Spectral Efficiency Loss Research Articles

Spectral efficiency improvement in cooperative RIS aided OFDM-IM system with hybrid indexing

Increasing demand for wireless communication leads to significant challenges in achieving high spectral efficiency (SE) and energy efficiency (EE). Orthogonal Frequency Division Multiplexing with Index Modulation (OFDM-IM) is one of the considerations, although it has the inherent disadvantage of a trade-off between SE and EE. In this work, frequency-dependent control on reconfigurable intelligent surfaces (RIS) and indexing to activate or deactivate the elements of RIS have been proposed to improve the SE of OFDM-IM systems. The Upper bound pairwise error probability has been derived and confirmed by simulation. The proposed work enhances the SE and EE compared to the conventional OFDM-IM systems. For instance, SE loss of 0.5bpcu in an OFDM-IM system with quadrature phase shift keying (QPSK) compared to an OFDM system has been compensated by the proposed work by maintaining EE.

Enabling endogenous distributed acoustic sensing in a digital subcarrier coherent transmission system.

To monitor the health of the fiber network and its ambient environment in densely populated access/metro network areas, in this Letter, an endogenous distributed acoustic sensing (DAS) has been proposed and achieved in a coherent digital subcarrier multiplexing (DSCM) system. Rather than specially allocating a sensing probe in general integrated communication and sensing schemes, the fractional Fourier transformed (FrFT) training sequence (TS) designated for time/frequency synchronization in DSCM coherent communications has been repurposed for sensing. While achieving excellent synchronization performance of communication, the FrFT-based TS can also be concurrently utilized to perform distributed vibration sensing. Experimental results demonstrate that the FrFT-based timing/frequency synchronization sequence is repurposed to achieve a DAS sensitivity of 70 p ε/Hz at a spatial resolution of 5 m, along with 100-Gb/s 16 quadrature amplitude modulation (QAM) DSCM transmission, without a loss of spectral efficiency.

DL-PC algorithm for partially-connected hybrid precoding in massive MIMO systems

In hybrid precoding, a partially-connected (PC) architecture has aroused significant attention for its low hardware complexity. Unfortunately, the hybrid precoding with the PC architecture may suffer from a severe spectral efficiency loss. To overcome the loss, a deep learning-based hybrid precoding algorithm for the PC architecture is proposed in this paper. Firstly, the optimization problem of hybrid precoding is transformed into a neural network prediction problem. Furthermore, a convolutional neural network(CNN) is designed to predict the hybrid precoder, where the channel matrix is used as input. Especially, to meet the constraints of the hybrid precoder, two lambda layers are introduced into the CNN architecture. Specifically, a lambda1 layer is constructed to address the constant modulus constraint of the analog precoding matrix and the block diagonal constraint. Then, a lambda2 layer is constructed to optimize the digital precoding matrix and address the transmit power constraint. Finally, the vectorized hybrid precoding matrix is output by the well-trained network. Simulation results show that the proposed algorithm can enhance spectral efficiency and energy efficiency with lower computation time.

Channel Customization for Limited Feedback in RIS-Assisted FDD Systems

Reconfigurable intelligent surfaces (RISs) represent a pioneering technology to realize smart electromagnetic environments by reshaping the wireless channel. Jointly designing the transceiver and RIS relies on the channel state information (CSI), whose feedback has not been investigated in multi-RIS-assisted frequency division duplexing systems. In this study, the limited feedback of the RIS-assisted wireless channel is examined by capitalizing on the ability of the RIS in channel customization. By configuring the phase shifters of the surfaces using statistical CSI, we customize a sparse channel in rich-scattering environments, which significantly reduces the feedback overhead in designing the transceiver and RISs. Since the channel is customized in terms of singular value decomposition (SVD) with full-rank, the optimal SVD transceiver can be approached without a matrix decomposition and feeding back the complete channel parameters. The theoretical spectral efficiency (SE) loss of the proposed transceiver and RIS design is derived by considering the limited CSI quantization. To minimize the SE loss, a bit partitioning algorithm that splits the limited number of bits to quantize the CSI is developed. Extensive numerical results show that the channel customization-based transceiver with reduced CSI can achieve satisfactory performance compared with the optimal transceiver with full CSI. Given the limited number of feedback bits, the bit partitioning algorithm can minimize the SE loss by adaptively allocating bits to quantize the channel parameters.

