOMA) principle emerges as a solution to improve the spectral efficiency while allowing some degree of multiple access interference at receivers. In this tutorial style paper, we target providing a unified model for NOMA, including uplink and downlink transmissions, along with the extensions to multiple input multiple output and cooperative communication scenarios. Through numerical examples, we compare the performances of OMA and NOMA networks. Implementation aspects and open issues are also detailed.

Spectral and Energy-Efficient Wireless Powered IoT Networks: NOMA or TDMA?

Abstract: Wireless powered communication networks (WPCNs), where multiple energy-limited devices first harvest energy in the downlink and then transmit information in the uplink, have been envisioned as a promising solution for the future Internet-of-Things (IoT). Meanwhile, nonorthogonal multiple access (NOMA) has been proposed to improve the system spectral efficiency (SE) of the fifth-generation (5G) networks by allowing concurrent transmissions of multiple users in the same spectrum. As such, NOMA has been recently considered for the uplink of WPCNs based IoT networks with a massive number of devices. However, simultaneous transmissions in NOMA may also incur more transmit energy consumption as well as circuit energy consumption in practice which is critical for energy constrained IoT devices. As a result, compared to orthogonal multiple access schemes such as time-division multiple access (TDMA), whether the SE can be improved and/or the total energy consumption can be reduced with NOMA in such a scenario still remains unknown. To answer this question, we first derive the optimal time allocations for maximizing the SE of a TDMA-based WPCN (T-WPCN) and a NOMA-based WPCN (N-WPCN), respectively. Subsequently, we analyze the total energy consumption as well as the maximum SE achieved by these two networks. Surprisingly, it is found that N-WPCN not only consumes more energy, but also is less spectral efficient than T-WPCN. Simulation results verify our theoretical findings and unveil the fundamental performance bottleneck, i.e., “worst user bottleneck problem”, in multiuser NOMA systems.

Energy-Efficient User Scheduling and Power Allocation for NOMA-Based Wireless Networks With Massive IoT Devices

Abstract: Nonorthogonal multiple access (NOMA) exhibits superiority in spectrum efficiency and device connections in comparison with the traditional orthogonal multiple access technologies. However, the nonorthogonality of NOMA also introduces intracell interference that has become the bottleneck limiting the performance to be further improved. To coordinate the intracell interference, we investigate the dynamic user scheduling and power allocation problem in this paper. Specifically, we formulate this problem as a stochastic optimization problem with the objective to minimize the total power consumption of the whole network under the constraint of all users’ long-term rate requirements. To tackle this challenging problem, we first transform it into a series of static optimization problems based on the stochastic optimization theory. Afterward, we exploit the special structure of the reformulated problem and adopt the branch-and-bound technique to devise an efficient algorithm, which can obtain the optimal control policies with a low complexity. As a good feature, the proposed algorithm can make decisions only according to the instantaneous system state and can guarantee the long-term network performance. Simulation results demonstrate that the proposed algorithm has good performance in convergence and outperforms other schemes in terms of power consumption and user satisfaction.

Terahertz Technologies to Deliver Optical Network Quality of Experience in Wireless Systems Beyond 5G

Abstract: This article discusses the basic system architecture for THz wireless links with bandwidths of more than 50 GHz into optical networks. New design principles and breakthrough technologies are required in order to demonstrate terabit- per-second data rates at near zero latency using the proposed system concept. Specifically, we present the concept of designing the baseband signal processing for both the optical and wireless links and using an E2E error correction approach for the combined link. We provide two possible electro-optical baseband interface architectures, namely transparent optical-link and digital- link architectures, which are currently under investigation. THz wireless link requirements are given as well as the main principles and research directions for the development of a new generation of transceiver front-ends that will be capable of operating at ultra-high spectral efficiency by employing higher-order modulation schemes. Moreover, we discuss the need for developing a novel THz network information theory framework, which will take into account the channel characteristics and the nature of interference in the THz band. Finally, we highlight the role of PBF, which is required in order to overcome the propagation losses, as well as the physical layer and medium access control challenges.

