Spectral Efficiency In Wireless Communications Research Articles

Two-Stage LMMSE/DNN Receiver for High-Order Modulation

High-order modulation has been seen as a promising technology to increase the spectral efficiency of wireless communications. Unfortunately, higher-order signals are susceptible to power amplifier (PA) nonlinearities and multi-path effects of the channel, leading to nonlinear distortion and severe inter-symbol interference. To guarantee the reliable detection of high-order signals, a two-stage receiver consisting of linear minimize mean squared error (LMMSE) equalizer and deep neural network (DNN) demodulator, namely TSLD receiver, is proposed, where LMMSE equalizer and DNN are deployed to eliminate inter-symbol interference and handle the amplifier nonlinearity, respectively. To facilitate the implementation of our proposed receiver, the specific pilot structure is designed, where low-order modulations are used for LMMSE equalizer and high-order modulations are used for DNN training. Simulation results show that our proposed TSLD receiver for high-order demodulation could recover the transmitted symbols effectively, even under serious multi-path and nonlinerity scenarios.

User Association for Reconfigurable Intelligent Surfaces Aided Cell-Free Networks

Cell-free (CF) network can efficiently suppress inter-cell interference and enable multiple base stations (BSs) to serve users cooperatively without being affected by cell boundaries. However, to further increase the network capacity, a large number of BSs need to be deployed, resulting in high cost and power consumption. To tackle this problem, reconfigurable intelligent surface (RIS) has emerged as a cost-effective technology to enhance energy and spectral efficiency of wireless communications. In this paper, we consider an RIS-aided CF network by exploiting their complementary advantages where each user assisted by a dedicated RIS can associate with multiple BSs. We first characterize each user's average signal-to-interference-plus-noise ratio (SINR) in the RIS-CF network. Then, we formulate an SINR balancing problem to maximize the minimum SINR among all users by designing the BS-user associations. Despite of the non-convexity and combinatorial feature of this problem, a two-step fractional linearization algorithm is developed to solve it optimally. Specifically, we transform a nested mixed-integer linear fractional program (MILFP) into a solvable mixed-integer linear programming (MILP) problem through the generalized fractional programming and reformulation-linearization method. Finally, we provide numerical results to validate the effectiveness of our proposed algorithm compared to other benchmark schemes.

Reconfigurable-Intelligent-Surface-Assisted B5G/6G Wireless Communications: Challenges, Solution, and Future Opportunities

Power consumption and hardware cost are two of the main challenges for realizing beyond fifth generation (B5G) and sixth generation (6G) wireless communications. Recently, the emerging reconfigurable intelligent surface (RIS) has been recognized as a promising tool for enhancing the propagation environment and improving the spectral efficiency of wireless communications by controlling low-cost passive reflecting elements. However, current cellular communications were designed on the basis of conventional communication theories, significantly restricting the development of RIS-assisted B5G/6G technologies and leading to severe limitations. In this article, we discuss RIS-assisted channel estimation issues involved in B5G/6G communications including channel state information (CSI) acquisition, imperfect cascade CSI for beamforming design, and co-channel interference coordination, and develop a few possible solutions or visionary technologies to promote the development of B5G/6G. Finally, potential research opportunities are discussed.

A Covariance Matrix-Based Cooperative Spectrum Sensing Algorithm in Electric Wireless Private Network

Cognitive radios can significantly improve the spectral efficiency of wireless communications. Spectrum sensing is a key function of cognitive radios to prevent the harmful interference with licensed users. This paper considers the cooperative spectrum sensing in 230 MHz electric wireless private networks. First, the statistical distribution of the sample covariance matrix of the received signals is investigated. Then, taking the ratio of the sum of absolute values of the off-diagonal elements of the sample covariance matrix to that of the diagonal elements as the decision metric, an improved covariance absolute value (ICAV) cooperative sensing algorithm is proposed. After that, a performance analysis concerning the probabilities of false alarm and detection is carried out. Theoretical analysis and simulation results show that the ICAV algorithm possesses an accurate decision threshold and is robust to the noise uncertainty.

MIMO Full-Duplex Networks With Limited Knowledge of the Relay State

Full-duplex (FD)-enabled relay networks represent a relevant solution to two critical needs of next-generation networks, namely, radio coverage extension and high spectral efficiency of wireless communications. Under practical conditions, however, the FD mode may not be the best operational setting for the relay; rather, operating in half-duplex may be more convenient when harsh channel conditions add up to self-interference. One of the fundamental challenges in the design of FD relay networks is thus how to determine the relay operational mode and the value of transmit power at both the relay and the data source, so that the achievable data rate is maximized as time varies. We address this problem in a two-hop, MIMO network, accounting for practical operational conditions in which the source is unaware of the symbols that the relay is transmitting. In light of the problem complexity, we also derive a lower-bound to the maximum achievable rate, which proves to be tight, especially for low-medium SNR values. We then tackle massive MIMO networks, and exploit our asymptotic analysis in the number of antennas to derive a low-complexity, yet highly efficient, operational mode and transmit power allocation scheme for a finite-size scenario.