Dynamic-Subarray With Fixed Phase Shifters for Energy-Efficient Terahertz Hybrid Beamforming Under Partial CSI

Terahertz (THz) communications are regarded as a pillar technology for the 6G systems, by offering multi-ten-GHz bandwidth. To overcome the huge propagation loss, THz ultra-massive MIMO systems with hybrid beamforming are proposed to offer high array gain. Notably, the adjustable phase shifters considered in most existing hybrid beamforming studies are power-hungry and difficult to realize in the THz band. Moreover, due to the ultra-massive antennas, full channel-state-information (CSI) is challenging to obtain. To address these practical concerns, in this paper, an energy-efficient dynamic-subarray with fixed phase shifters (DS-FPS) architecture is proposed for THz hybrid beamforming. To compensate for the spectral efficiency loss caused by the fixed phase of FPS, a switch network is inserted to enable dynamic connections. In addition, by considering the partial CSI, we propose a row-successive-decomposition (RSD) algorithm to design the hybrid beamforming matrices for DS-FPS. A row-by-row (RBR) algorithm is further proposed to reduce the computational complexity. Extensive simulation results show that, the proposed DS-FPS architecture with the RSD and RBR algorithms achieves much higher energy efficiency than the existing architectures. Moreover, the spectral efficiency of the DS-FPS architecture with the proposed algorithms is robust to the CSI error.

Mitigating Clipping Distortion in Multicarrier Transmissions Using Tensor-Train Deep Neural Networks

Multicarrier transmissions, such as orthogonal frequency/chirp division multiplexing (OF/CDM), offer high spectral efficiency and low complexity equalization in multipath fading channels at the cost of high peak-to-average power ratio (PAPR). High peak powers can occur randomly and may drive the power amplifier (PA) into saturation, resulting in non-linear distortion. In this work, we propose a novel tensor-train (TT) deep neural network (DNN) architecture combined with soft clipping to reduce the PAPR to a deterministic level and minimize in-band distortion, while also satisfying spectral mask constraints. The proposed solution requires modifications only at the transmitter and there is no loss of spectral efficiency. Employing the TT decomposition allows for significant reduction in parameters. Results show that the proposed solution allows for significant reduction in PAPR with minimal performance loss. Furthermore, an upper bound for the PAPR is also derived which allows for the prediction of the required input power back off (IBO) without extensive simulations and trial-and-error.

Towards a Fair Allocation and Effective Utilization of Resource Units in Multi-User WLANs-based OFDMA technology

To promote the MU (Multi-User) communications in High-Efficiency WLANs (Wireless Local Area Networks), the new IEEE 802.11ax standard introduced the concept of RU (Resource Unit) by means of the OFDMA (Orthogonal Frequency Division Multiple Access) transmission technique. Although the OFDMA MU communications enable multiple users to be served at the same time in both DL (Down-Link) and UL (Up-Link) directions, several challenges remain to be met in order to design a MAC (Medium Access Control) protocol that fairly allocates and effectively utilizes the RUs. The challenges addressed are: (1) define when and how using 802.11ax control frames, (2) establish a fair sending policy of UL needs, (3) adopt a strategy to select a channel structure, and (4) avoid loss in spectral efficiency and timeout BA (Block Acknowledgment). In this paper, we proposed the FAEU-RUs protocol (Fair Allocation and Effective Utilization of RUs) by meeting each of the challenges of OFMDA MU communications. The performance evaluation demonstrates that the FAEU-RUs protocol significantly enhances the overall performance of the network but also the individual performance of each type of traffic (DL and UL) and each category of station.