Deep Learning-Aided SCMA

Abstract: Sparse code multiple access (SCMA) is a promising code-based non-orthogonal multiple-access technique that can provide improved spectral efficiency and massive connectivity meeting the requirements of 5G wireless communication systems. We propose a deep learning-aided SCMA (D-SCMA) in which the codebook that minimizes the bit error rate (BER) is adaptively constructed, and a decoding strategy is learned using a deep neural network-based encoder and decoder. One benefit of D-SCMA is that the construction of an efficient codebook can be achieved in an automated manner, which is generally difficult due to the non-orthogonality and multi-dimensional traits of SCMA. We use simulations to show that our proposed scheme provides a lower BER with a smaller computation time than conventional schemes.

Index Modulation for 5G: Striving to Do More with Less

Abstract: 5G wireless communications expect to bring both high spectrum efficiency and high energy efficiency. To meet the requirements, various new techniques have been proposed. Among these, the recently emerging index modulation has attracted significant interest. By judiciously activating a subset of certain communication building blocks, such as antenna, subcarrier, and time slot, index modulation is claimed to have the potential to meet the challenging 5G needs. In this article, we discuss index modulation and its general and specific representations, enhancements, and potential applications in various 5G scenarios. The objective is to reveal whether, and how, index modulation may strive for more performance gains with less medium resource occupation.

OTFS: A New Generation of Modulation Addressing the Challenges of 5G.

Abstract: In this paper, we introduce a new 2D modulation scheme referred to as OTFS (Orthogonal Time Frequency & Space) that multiplexes information QAM symbols over new class of carrier waveforms that correspond to localized pulses in a signal representation called the delay-Doppler representation. OTFS constitutes a far reaching generalization of conventional time and frequency modulations such as TDM and FDM and, from a broader perspective, it establishes a conceptual link between Radar and communication. The OTFS waveforms couple with the wireless channel in a way that directly captures the underlying physics, yielding a high-resolution delay-Doppler Radar image of the constituent reflectors. As a result, the time-frequency selective channel is converted into an invariant, separable and orthogonal interaction, where all received QAM symbols experience the same localized impairment and all the delay-Doppler diversity branches are coherently combined. The high resolution delay-Doppler separation of the reflectors enables OTFS to approach channel capacity with optimal performance-complexity tradeoff through linear scaling of spectral efficiency with the MIMO order and robustness to Doppler and multipath channel conditions. OTFS is an enabler for realizing the full promise of MUMIMO gains even in challenging 5G deployment settings where adaptation is unrealistic.

Non-Orthogonal Multiple Access for Unmanned Aerial Vehicle Assisted Communication

Abstract: The future wireless networks promise to provide ubiquitous connectivity to a multitude of devices with diversified traffic patterns wherever and whenever needed. For the sake of boosting resilience against faults, natural disasters, and unexpected traffic, the unmanned aerial vehicle (UAV)-assisted wireless communication systems can provide a unique opportunity to cater for such demands in a timely fashion without relying on the overly engineered cellular network. However, for UAV-assisted communication, issues of capacity, coverage, and energy efficiency are considered of paramount importance. The case of non-orthogonal multiple access (NOMA) is investigated for aerial base station (BS). NOMA’s viability is established by formulating the sum-rate problem constituting a function of power allocation and UAV altitude. The optimization problem is constrained to meet individual user-rates arisen by orthogonal multiple access (OMA) bringing it at par with NOMA. The relationship between energy efficiency and altitude of a UAV inspires the solution to the aforementioned problem considering two cases, namely, altitude fixed NOMA and altitude optimized NOMA. The latter allows exploiting the extra degrees of freedom of UAV-BS mobility to enhance the spectral efficiency and the energy efficiency. Hence, it saves joules in the operational cost of the UAV. Finally, a constrained coverage expansion methodology, facilitated by NOMA user rate gain is also proposed. Results are presented for various environment settings to conclude NOMA manifesting better performance in terms of sum-rate, coverage, and energy efficiency.

Hybrid Precoder and Combiner Design With Low-Resolution Phase Shifters in mmWave MIMO Systems

