Spectral efficiency for IRS-assisted uplink mmWave massive MISO systems with low-resolution ADCs

In this paper, we investigate the uplink achievable spectral efficiency (SE) for an intelligent reflecting surface (IRS)-assisted millimeter wave (mmWave) multiple-input single-output (MISO) system, where all antennas at the BS are equipped with cheaper low-resolution analog-to-digital converters (ADCs) and an IRS adjusts its reflecting phase shifts to facilitate information transfer. To maximize the uplink achievable SE, we design the phase shift of each reflecting element and obtained the optimal phase shift matrix in the terms of the statistical channel state information (CSI). An theoretical expression of the uplink achievable SE of massive MISO system is obtained with the zero forcing (ZF) detector is derived. Based on this derived theoretical result, the behaviors of the achievable SE with respect to several physical parameters are revealed that includes the number of antennas, the transmit power, the number of reflecting elements, and the quantization bits of the low-resolution ADCs. Finally, we provide the numerical results by Monte Carlo simulation to verify that our theoretical analysis is accurate. Results show that the achievable SE increases with the number of antennas, the number of quantization bits of the ADC and the reflecting elements of the IRS, but tends to a saturation rate. In addition, we find that the SE inevitably suffers a certain loss due to the phase shift noise is unavoidable and the quantization accuracy of IRS, which can be compensated by increasing the transmit power and the number of reflecting elements.     

Performance analysis of massive MIMO systems with low-resolution ADCs and IQI

In massive multiple-input multiple-output (MIMO) systems, the substantial increase in the number of antennas leads to a surge in hardware cost and power consumption. Meanwhile, the impact of IQ imbalance (IQI) on system performance also tends to be serious. In this paper, closed-form expressions for the achievable rates of maximum-ratio combining (MRC) receivers are derived for uplink massive MIMO systems with both low-resolution analog-to-digital converters (ADCs) and IQI. Based on the derived closed-form expression, the influence of system parameters on the achievable rate is analyzed. The simulation results verify the accuracy of the theoretical results. It is found that low-resolution ADC and IQI will degrade the achievable rate compared with employing high resolution ADCs, but this loss can be compensated for by increasing the number of base station (BS) antennas, so as to significantly increase the energy efficiency.     

Low-Resolution ADCs for Two-Hop Massive MIMO Relay System under Rician Channels

This paper works on building an effective massive multi-input multi-output (MIMO) relay system by increasing the achievable sum rate and energy efficiency. First, we design a two-hop massive MIMO relay system instead of a one-hop system to shorten the distance and create a Line-of-Sight (LOS) path between relays. Second, we apply Rician channels between relays in this system. Third, we apply low-resolution Analog-to-Digital Converters (ADCs) at both relays to quantize signals, and apply Amplify-and-Forward (AF) and Maximum Ratio Combining (MRC) to the processed signal at relay R1 and relay R2 correspondingly. Fourth, we use higher-order statistics to derive the closed-form expression of the achievable sum rate. Fifth, we derive the power scaling law and achieve the asymptotic expressions under different power scales. Last, we validate the correctness of theoretical analysis with numerical simulation results and show the superiority of the two-hop relay system over the one-hop relay system. From both closed-form expressions and simulation results, we discover that the two-hop system has a higher achievable sum rate than the one-hop system. Besides, the energy efficiency in the two-hop system is higher than the one-hop system. Moreover, in the two-hop system, when quantization bits q = 4, the achievable sum rate converges. Therefore, deploying low-resolution ADCs can improve the energy efficiency and achieve a fairly considerable achievable sum rate.     