Network-Assisted Full-Duplex Distributed Massive MIMO Systems With Beamforming Training Based CSI Estimation

Network-assisted full-duplex (NAFD) distributed massive multiple-input multiple-output (MIMO) systems enable simultaneous uplink and downlink communications by dynamically allocating the numbers of uplink and downlink remote antenna units (RAUs), which potentially improve the spectral efficiency in wireless communications. In such systems, channel state information (CSI) plays a critical role in uplink reception and downlink transmission, as well as the cross link interference cancelation caused by downlink RAUs to uplink RAUs. Moreover, downlink terminals need to estimate CSI to reliably decode the received signals due to the reduced channel hardening effect. However, high training overhead makes it generally impossible to directly estimate CSI. This paper proposes to estimate effective CSI (inner products of beamforming and channel vectors) instead based on beamforming training scheme. Under this scheme, we derive closed-form expressions for uplink and downlink achievable rates with different receivers and beamforming. Given these expressions, we propose an efficient power allocation scheme which is only dependent on slowly varying large-scale fading from the perspective of multi-objective optimization. Numerical results verify the accuracy of the derived closed-form expressions and effectiveness of beamforming training based CSI estimation. Moreover, trade-off regions between the considered optimization objectives under various system parameters offer numerous flexibilities for system optimization.

Joint Power Allocation and Relay Beam-forming in Orbital Angular Momentum Amplify-and-Forward Relay Networks

Orbital Angular Momentum (OAM) is a promising technology that can effectively improve the spectral efficiency of wireless communications. However, it is important for OAM to keep the antenna alignment of transmitter and receiver. The alignment requirements greatly increases the difficulty of the practical application of OAM, especially when there is a barrier or a large turning angle between uniform circular arrays (UCAs). In this letter, we studied the application of amplify-and-forward (AF) relay in multiple-input multiple-output (MIMO) OAM system to solve the problem caused by the existence of UCAs corners. In this work, our goal is to achieve the maximum achievable rate by jointly optimizing the source power allocation matrix and the relay pre-coding matrix, constrained by the power of the source and the relay. The problem is expressed as a convex problem by mathematical operations, and then based on the Lagrange dual method, we solved it by proposing an iterative algorithm. Numerical simulations show the superiority of the algorithm.

Energy-Efficient Resource Allocation in NOMA Heterogeneous Networks

Non-orthogonal multiple access (NOMA) has attracted much recent attention owing to its capability for improving the system spectral efficiency in wireless communications. Deploying NOMA in heterogeneous network can satisfy users' explosive data traffic requirements, and NOMA will likely play an important role in the fifth-generation (5G) mobile communication networks. However, NOMA brings new technical challenges on resource allocation due to the mutual cross-tier interference in heterogeneous networks. In this article, to study the tradeoff between data rate performance and energy consumption in NOMA, we examine the problem of energy-efficient user scheduling and power optimization in 5G NOMA heterogeneous networks. The energy-efficient user scheduling and power allocation schemes are introduced for the downlink 5G NOMA heterogeneous network for perfect and imperfect channel state information (CSI) respectively. Simulation results show that the resource allocation schemes can significantly increase the energy efficiency of 5G NOMA heterogeneous network for both cases of perfect CSI and imperfect CSI.

A factor graph-based iterative detection of faster-than-Nyquist signaling in the presence of phase noise and carrier frequency offset

With the increasing demand for higher spectral efficiency in wireless communications, faster-than-Nyquist (FTN) signaling has been rediscovered to increase transmission rate without expanding signaling bandwidth. Most existing studies focus on low-complexity FTN receiver design by assuming perfect synchronization. In practice, however, phase noise (PHN) and carrier frequency offset (CFO) may degrade the performance of FTN detector significantly. In this paper, we develop iterative FTN detector in the presence of PHN and CFO in a factor graph framework. Wiener process is employed to model the time evolution of nonstationary channel phase. The colored noise imposed by sampling of FTN signaling is approximated by autoregressive model. Based on the factor graph constructed, messages are derived on the two subgraphs, i.e., PHN and CFO estimation subgraph and the FTN symbol detection subgraph. We propose two methods to update the messages between subgraphs, namely, Gaussian approximation via Kullback–Leibler divergence (KLD) minimization and the combined sum-product and variational message passing (SP-VMP), both of which enable low-complexity parametric message passing. The proposed SP-VMP algorithm can provide closed-form expressions for parameters updating. Moreover, conjugate gradient (CG) method is adopted to solve the maximum a posteriori probability (MAP) estimation of CFO with fast convergence speed. Simulation results show the superior performance of the proposed algorithm compared with the existing methods and verify the advantage of FTN signaling compared with the Nyquist counterpart.