Abstract: Millimeter-wave (mmWave) communications have been considered as a key technology for next-generation cellular systems and Wi-Fi networks because of its advances in providing orders-of-magnitude wider bandwidth than current wireless networks. Economical and energy-efficient analog/digital hybrid precoding and combining transceivers have been often proposed for mmWave massive multiple-input multiple-output (MIMO) systems to overcome the severe propagation loss of mmWave channels. One major shortcoming of existing solutions lies in the assumption of infinite or high-resolution phase shifters (PSs) to realize the analog beamformers. However, low-resolution PSs are typically adopted in practice to reduce the hardware cost and power consumption. Motivated by this fact, in this paper, we investigate the practical design of hybrid precoders and combiners with low-resolution PSs in mmWave MIMO systems. In particular, we propose an iterative algorithm which successively designs the low-resolution analog precoder and combiner pair, aiming at conditionally maximizing the spectral efficiency. Then, the digital precoder and combiner are computed based on the obtained effective baseband channel to further enhance the spectral efficiency. In an effort to achieve an even more hardware-efficient large antenna array, we also investigate the design of hybrid beamformers with one-bit resolution (binary) PSs, and present a novel binary analog precoder and combiner optimization algorithm. After analyzing the computational complexity, the proposed low-resolution hybrid beamforming design is further extended to multiuser MIMO communication systems. Simulation results demonstrate the performance advantages of the proposed algorithms compared to existing low-resolution hybrid beamforming designs, particularly for the one-bit resolution PSs scenario.

Non-Orthogonal Multiple Access for Cooperative Communications: Challenges, Opportunities, and Trends

Abstract: NOMA is a promising radio access technique for next-generation wireless networks. In this article, we investigate the NOMA-based cooperative relay network. We begin with an introduction of the existing relay-assisted NOMA systems by classifying them into three categories: uplink, downlink, and composite architectures. Then we discuss their principles and key features, and provide a comprehensive comparison from the perspective of spectral efficiency, energy efficiency, and total transmit power. A novel strategy called hybrid power allocation is further discussed for the composite architecture, which can reduce the computational complexity and signaling overhead at the expense of marginal sum rate degradation. Finally, major challenges, opportunities, and future research trends for the design of NOMA-based cooperative relay systems with other techniques are also highlighted to provide insights for researchers in this field.

Hybrid Precoding-Based Millimeter-Wave Massive MIMO-NOMA with Simultaneous Wireless Information and Power Transfer

Abstract: Non-orthogonal multiple access (NOMA) has been recently considered in millimeter-wave (mmWave) massive MIMO systems to further enhance the spectrum efficiency. In addition, simultaneous wireless information and power transfer (SWIPT) is a promising solution to maximize the energy efficiency. In this paper, for the first time, we investigate the integration of SWIPT in mmWave massive MIMO-NOMA systems. As mmWave massive MIMO will likely use hybrid precoding (HP) to significantly reduce the number of required radio-frequency (RF) chains without an obvious performance loss, where the fully digital precoder is decomposed into a high-dimensional analog precoder and a low-dimensional digital precoder, we propose to apply SWIPT in HP-based MIMO-NOMA systems, where each user can extract both information and energy from the received RF signals by using a power splitting receiver. Specifically, the cluster-head selection (CHS) algorithm is proposed to select one user for each beam at first, and then the analog precoding is designed according to the selected cluster heads for all beams. After that, user grouping is performed based on the correlation of users' equivalent channels. Then, the digital precoding is designed by selecting users with the strongest equivalent channel gain in each beam. Finally, the achievable sum rate is maximized by jointly optimizing power allocation for mmWave massive MIMO-NOMA and power splitting factors for SWIPT, and an iterative optimization algorithm is developed to solve the non-convex problem. Simulation results show that the proposed HP-based MIMO-NOMA with SWIPT can achieve higher spectrum and energy efficiency compared with HP-based MIMO-OMA with SWIPT.

Hybridly Connected Structure for Hybrid Beamforming in mmWave Massive MIMO Systems

Abstract: In this paper, we propose a hybridly connected structure for hybrid beamforming in millimeter-wave (mmWave) massive MIMO systems, where the antenna arrays at the transmitter and receiver consist of multiple sub-arrays, each of which connects to multiple radio frequency (RF) chains, and each RF chain connects to all the antennas corresponding to the sub-array. In this structure, through successive interference cancelation, we decompose the precoding matrix optimization problem into multiple precoding sub-matrix optimization problems. Then, near-optimal hybrid digital and analog precoders are designed through factorizing the precoding sub-matrix for each sub-array. Furthermore, we compare the performance of the proposed hybridly connected structure with the existing fully and partially connected structures in terms of spectral efficiency, the required number of phase shifters, and energy efficiency. Finally, simulation results are presented to demonstrate that the spectral efficiency of the hybridly connected structure is better than that of the partially connected structure and that its spectral efficiency can approach that of the fully connected structure with the increase in the number of RF chains. Moreover, the proposed algorithm for the hybridly connected structure is capable of achieving higher energy efficiency than existing algorithms for the fully and partially connected structures.