Secrecy energy efficiency optimization for multiuser massive MIMO wiretap systems with transmit antenna selection

Massive multiple-input-multiple-output (Massive MIMO) significantly improves the capacity of wireless communication systems. However, large-scale antennas bring high hardware costs, and security is a vital issue in Massive MIMO networks. To deal with the above problems, antenna selection (AS) and artificial noise (AN) are introduced to reduce energy consumption and improve system security performance, respectively. In this paper, we optimize secrecy energy efficiency (SEE) in a downlink multi-user multi-antenna scenario, where a multi-antenna eavesdropper attempts to eavesdrop the information from the base station (BS) to the multi-antenna legitimate receivers. An optimization problem is formulated to maximize the SEE by jointly optimizing the transmit beamforming vectors, the artificial noise vector and the antenna selection matrix at the BS. The formulated problem is a nonconvex mixed integer fractional programming problem. To solve the problem, a successive convex approximation (SCA)-based joint antenna selection and artificial noise (JASAN) algorithm is proposed. After a series of relaxation and equivalent transformations, the nonconvex problem is approximated to a convex problem, and the solution is obtained after several iterations. Simulation results show that the proposed algorithm has good convergence behavior, and the joint optimization of antenna selection and artificial noise can effectively improve the SEE while ensuring the achievable secrecy rate.     

Performance Analysis and Optimization of a Cooperative Transmission Protocol in NOMA-Assisted Cognitive Radio Networks with Discrete Energy Harvesting

In this paper, we propose a spectrum-sharing protocol for a cooperative cognitive radio network based on non-orthogonal multiple access technology, where the base station (BS) transmits the superimposed signal to the primary user and secondary user with/without the assistance of a relay station (RS) by adopting the decode-and-forward technique. RS performs discrete-time energy harvesting for opportunistically cooperative transmission. If the RS harvests sufficient energy, the system performs cooperative transmission; otherwise, the system performs direct transmission. Moreover, the outage probabilities and outage capacities of both primary and secondary systems are analyzed, and the corresponding closed-form expressions are derived. In addition, one optimization problem is formulated, where our objective is to maximize the energy efficiency of the secondary system while ensuring that of the primary system exceeds or equals a threshold value. A joint optimization algorithm of power allocation at BS and RS is considered to solve the optimization problem and to realize a mutual improvement in the performance of energy efficiency for both the primary and secondary systems. The simulation results demonstrate the validity of the analysis results and prove that the proposed transmission scheme has a higher energy efficiency than the direct transmission scheme and the transmission scheme with simultaneous wireless information and power transfer technology.     

A novel time and wavelength interleaved optical pulsed signal for a high resolution photonic analogue to digital converter

This paper presents a parallel architecture for a photonic Analog to Digital Converter (ADC) in a direct conversion receiver. A novel technique for the generation of time and wavelength interleaved laser source having a broad spectrum and a repetition rate of 8 GHz is proposed for the sampling of the photonic ADC. The quantization is realized in electrical domain by employing four state of the art ADCs , each having a sampling rate of 2 GHz and a resolution of 10 bit. We investigate the performance of our novel architecture by computing the Signal to Noise Ratio and comparing it with the conventional electronic ADC. Additionally we have also observed the effect of laser jitter on the sensitivity of a direct conversion receiver.     

Successive approximation-like 4-bit full-optical analog-to-digital converter based on Kerr-like nonlinear photonic crystal ring resonators

Implementing of photonic sampling and quantizing analog-to-digital converters (ADCs) enable us to extract a single binary word from optical signals without need for extra electronic assisting parts. This would enormously increase the sampling and quantizing time as well as decreasing the consumed power. To this end, based on the concept of successive approximation method, a 4-bit full-optical ADC that operates using the intensity-dependent Kerr-like nonlinearity in a two dimensional photonic crystal (2DPhC) platform is proposed. The Silicon (Si) nanocrystal is chosen because of the suitable nonlinear material characteristic. An optical limiter is used for the clamping and quantization of each successive levels that represent the ADC bits. In the proposal, an energy efficient optical ADC circuit is implemented by controlling the system parameters such as ring-to-waveguide coupling coefficients, the ring’s nonlinear refractive index, and the ring’s length. The performance of the ADC structure is verified by the simulation using finite difference time domain (FDTD) method.     