Location-aided uplink transmission for user-centric cell-free massive MIMO systems: a fairness priority perspective

In this paper, we investigate the uplink transmission for user-centric cell-free massive multiple-input multiple-output (MIMO) systems. The largest-large-scale-fading-based access point (AP) selection method is adopted to achieve a user-centric operation. Under this user-centric framework, we propose a novel inter-cluster interference-based (IC-IB) pilot assignment scheme to alleviate pilot contamination. Considering the local characteristics of channel estimates and statistics, we propose a location-aided distributed uplink combining scheme to balance the relationship among the spectral efficiency (SE), user equipment (UE) fairness and complexity, in which local partial minimum mean-squared error (LP-MMSE) combining is adopted for some APs, while maximum-ratio (MR) combining is adopted for the remaining APs. A corresponding AP selection scheme based on a novel proposed metric representing inter-user interference is proposed. We also propose a new fairness coefficient taking SE performance into account to indicate the UE fairness. Moreover, the performance of the proposed scheme is investigated under fractional power control and max–min fairness (MMF) power control. Simulation results demonstrate that the channel estimation accuracy of our proposed IC-IB pilot assignment scheme outperforms that of the conventional pilot assignment schemes. It is also shown that compared with the benchmark LP-MMSE combining, the proposed location-aided combining trades 13.45% average SE loss for 26.61% UE fairness improvement and 28.58% complexity reduction when gamma = 0.6. And by adjusting the threshold gamma, a good trade-off between the average SE, UE fairness and computational complexity can be provided by the proposed scheme. Furthermore, the proposed scheme with fractional power control can better demonstrate the advantages of trade-off performance than MMF power control and full power transmission.

A Family of Hybrid Precoding Schemes for Millimeter-Wave Massive MIMO Systems

For millimeter-wave (mmWave) massive multiple-input and multiple-output (MIMO) systems, hybrid precoding/combining is a promising way to reduce hardware cost and power consumption by decreasing the number of radio-frequency (RF) chains without causing a significant spectral-efficiency loss. Most of the existing hybrid precoding schemes involve iterative searching or alternating optimization, so their computational complexity is high and they do not take advantage of parallel computing to improve the real-time performance. In this article, considering the scenarios where the number of data streams equals to the number of RF chains, we propose a family of hybrid precoding schemes by leveraging the equivalent channel and singular value decomposition for a better tradeoff between spectral efficiency and computational complexity. Simulation results with different system settings show that our proposed schemes are superior to other existing schemes in terms of system spectral efficiency.

Joint User Grouping and Beam Selection for Beamspace mmWave Multi-User MIMO System

Lens antenna arrays based beamspace millimeter-wave multi-user massive MIMO (B-MIMO) can significantly improve energy efficiency without significant loss of spectral efficiency (SE), which is considered as a highly expected technology for future wireless communication networks. Motivated by the requirement of reducing SE loss by efficient user grouping (UG) and beam selection (BS), a joint user grouping and beam selection algorithm is studied. Specifically, a local search based BS algorithm is proposed by proving the convexity of the BS problem after relaxing the constraints. Moreover, a deep learning based UG algorithm is proposed by equivalently transforming the UG problem into a classification problem. The results of theoretical analysis and numerical simulation show that the proposed algorithms can be more closely with the performance of the exhaustive search algorithm and the complexity is lower than that of the traditional algorithms.