Short-Packet Downlink Transmission With Non-Orthogonal Multiple Access

Abstract: This paper introduces downlink non-orthogonal multiple access (NOMA) into short-packet communications. NOMA has great potential to improve fairness and spectral efficiency with respect to orthogonal multiple access (OMA) for low-latency downlink transmission, thus making it attractive for the emerging Internet of Things. We consider a two-user downlink NOMA system with finite blocklength constraints, in which the transmission rates and power allocation are optimized. To this end, we investigate the trade-off among the transmission rate, decoding error probability, and the transmission latency measured in blocklength. Then, a 1-D search algorithm is proposed to resolve the challenges mainly due to the achievable rate affected by the finite blocklength and the unguaranteed successive interference cancellation. We also analyze the performance of OMA as a benchmark to fully demonstrate the benefit of NOMA. Our simulation results show that NOMA significantly outperforms OMA in terms of achieving a higher effective throughput subject to the same finite blocklength constraint, or incurring a lower latency to achieve the same effective throughput target. Interestingly, we further find that with the finite blocklength, the advantage of NOMA relative to OMA is more prominent when the effective throughput targets at the two users become more comparable.

Hybrid Time-Switching and Power Splitting SWIPT for Full-Duplex Massive MIMO Systems: A Beam-Domain Approach

Abstract: In this paper, we consider the hybrid time switching (TS) and power splitting (PS) simultaneous wireless information and power transfer (SWIPT) protocol design in a full-duplex (FD) massive MIMO system. In this system, an FD base station (BS) serves a set of half-duplex (HD) users and a set of fixed HD sensors. The whole protocol can be divided into two phases based on the idea of TS. The first phase is Training Phase , which is designed for users uplink training and sensors energy harvesting as well as downlink training. Specifically, users transmit uplink pilots for beam-domain (BD) uplink channel estimation at the BS, and the BS transmits energy signals to sensors. Based on the idea of PS, sensors utilize the received energy signals for energy harvesting and BD downlink channel estimation. In the second phase, that is Information Transmission Phase , the BS intelligently schedules users and sensors based on the BD distributions of channels to mitigate self-interference and improve transmission spectral efficiency (SE). Then, the BS forms transmit beamformers for transmitting information to users and receive beamformers for receiving signals transmitted by sensors. By optimizing transmit powers at the BS during the two phases and the TS ratio, the system achievable sum-rate is maximized. Simulation results show the superiority of the proposed protocol on SE compared with conventional massive MIMO SWIPT protocol.

Fully Non-Orthogonal Communication for Massive Access

Abstract: To achieve spectral-efficient massive access in future wireless networks, this paper proposes a comprehensive fully non-orthogonal communication framework. First, we design a fully non-orthogonal communication scheme which consists of non-orthogonal channel estimation and non-orthogonal multiple access. Then, we analyze the performance of the proposed fully non-orthogonal communication, and derive a tight lower bound on the spectral efficiency in terms of key system parameters and channel conditions. Meanwhile, several novel insights are provided on spectral efficiency via asymptotic analysis in three important cases, i.e., a large number of base station (BS) antennas, a high BS transmit power, and perfect channel state information (CSI) at the BS. Finally, we optimize the performance of the proposed fully non-orthogonal communication and present two simple but efficient optimization algorithms for maximizing the weighted sum of spectral efficiency. Extensive simulation results validate the effectiveness of the proposed schemes.

Resource Allocation for Multi-Channel Underlay Cognitive Radio Network Based on Deep Neural Network

Abstract: In this letter, a resource allocation strategy based on a deep neural network (DNN) is proposed for multi-channel cognitive radio networks, where the secondary user (SU) opportunistically utilizes channels without causing excessive interference to the primary user (PU). In the proposed scheme, the allocation of transmit power in each channel for SUs is found by utilizing the newly proposed DNN model, which separately determines the overall transmit power of individual SUs and the proportion of transmit power allocated to each channel. Both the spectral efficiency (SE) of the SU and the amount of interference caused to the PU are considered in the training of the DNN model, such that the interference caused to the PUs can be properly regulated while the SE of the SU is improved. Through simulations, we show that our scheme enables a high SE of the SU to be achieved while the interference caused to the PU can be maintained at less than the threshold.