A low complexity burst channel estimation algorithm for FDD massive MIMO systems

To fully attain array gains of massive multiple-input multiple-output (MIMO) and its energy and spectral efficiency, deriving channel state information (CSI) at the base station (BS) side is essential. However, CSI estimation of frequency-division duplex (FDD) based massive MIMO is a challenging task owning to the required pilots, which are proportional to the number of antennas at the BS side. Therefore, the pilot overhead should be inevitably mitigated in the process of downlink channel estimation of FDD technique. In this paper, we propose a novel compressed sensing (CS) algorithm which takes advantage of correlation between the received and transmitted signals to estimate the channel with high precision, and moreover, to reduce the computational complexity imposed on the BS side. The main idea behind the proposed algorithm is to sort the specific number of maximum correlations as a common support in each iteration of the algorithm. Simulation results indicate that the proposed algorithm is capable of estimating downlink channel better than the counterpart algorithms in terms of mean square error (MSE) and the computational complexity. Meanwhile, the complexity of the proposed method linearly grows up when the number of BS antennas increases.     

Design of bitstream-based adaptive-connected array architecture for mmWave Multiuser MIMO systems

We investigate a bitstream-based adaptive-connected massive multiple-input multiple-output (MIMO) architecture that trades off between high-power full-connected and low-performance sub-connected hybrid precoding architectures. The proposed adaptive-connected architecture which enables each data stream to be computed independently and in parallel, consists of fewer phase shifters (PS) and switches than the other adaptive-connected architectures. With smaller array groups, the proposed architecture uses fewer PS and switches, so that its power consumption gradually decreases in millimeter wave (mmWave) Multiuser MIMO (MU-MIMO) system. To fully demonstrate the performance of the proposed architecture in mmWave MU-MIMO system with practical constraints, we combine the connection-state matrix with the hybrid precoders and combiners to maximize energy efficiency (EE) of the system equipped with the proposed architecture. We then propose the hybrid precoding and combining (HPC) scheme suitable for multi-user and multi-data streams which utilizes the SCF algorithm to obtain the constant modulus of the analog precoder at convergence. In the digital precoding and combining stage, the digital precoder and combiner are designed to reduce the amount of computation by utilizing the singular value decomposition (SVD) of corresponding equivalent channel. In the mmWave MU-MIMO-OFDM system equipped with the proposed architecture, with the increase of the total number of data streams, simulation results demonstrate that we can exploit the proposed HPC scheme to achieve better EE than the traditional hybrid full-connected architecture exploiting some existing schemes.     

Energy-Efficient Next-Generation Passive Optical Networks Based on Sleep Mode and Heuristic Optimization

Abstract

In this article, an energy-efficiency mechanism for next-generation passive optical networks is investigated through heuristic particle swarm optimization. Ten-gigabit Ethernet–wavelength division multiplexing optical code division multiplexing–passive optical network next-generation passive optical networks are based on the use of a legacy 10-gigabit Ethernet–passive optical network with the advantage of using only an en/decoder pair of optical code division multiplexing technology, thus eliminating the en/decoder at each optical network unit. The proposed joint mechanism is based on the sleep-mode power-saving scheme for a 10-gigabit Ethernet–passive optical network, combined with a power control procedure aiming to adjust the transmitted power of the active optical network units while maximizing the overall energy-efficiency network. The particle swarm optimization based power control algorithm establishes the optimal transmitted power in each optical network unit according to the network pre-defined quality of service requirements. The objective is controlling the power consumption of the optical network unit according to the traffic demand by adjusting its transmitter power in an attempt to maximize the number of transmitted bits with minimum energy consumption, achieving maximal system energy efficiency. Numerical results have revealed that it is possible to save 75% of energy consumption with the proposed particle swarm optimization based sleep-mode energy-efficiency mechanism compared to 55% energy savings when just a sleeping-mode-based mechanism is deployed.     

New generalized zero forcing beamforming for serving more users in energy-harvesting enabled networks

This paper considers a multi-user wireless communication network supported by a multiple-antenna base station (BS), where the users who are located sufficiently close to the BS employ wireless energy harvesting (EH) to replenish their energy needs. The objective of this work is to design an efficient beamforming to maximize the minimum throughput among all the information users (IUs), subject to EH constraints. In this regard, transmit time-switching approach is employed, where energy and information are transmitted over different fractions of a time-slot. To achieve efficient EH, a conjugate beamforming (matched filtering) is applied. To design efficient information beamforming for max–min throughput optimization, conventional zero-forcing (ZF) beamforming can be adopted, however, it will not suppress multi-user interference if the number of users is greater than the number of antennas at the BS. To this end, different from the existing works which employ regularized zero-forcing (RZF) beamforming, this work proposes a new generalized zero-forcing (GZF) beamforming, which promises better max–min throughput compared to that achieved by the RZF beamforming. A new path-following algorithm is developed to achieve max–min throughput optimization by GZF beamforming, which is based on a simple convex quadratic program over each iteration.     