Impact of Finite-Resolution Precoding and Limited Feedback on Rates of IRS Based mmWave Networks

Intelligent reflecting surfaces (IRSs) can enhance the system performance of millimeter wave (mmWave) networks. In practice, phase shifts at the base station and the IRSs are digitally controlled and have discrete values. The channel state information (CSI) feedback also has a limited rate. This work analyzes the spectral efficiency performance of an IRS based mmWave network in which the beamsteering codebooks are used for the passive precoding and analog precoding, and the zero-forcing precoder is used for digital precoding. To capture the features of mmWave channels and reflect the impact of passive and analog precoding, a channel correlation based codebook is employed to quantize the effective channels. Upper-bounds are derived for the spectral efficiency losses due to finite-resolution beamsteering codebooks and limited CSI feedback. It is found that the spectral efficiency loss due to finite-resolution beamsteering codebooks does not depend on the transmit power in large signal-to-noise ratio regimes, while the spectral efficiency loss due to limited CSI feedback increases with the transmit power. Then, the asymptotic performance is analyzed when the numbers of transmit antenna elements and reflecting elements go to infinity. Simulations verify the derivations and findings.

Design and Development of Novel Hybrid Precoder for Millimeter-Wave MIMO System

Power consumption and hardware cost reduction with the use of hybrid beamforming in large-scale millimeter wave MIMO systems. The large dimensional analog precoding integrates with the hybrid beamforming based on the phase shifters including digital precoding with lower dimensionality. The reduction of Euclidean distance between the hybrid precoder and fully digital is the major problem to overcome the minimization of resultant spectral efficiency. The issue formulates as a fully digital precoder’s matrix factorization problem based on the analog RF precoder matrix and the digital baseband precoder matrix. An additional element-wise unit modulus constraint is imposed by the phase shifters on the analog RF precoder matrix. The traditional methods have a problem of performance loss in spectral efficiency. In the processing time and iteration, high complexities result in optimization algorithms. In this paper, a novel low complexity algorithm proposes which maximizes the spectral efficiency and reduces the computational processing time.

A Systems Approach for Solving Inter-Policy Gaps in Dynamic Spectrum Access-Based Wireless Rural Broadband Networks

In this paper, we articulate the challenge of multiple intersecting policies for the realization of rural broadband networks employing dynamic spectrum access (DSA). Broadband connectivity has been identified as a critical component of economic development, especially during the COVID-19 pandemic, and rural communities have been significantly (and negatively) affected by the lack of this important resource. Although technologies exist that can deliver broadband connectivity, such as 4G LTE and 5G cellular networks, the challenges associated with efficiently deploying this infrastructure within a rural environment are multi-dimensional in terms of the different dependent policy decisions that need to be considered. To resolve this issue, we describe how systems engineering tools can be used for representing these intersecting policies such that system configurations can be optimized for efficient infrastructure deployment and operations. One technology requiring increased attention is DSA, where licensed and emerging wireless services can coexist together via spectrum sharing. However, implementation of this technology is challenging, where highly efficient Radio Access Technology (RAT), available spectrum, and user requirements need to be precisely aligned. All these elements to be configured are typically described by independent policies. While DSA is more complicated than previously used spectrum allocation schemes, inter-policy gaps occur that ultimately decrease the network’s efficiency. Consequently, a systems engineering framework has the potential to obtain the optimal solutions although the systems and wireless communities conceptualize and scope problems differently, which can impede collaboration. We present the use case where 4G LTE RAT technology employing DSA applied to digital terrestrial television (DTT) frequency bands can yield spectral efficiency loss when the different policy dimensions are not sufficiently accounted for within the use case. Numerical experiments have shown that in an example rural scenario the availability of rural broadband can increase from 1% to 21% of locations if the inter-policy gaps are removed.

Design and Development of Novel Hybrid Precoder for Millimeter-Wave MIMO System

Power consumption and hardware cost reduction with the use of hybrid beamforming in large-scale millimeter wave MIMO systems. The large dimensional analog precoding integrates with the hybrid beamforming based on the phase shifters including digital precoding with lower dimensionality. The reduction of Euclidean distance between the hybrid precoder and fully digital is the major problem to overcome the minimization of resultant spectral efficiency. The issue formulates as a fully digital precoder’s matrix factorization problem based on the analog RF precoder matrix and the digital baseband precoder matrix. An additional element-wise unit modulus constraint is imposed by the phase shifters on the analog RF precoder matrix. The traditional methods have a problem of performance loss in spectral efficiency. In the processing time and iteration, high complexities result in optimization algorithms. In this paper, a novel low complexity algorithm proposes which maximizes the spectral efficiency and reduces the computational processing time.