Improving the Coverage and Spectral Efficiency of Millimeter-Wave Cellular Networks Using Device-to-Device Relays

Abstract: The susceptibility of millimeter waveform propagation to blockages limits the coverage of millimeter-wave (mmWave) signals. To overcome blockages, we propose to leverage two-hop device-to-device (D2D) relaying. Using stochastic geometry, we derive expressions for the downlink coverage probability of relay-assisted mmWave cellular networks when the D2D links are implemented in either uplink mmWave or uplink microwave bands. We further investigate the spectral efficiency (SE) improvement in the cellular downlink, and the effect of D2D transmissions on the cellular uplink. For mmWave links, we derive the coverage probability using dominant interferer analysis while accounting for both blockages and beamforming gains. For microwave D2D links, we derive the coverage probability considering both line-of-sight and non-line-of-sight (NLOS) propagation. Numerical results show that downlink coverage and SE can be improved using two-hop D2D relaying. Specifically, microwave D2D relays achieve better coverage because D2D connections can be established under NLOS conditions. However, mmWave D2D relays achieve better coverage when the density of interferers is large because blockages eliminate interference from NLOS interferers. The SE on the downlink depends on the relay mode selection strategy, and mmWave D2D relays use a significantly smaller fraction of uplink resources than microwave D2D relays.

Capacity Scaling for D2D Aided Cooperative Relaying Systems Using NOMA

Abstract: This letter proposes a device-to-device (D2D) aided cooperative relaying system (CRS) using non-orthogonal multiple access (NOMA) to enhance the spectral efficiency. In addition, a power allocation strategy is proposed to achieve the maximum capacity scaling according to signal-to-noise ratio (SNR). The proposed D2D aided CRS using NOMA with the power allocation is shown to improve the achievable rate greatly compared to conventional CRSs with and without NOMA. In particular, it is proved that the sum-capacity scaling is log SNR for the proposed one, whereas (2/3) log SNR for the conventional ones.

Energy Efficiency of Rate-Splitting Multiple Access, and Performance Benefits over SDMA and NOMA

Abstract: Rate-Splitting Multiple Access (RSMA) is a general and powerful multiple access framework for downlink multiantenna systems, and contains Space-Division Multiple Access (SDMA) and Non-Orthogonal Multiple Access (NOMA) as special cases. RSMA relies on linearly precoded rate-splitting with Successive Interference Cancellation (SIC) to decode part of the interference and treat the remaining part of the interference as noise. Recently, RSMA has been shown to outperform both SDMA and NOMA rate-wise in a wide range of network loads (underloaded and overloaded regimes) and user deployments (with a diversity of channel directions, channel strengths and qualities of channel state information at the transmitter). Moreover, RSMA was shown to provide spectral efficiency and QoS enhancements over NOMA at a lower computational complexity for the transmit scheduler and the receivers. In this paper, we build upon those results and investigate the energy efficiency of RSMA compared to SDMA and NOMA. Considering a multiple-input single-output broadcast channel, we show that RSMA is more energy-efficient than SDMA and NOMA in a wide range of user deployments (with a diversity of channel directions and channel strengths). We conclude that RSMA is more spectrally and energy-efficient than SDMA and NOMA.

Generalized Multiple-Mode OFDM With Index Modulation

Abstract: Multiple-mode orthogonal frequency division multiplexing with index modulation (MM-OFDM-IM), which transmits an OFDM signal with information bits embedded onto multiple distinguishable signal constellations of the same cardinality and their permutations, is a recently proposed IM technique in the frequency domain. It is capable of achieving higher spectral efficiency and better error performance than classical OFDM and existing frequency-domain IM schemes. In this paper, we propose the scheme of generalized (G-) MM-OFDM-IM, which allows a different subcarrier to utilize a signal constellation of a different size while conveying the same number of IM bits. Considering phase shift keying constellations, we present design guidelines for GMM-OFDM-IM to achieve an optimal error performance in the asymptotically high signal-to-noise ratio region. A computationally efficient and near-optimal detector based on the idea of sequential decoding is also tailored to GMM-OFDM-IM, which avoids the detection of an illegitimate constellation permutation. Monte Carlo simulations are conducted to validate the inherent properties and advantages of GMM-OFDM-IM.