Fairness driven performance analysis for 3-D Poisson Voronoi cell

The requirement of excellent anywhere–anytime data transmission service in future wireless network encourages us to reconsider the fairness among different types of users. To this end, the three-dimensional Poisson point process (PPP) model-based closed-form expressions of coverage probability for both cell-edge user (CEU) and cell inner user (CIU) under multi-user multiple-input multiple-output (MIMO) are derived. It is found that the spectral efficiency of CEU is about 30% of that of CIU under single user scenario. Moreover, when the number of users equals to that of base station (BS) antennas, the difference of coverage probability between CIU and CEU decreases with the number of BS antennas for large signal-to-interference ratio threshold. In addition, for the fixed number of users case, an inverted U-shaped relationship (thereby resulting in a worst case) between the fairness among CEU and CIU, and the number of BS antennas is detected. The impact of massive MIMO on the fairness under the metric of spectral efficiency is also discussed.     

Development of an ADC radiation tolerance characterization system for the upgrade of the ATLAS LAr calorimeter

ATLAS LAr calorimeter will undergo its Phase-I upgrade during the long shutdown(LS2) in 2018, and a new LAr Trigger Digitizer Board(LTDB) will be designed and installed. Several commercial-off-the-shelf(COTS)multi-channel high-speed ADCs have been selected as possible backups of the radiation tolerant ADC ASICs for the LTDB. To evaluate the radiation tolerance of these backup commercial ADCs, we developed an ADC radiation tolerance characterization system, which includes the ADC boards, data acquisition(DAQ) board, signal generator,external power supplies and a host computer. The ADC board is custom designed for different ADCs, with ADC drivers and clock distribution circuits integrated on board. The Xilinx ZC706 FPGA development board is used as a DAQ board. The data from the ADC are routed to the FPGA through the FMC(FPGA Mezzanine Card)connector, de-serialized and monitored by the FPGA, and then transmitted to the host computer through the Gigabit Ethernet. A software program has been developed with Python, and all the commands are sent to the DAQ board through Gigabit Ethernet by this program. Two ADC boards have been designed for the ADC, ADS52J90 from Texas Instruments and AD9249 from Analog Devices respectively. TID tests for both ADCs have been performed at BNL, and an SEE test for the ADS52J90 has been performed at Massachusetts General Hospital(MGH). Test results have been analyzed and presented. The test results demonstrate that this test system is very versatile, and works well for the radiation tolerance characterization of commercial multi-channel high-speed ADCs for the upgrade of the ATLAS LAr calorimeter. It is applicable to other collider physics experiments where radiation tolerance is required as well.     

The Optimal Power Allocation for Sum Rate and Energy Efficiency of Full-Duplex Two-Way Communication Network

Full-duplex (FD) transmission holds a great potential of improving the sum data rate of wireless communication systems. However, the self-interference introduced by the full-duplex transmitter brings a big challenge to enhance the energy efficiency. This paper investigates the power allocation problem in a full-duplex two-way (FDTW) communication network over an OFDM channel, aiming at improving the sum data rate and energy efficiency. We first characterize the sum rate and energy efficiency achieved in a single-carrier FDTW system. The optimal transmit power that achieves the maximal sum data rate is presented. The energy efficiency maximization problem is solved by using fractional programming. Then we further formulate sum rate and energy efficiency maximization problem in a multi-subcarrier FDTW system. In particular, the sub-optimal transmit power allocation which achieves a decent sum rate improvement is found by using a proposed iterative algorithm. By combining the iterative algorithm and fractional programming, we further maximize the energy efficiency of the multi-subcarrier system. With our proposed algorithm, we can easily obtain an optimal transmit power that approximates the global optimal solution. Simulation results show that using the obtained optimal transmit power allocation algorithm can significantly improve the sum rate and energy efficiency in both single-carrier and multi-subcarrier systems.     