On the optimal energy efficiency and spectral efficiency trade-off of CF massive MIMO SWIPT system

Energy efficiency is a key requirement for future network design, and user-centric (UC) cell-free (CF) massive multi-input multi-output (MIMO) networks can achieve over ten times the energy efficiency. Based on this, this paper studies a CF MIMO simultaneous wireless information and power transmission system and proposes a UC access point (AP) selection method and a trade-off performance optimization scheme for spectral efficiency and energy efficiency. In this system, users have both energy recovery and information transmission functions. According to the difference between the interference in the energy harvesting and information transmission process, a flexible AP selection scheme is designed. Blindly pursuing high spectral efficiency will result in waste of resources. This paper proposes an evaluation index that takes into account both energy efficiency and spectral efficiency, analyses the trade-off between energy efficiency and spectral efficiency, and jointly optimizes the AP selection scheme and the uplink (UL) and downlink (DL) time switching ratio to maximize the trade-off performance. Then, the non-convex problem is converted to a geometric planning problem to solve. The simulation results show that by implementing a suitable AP selection scheme and UL and DL time allocation, the information processing scheme on the AP side has a slight loss in spectral efficiency, but the energy efficiency is close to the performance of global processing on the central processing unit.

High Spectral Efficiency Coherent Superchannel Transmission With Soliton Microcombs

Spectral efficiency (SE) is one of the key metrics for optical communication networks. An important building block for its maximization are optical superchannels, channels that are composed of several subchannels with an aggregate bandwidth larger than the bandwidth of the detector electronics. Superchannels which are routed through the network as a single entity, together with flex-grid routing, allow to more efficiently utilize available bandwidth and eliminate the guard-bands between channels, thus increasing spectral efficiency. In contrast to traditional wavelength division multiplexing (WDM) channels, subchannel spacing and thus superchannel SE is governed by the linewidth and stability of the frequency spacing of the transmitter lasers. Integrated optical frequency combs, particulary the parametrically generated so-called microcombs, which provide optical lines on a fixed frequency grid are a promising solution for low power superchannel laser sources that allow to minimize the SE loss from suboptimal channel spacing. However, it is extremely challenging to realize microcombs with sufficient line power, coherence and line spacing that is compatible with electronic bandwidths. Because the line-spacing generated by most devices is above 40 GHz, demonstrations often rely on additional electro-optic frequency shifter or divider stages to avoid digital-to-analog-converter (DAC) performance degradation when operating at high symbol rates. Here we demonstrate a 52-line superchannel from a single 22 GHz line spacing soliton microcomb. We demonstrate 12 Tb/s throughput with >10 bits/s/Hz SE efficiency after 80 km transmission and 8 Tb/s throughput (SE >6 bits/s/Hz) after 2100 km, proving the feasibility and benefits of generating high signal quality, broadband waveforms directly from the output of a micro-scale device with a symbol rate close to the comb repetition rate.

Energy-Efficient Beamforming for Beamspace HAP-NOMA Systems

In this letter, we study an energy-efficient algorithm for beamspace high altitude platform with non-orthogonal multiple access (HAP-NOMA) systems over Rician fading channels. We first derive the non-line-of-sight (NLOS) theorem of beamspace HAP channel in large scale array regime according to the asymptotic property of the Toeplitz matrix. Then, we propose the beamspace HAP-NOMA scheme based on the derived NLOS theorem, which can be partitioned into two stages, i.e. user grouping scheme and power optimization scheme. The statistical channel state information (CSI) is only required in the proposed algorithm, which avoids acquiring instantaneous CSI. NOMA can serve users in each beam simultaneously to compensate for the loss of spectral efficiency due to the beamspace HAP. The digital precoder can be obtained by zero forcing (ZF) based on the equivalent channel. Numerical results show the performance enhancement of the proposed beamspace HAP-NOMA algorithm.