DSP-free `coherent-lite' transceiver for next generation single wavelength optical intra-datacenter interconnects

Abstract: We propose a DSP-free coherent-lite system that requires neither high-speed DSP nor high-resolution signal converters for deployment inside datacenters over single mode fiber links with reaches of 10 km and less. The removal of converters and DSP, in which some subsystems are fundamental for successful coherent detection, is enabled by either replacing DSP subsystems with optics having equivalent functions or by re-engineering the system. We validate in a proof-of-concept experiment the proposed DSP-free system using 50 Gbaud DP-16QAM delivering 400 Gb/s over 10 km of single mode fiber (SMF) below the KP4 forward error correction (FEC) threshold of 2.2 × 10-4. In addition, we perform a detailed experimental parametric study of the coherent-lite system in which various system parameters are swept such as baud rate, reach, laser power and laser linewidth. Our results verify that the coherent-lite system can be realized using low-cost DFB lasers with linewidths of a few hundred kHz. Moreover, we compare the performance of the coherent-lite system with that of a conventional coherent transceiver leveraging the full DSP stack. Then, we evaluate the power consumption savings achieved by the coherent-lite scheme relative to a classic DSP-based coherent system. Assuming a CMOS node ranging from 28 to 7 nm for DSP implementation, our estimate shows that the coherent-lite scheme can save 95 to 78% of the power consumed by the following subsystems: analog-to-digital converters, chromatic dispersion compensation, 2 × 2 MIMO polarization demultiplexing and carrier recovery. Finally, we compare the power consumption of the coherent-lite scheme with more standard 400G IM-DD systems utilizing either eight or four parallel WDM lanes (8 × 50G and 4 × 100G). The coherent-lite system is found to have similar module power consumption requirements as a corresponding 4 × 100G IM-DD system while bringing the benefits of coherent detection including improved sensitivity and higher spectral efficiency leading to fewer light sources per transceiver module. To the best of our knowledge, this work represents the first experimental demonstration of a DSP-free coherent-lite system for single channel 400G datacenter 10 km interconnects, a potential attractive solution due to its scalability to future 800G and 1.6T intra-datacenter optical interconnects.

Deep Reinforcement Learning Based Dynamic Channel Allocation Algorithm in Multibeam Satellite Systems

Abstract: Dynamic channel allocation (DCA) is the key technology to efficiently utilize the spectrum resources and decrease the co-channel interference for multibeam satellite systems. Most works allocate the channel on the basis of the beam traffic load or the user terminal distribution of the current moment. These greedy-like algorithms neglect the intrinsic temporal correlation among the sequential channel allocation decisions, resulting in the spectrum resources underutilization. To solve this problem, a novel deep reinforcement learning (DRL)-based DCA (DRL-DCA) algorithm is proposed. Specifically, the DCA optimization problem, which aims at minimizing the service blocking probability, is formulated in the multibeam satellite systems. Due to the temporal correlation property, the DCA optimization problem is modeled as the Markov decision process (MDP) which is the dominant analytical approach in DRL. In modeled MDP, the system state is reformulated into an image-like fashion, and then, convolutional neural network is used to extract useful features. Simulation results show that the DRL-DCA algorithm can decrease the blocking probability and improve the carried traffic and spectrum efficiency compared with other channel allocation algorithms.

A Hardware-Efficient Analog Network Structure for Hybrid Precoding in Millimeter Wave Systems

Abstract: Hybrid precoding has been recently proposed as a cost-effective transceiver solution for millimeter wave systems. While the number of radio frequency chains has been effectively reduced in existing works, a large number of high-precision phase shifters are still needed. Practical phase shifters are with coarsely quantized phases, and their number should be reduced to a minimum due to cost and power consideration. In this paper, we propose a novel hardware-efficient implementation for hybrid precoding, called the fixed phase shifter (FPS) implementation. It only requires a small number of phase shifters with quantized and fixed phases. To enhance the spectral efficiency, a switch network is put forward to provide dynamic connections from phase shifters to antennas, which is adaptive to the channel states. An effective alternating minimization algorithm is developed with closed-form solutions in each iteration to determine the hybrid precoder and the states of switches. Moreover, to further reduce the hardware complexity, a group-connected mapping strategy is proposed to reduce the number of switches. Simulation results show that the FPS fully-connected hybrid precoder achieves higher hardware efficiency with much fewer phase shifters than existing proposals. Furthermore, the group-connected mapping achieves a good balance between spectral efficiency and hardware complexity.