12 bit 30 MSPS逐次比较型ADC的测试

针对物理实验读出的需求设计了一款低功耗12 bit 30 MSPS逐次比较型模数变换器（Analog-to-Digital Converter,ADC）芯片,为评估其性能指标参数,需进行系统的测试。在本研究工作中构建了测试系统,然后按照IEEE标准进行了系统的测试和分析。测试结果表明,输入信号在基带范围内ADC有效位（Effective Number Of Bit,ENOB）约为9 bit,达到了本版本芯片的设计指标。同时,综合分析静态性能与动态性能测试结果,可以通过优化逐次比较型ADC中电容阵列电容失配参数,进一步提升ADC的非线性指标,为下一版芯片的改进设计提供了参考依据。Aiming at the requirement of readout electronics in physics experiments, a 12 bit 30 MSPS successiveapproximation-register (SAR) analog-to-digital converter (ADC) with low power consumption has been designed. To evaluate the performance of this ASIC, we conducted a series of tests. We set up a test system, and we tested the ADC according to IEEE std 1241-2010. The test results indicate that the effective number of bit (ENOB) of the ADC is around 9 bits when the input signal is in the first Nyquist zone, which has met the design requirements. According to the results of dynamic and static tests of this ADC, we found that the non-linearity performance of this ASIC can be further enhanced by improving the mismatching among the capacitor array, and this provides important information for the design of the second version of this ADC.     

Optimal power allocation for maximizing the energy efficiency of NOMA enabled full-duplex coordinated direct and relay transmission (CDRT) system with SWIPT

In this paper, we investigate the energy efficiency (EE) performance of non-orthogonal multiple access (NOMA) enabled full-duplex (FD) coordinated direct and relay transmission (CDRT) system (i.e., NOMA-FD-CDRT system). Firstly, we consider a two-user scenario, where the base station (BS) can directly communicate with the near user, while it requires the help of a dedicated FD relay node to communicate with the far user. In the second part, we consider that there are two near users and two far users in the system. To improve the EE, we consider integrating the simultaneous wireless information and power transfer (SWIPT) technique at the FD relay. We formulate an analytical expression for the overall EE of the SWIPT-assisted NOMA-FD-CDRT system. We determine optimal power allocation (OPA) for the downlink users at the BS that maximizes the EE. An iterative algorithm based on Dinkelbach method is proposed to determine the OPA vector. With the help of detailed numerical and simulation investigations, it is demonstrated that the proposed OPA can provide significant enhancement of EE of the considered SWIPT-assisted NOMA-FD-CDRT system.     

Joint user grouping and power allocation in VLC-NOMA system

With the energy consumption of wireless networks increasing, visible light communication (VLC) has been regarded as a promising technology to realize energy conservation. Due to the massive terminals access and increased traffic demand, the implementation of non-orthogonal multiple access (NOMA) technology in VLC networks has become an inevitable trend. In this paper, we aim to maximize the energy efficiency in VLC-NOMA networks. Assuming perfect knowledge of the channel state information of user equipment, the energy efficiency maximization problem is formulated as a mixed integer nonlinear programming problem. To solve this problem, the joint user grouping and power allocation (JUGPA) is proposed including user grouping and power allocation. In user grouping phase, we utilize the average of channel gain among all user equipment and propose a dynamic user grouping algorithm with low complexity. The proposed scheme exploits the channel gain differences among users and divides them into multiple groups. In power allocation phase, we proposed a power allocation algorithm for maximizing the energy efficiency for a given NOMA group. Thanks to the objective function is fraction form and non-convex, we firstly transform it to difference form and convex function. Then, we derive the closed-form optimal power allocation expression that maximizes the energy efficiency by Dinkelbach method and Lagrange dual decomposition method. Simulation results show that the JUGPA can effectively improve energy efficiency of the VLC-NOMA networks.     