2 <formula formulatype="inline"><tex Notation="TeX">$\times$</tex></formula> 2 MIMO OFDM-RoF System Employing LMS-Based Equalizer With I/Q Imbalance Compensation at 60 GHz

Multiple-input–multiple-output (MIMO) technology is a promising method to increase spectral efficiency in wireless communications. In this paper, a 60-GHz orthogonal frequency-division multiplexing radio over fiber (OFDM-RoF) system employing 2 <formula formulatype="inline" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex Notation="TeX">$\times$</tex></formula> 2 MIMO wireless technology is demonstrated. With the proposed equalizer employing least mean squares (LMS) algorithm, MIMO channel mixing and I/Q-mismatch can be compensated simultaneously. 16-QAM and 32-QAM OFDM signal transmissions under forward error correction (FEC) threshold ( <formula formulatype="inline" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex Notation="TeX">$1\times 10^{-3}$</tex></formula> ) are demonstrated. A data rate of 76.3 Gb/s can be achieved with a bit-loading algorithm over 25-km fiber transmission and 3.5-m wireless transmission.

Cross-layer design in opportunistic spectrum access-based cognitive radio networks

Cognitive radio is considered as one of the most important enablers for achieving enhanced spectral efficiency in wireless communications. In this work, we present a cross-layer design for reliable data transmission over a cognitive radio network which combines adaptive modulation at the physical layer and hybrid automatic repeat request at the data link layer. The cognitive radio network follows the principles of opportunistic spectrum access that utilises an optimal power adaptation policy for channel allocation. The obtained numerical results denote that the considered approach achieves significant spectral efficiency improvement and therefore it could be deployed in wireless communication networks that encompass cognitive capabilities. Furthermore, we assess the introduced interference and we show that it can be kept within levels that do not jeopardise our design.

The Effect of a Selective Receiver on CDMA

The quest for higher spectral efficiency in wireless communications is creating a new impetus for selective and sensitive base-station receivers. One consequence of high selectivity is phase dispersion, which critically affects the operation of a phase-modulated communications system. If phase equalization is not used, increasing selectivity will eventually compromise the performance of a receiver. These performance limitations are examined in a coherent and noncoherent direct-sequence spread-spectrum system

A receiver-based variable-size-burst equalization strategy for spectrally efficient wireless communications

Strategies for improving spectral efficiency in wireless communications, while maintaining quality of service, are proposed. The idea is to make the communication system adapt to the encountered environment. To this end, a time-varying channel model explicitly characterizing changing environments is developed. Under this model, methods for tracking channel stationarity are proposed based on analysis of variance and minimum description length. Tracking enables efficient construction of variable-size data bursts for improved equalization at the receiver. The performance is evaluated first in a training-based equalization framework, then extended to a semi-blind situation. In either case, the obtained results demonstrate feasibility of variable-size burst construction for improving spectral efficiency. The proposed methods are applicable to burst-by-burst or block-based equalization systems, without the requirement of feedback.

Adaptive MLSE Equalizer with Per-Survivor QR Decomposition for Trellis-Coded MIMO Transmission

A trellis-coded multiple-input multiple-output (MIMO) transmission technique, which exploits multiple-antenna elements at both transmitter and receiver sides and employs trellis-coded modulations (TCMs), has potential to significantly increase spectral efficiency in wireless communications. At the receiver, an adaptive equalizer based on maximum-likelihood sequence estimation (MLSE) deals with intersymbol interference (ISI) incurred in wideband transmissions and jointly decodes multiplexed TCM signals. Recently, a sphere-constrained maximum-likelihood detection, so-called sphere decoding, has drawn much attention for reducing the computational burden in MIMO transmission systems. This paper describes the super-trellis structured Viterbi algorithm applying per-survivor sphere decoding, and evaluates the effect of the complexity reduction in branch metric computations.

Multiple Co-Polar Co-Channel Point-to-Point Radio Transmission

Abstract The use of multiple antennas both at transmitter and receiver improves the spectral efficiency in wireless communications. We propose a multiple antenna system, which is tailored for the scenario of line-of-sight fixed radio. The interference is removed by means of an equalizer operating at the receiver side without any onerous pre-processing at the transmit side. A suitable choice of the spatial separation among the individual transmit/receive antennas guarantees not only the possibility to re-use the frequency band but also an increase in the power efficiency respect to a single-input-single-output system.