Low-Complexity Blind PAPR Reduction for OFDM Systems With Rotated Constellations

The high Peak-to-Average Power Ratio (PAPR) of Orthogonal Frequency Division Multiplexing (OFDM) signals leads to a serious system performance degradation. To work around this issue, several algorithms have been proposed in the literature to reduce the PAPR, but, they often suffer from multiple limitations; in particular, the main issue with interleaving techniques is the spectral efficiency loss, as the transmission of a Side Information (SI) is generally required. In contrast to previous works, this article proposes a blind interleaving technique for OFDM systems with signal space diversity. Indeed, with Rotated and Cyclically Q-Delayed (RCQD) constellations, the In-phase (I) and Quadrature (Q) components of constellations symbols are correlated, which allows the receiver to estimate the interleaver index without any SI. Moreover, to lower down the complexity burden at the receiver side, we first design a blind decoder based on the Minimum Mean Square Error (MMSE) criterion and we then propose a low complexity decoder for the Uniformly Projected RCQD (UP-RCQD) QAM, as this constellation has several interesting structural properties and achieves near optimum BER performance. Simulation results show that our proposal leads to a large PAPR reduction and to a near optimum BER performance that outperforms, over various channels, the solution currently used in DVB-T2. They also underline the good performance of the blind decoding performed with up to 98% of complexity reduction compared to the max-log Maximum Likelihood (ML) estimation.

Low-Complexity Hybrid Precoding Algorithm Based on Log-Det Expansion for GenSM-Aided MmWave MIMO System

Generalized spatial modulation (GenSM) aided millimeter wave (mmWave) multiple-input multiple-output (MIMO) system has been recently considered as a new efficient technique due to the combination of numerous antennas and reduced number of radio frequency (RF) chains. However, the present hybrid precoding schemes for GenSM-aided system are still troubled by high computational complexity and performance loss in spectral efficiency (SE). In this paper we propose low-complexity hybrid precoding schemes based on Martin's expansion for logarithmic determinant (log-det) form in analytical SE lower bound. Digital and analog precoders are herein optimized separately, which means complicated alternating minimization iteration is omitted. Besides, we can adjust algorithmic complexity adaptively corresponding to different demand levels for users. Finally the numerical simulations show that the proposed methods outperform other GenSM-aided mmWave MIMO schemes and can achieve a better tradeoff between complexity and SE.

Performance-Enhanced DMT System With Joint Precoding and Probabilistic Constellation Shaping

The promising solution for short-reach optical communication, discrete multitone (DMT) system suffer from high peak-to-average power ratio (PAPR). It is easy for the DMT signal to enter the nonlinear region of the components in the systems, which distorts the signal and limits the modulation efficiency. It is well-known that the precoding technique can suppress the PAPR of DMT without loss of spectral efficiency. We found that, in the I/Q plane, the nonlinear distortion clusters in the constellation points with higher power due to the joint precoding and inverse fast Fourier transform. The principle of this phenomenon has been studied. To cope with the specially distributed nonlinear distortions induced by precoding, we adopted the probabilistic constellation shaping (PCS) technique to reduce the probability of constellation points with high power, resulting in the overall performance improvement. Joint precoding and PCS significantly improve the resistance to nonlinear distortions for DMT systems. Simulations and experiments of 16-QAM and 64-QAM DMT transmission systems were conducted to evaluate the performance. The experimental results show that at the NGMI threshold of 0.92, up to 4 dB enhancement of the receiver sensitivity has been achieved by the proposed scheme when 4-GBd 64-QAM signals are transmitted.