RIS-assisted cell-free massive MIMO systems with reflection area: AP number reduction

Cell-free massive multiple-input multiple-output (MIMO) has been regarded as a promising technology due to high spectral efficiency. However, as large number of access points (APs) are deployed with fibers connecting to the central processing unit, the increase of energy consumption and hardware cost raise concerns. The reconfigurable intelligent surface (RIS) with impressing potential for low energy and cost finds a way to solve this problem. In this paper, we investigate the performance of the cell-free massive MIMO system with a RIS. As RIS can only reflect signals from the front, user equipments (UEs) and APs are divided into two categories according to their relative position with the RIS, i.e., one is on the reflection area of the RIS and the other is not. A closed-form approximation of the UE achievable downlink rate is derived. Based on it, we obtain the optimal RIS position and phase shift that can maximize the UE sum rate, through alternating optimization method. It is found that compared with the cell-free massive MIMO system without RIS, to achieve the same rate performance, the number of required AP in the RIS-assisted system can be significantly reduced. Moreover, as the RIS component increases, the number of required AP can be reduced almost linearly without rate reduction, which means the hardware and energy cost can be greatly cut down. Furthermore, from our simulation results, we can see that when users are densely distributed, the optimal location of the RIS should be closer to users. When users are uniformly distributed, the optimal position of RIS is close to the central position.     

Joint Resource Allocation for Multiuser Opportunistic Beamforming Systems with OFDM-NOMA

Opportunistic beamforming (OBF) is an effective technique to improve the spectrum efficiencies (SEs) of multiple-input-multiple-output (MIMO) systems, which can obtain multiuser diversity gains with both low computation complexity and feedback information. To serve multiple users simultaneously, many multiple-access schemes have been researched in OBF. However, for most of the multiple-access schemes, the SEs are not satisfactory. To further improve the SE, this paper proposes a downlink multiuser OBF system, where both orthogonal frequency division multiplexing (OFDM) and non-orthogonal multiple-access (NOMA) methods are applied. The closed-form expressions of the equivalent channels and SE are derived in frequency selective fading channels. Then, an optimization problem is formulated to maximize the SE, although the optimization problem is non-convex and hard to solve. To obtain the solution, we divide the optimization problem into two suboptimal issues, and then a joint iterative algorithm is applied. In the proposed optimization scheme, the subcarrier mapping ϑ, user pairing knc and allocated power Pknc are determined to maximize spectrum efficiency (SE) and reduce bit error ratio (BER). According to numerical results, the proposed method achieves approximately 5 dB gain on both SE and BER, compared to the existing beamforming methods with low feedback information. Moreover, the SE of the proposed method is approximately 2 (bps/Hz) higher than sparse code multiple-access (SCMA), when the number of waiting users and the ratio of transmit power to noise variance are respectively 10 and 20 dB. It is indicated that the proposed scheme can achieve high and low BER with the limited feedback and computation complexity, regardless of the transmit power and the number of waiting users.     

Closed-form MSE and achievable rate for indirect learning DPD

The digital pre-distortion (DPD) signal processing is an effective way to mitigate the power amplifier (PA) nonlinearity effect. For communication systems containing DPD and PA, it is difficult to acquire performance metrics closed-forms for any DPD architecture since there was no mathematical expression for each DPD coefficient. Usually, researchers look for more efficient DPD algorithms for DPD coefficients (compared to the existing ones) in terms of computational complexity, delay, power consumption, etc. Consequently, the performance is evaluated through intensive simulation. In this paper, we show how one can exploit the results of our recent work to mathematically model the indirect learning architecture (ILA) DPD and efficiently derive important measures in communication systems, e.g. normalized mean square error (NMSE), achievable rate, and signal-to-noise plus distortion ratio (SNDR). The author would like to clarify that this work might be the first one to provide closed-form analysis for DPD systems. We think the provided framework/analysis will open the door to other researchers/engineers to plug their own assumptions and derive the performance metrics. The derived expressions of the performance metrics (NMSE, SNDR, and achievable rate) are validated through Monte Carlo simulations. We also derive a closed-form expression for the achievable rate bound for the transmit chain. Moreover, we analytically study the effect of the thermal noise and the quantization noise, in the analog-digital conversion (ADC) process, on the NMSE and achievable rate. The analytical expressions are validated through numerical simulations.