Search

To enhance the information security in multiple input multiple output (MIMO) wireless communication systems, nonlinear transmission is studied in this paper by pushing the power amplifier (PA) at the transmitter to operate in the nonlinear region, even near to the saturate point. Linearization reception technique is then adopted at the legal user's receiver to remove the distortion caused by the nonlinear PA, so that the distortion-free signal can be drawn, and correct demodulation and decoding could be achieved. While for the eavesdroppers, the information required to complete the nonlinear reception could hardly be obtained, since the critical training sequence is designed to be invisible to the eavesdropping users, so the security transmission between the legitimate users can be obtained. Then, the security capacity by nonlinear transmission is analyzed in the MIMO–OFDM systems, where the signal to distortion plus noise ratio is derived, and the upper approximation is also presented. Numerical simulations are carried out to verify the effectiveness of the proposed scheme with practical reception algorithm, and it is shown that obvious security capacity can be acquired with both memory and memoryless PAs. [ABSTRACT FROM AUTHOR]

Millimeter wave massive multiple-input and multiple-output (MIMO) systems support several antennas at the receiver and transmitter sides to serve several users in a communication system. Due to its several antennas, the system cost is very high and faces challenges such as blockage, path loss, and interference. To solve the above interference problem, beamforming technology and LMS Kalman filter-based Hybrid Precoding are used in millimeter wave massive MIMO system by directing the signal in the desired direction and to get a reduced bit error rate. Therefore, proposed hybrid precoding aims to leverage the advantages of both digital and analog beamforming while significantly reducing the number of RF chains compared to the number of antennas, all while maintaining the benefits of spatial multiplexing. This paper compares the performance of various precoding techniques, including Analog-only Beamsteering, Zero Forcing (ZF), Minimum Mean Square Error (MMSE), Kalman, Minimum Square Error Fully digital (MSE Fully digital), and Proposed Least Mean Squares (LMS) Kalman Hybrid Precoding, using performance metric parameters such as spectral efficiency, energy efficiency, bit error rate, and Information rate. The LMS Kalman Hybrid Precoding improved the spectral efficiency by almost 6.228 bps/Hz at 10 dB with ten channel paths concerning the Analog-only Beamsteering and almost 3.748, 2.974, 2.758, and 0.399 bps/Hz for the Zero Forcing (ZF) Hybrid Precoding, MMSE, Kalman, and MSE Fully Digital Hybrid Precoding techniques, respectively, which shows the superiority of the Proposed Least Mean Squares (LMS) Kalman Hybrid Precoding. [ABSTRACT FROM AUTHOR]

In this research, we study the interference cancellation capabilities of receivers and transmitters in multiple-input-multiple-output (MIMO) systems using theoretical calculations and numerical simulations in Quadriga. We study so-called Reduced Channel Zero-Forcing (RCZF) class of precoding as well as Minimum MSE Interference Rejection Combiner (MMSE-IRC) and QR Maximum Likelihood Detection (QR-MLD) receivers. The precodings from the RCZF class are widely used in practice and include for example Zero-Forcing (ZF) and Eigen Zero-Forcing (EZF) precodings. Our theoretical and experimental results confirm that MMSE-IRC and QR-MLD receivers in combination with the RCZF precoding provide complete interference suppression asymptotically. The major findings and the calculation results far as the RCZF class of precoding as well as the MMSE-IRC and QR-MLD receivers' performance concerned, which is a subject of the paper. [ABSTRACT FROM AUTHOR]

In recent years, Multiple Input–Multiple Output (MIMO) has been used to expand data transfer for ensuring consistency. The transmitter and receiver use several antennas and they can achieve high spectral characteristics. The numbers of users and antennas increase rapidly questions the stability and reliability of the system. When MIMO is deployed, the complexity of the system increases and it becomes a major problem in many detection systems. When more and more number of receiver and senders pre-require an increased number of hardware components and a part it further increases the system's complexity and design. It is important to develop sophisticated components to improve compliance with many standards without compromising the Bit Error Rate (BER) performance of the components. The proposed work introduces a New Hybrid MIMO Detector (NHMD), which provides the solution for the complicated design procedure. The core concentration of this work is to minimize the complexity (Hardware) of the system by applying simplest design approach. This Hybrid system with a minimalistic detection approach helps in improve the BER: (Bit Error Rate) of the framework without compromising the overall performance of the system. This proposed method is designed on the Modified Optimal Differential Evolution (MODE) algorithm which is used to apt the best detector by deploying the objectives of this work. In addition, this method uses parallel processing to reduce the amount of arithmetic logic. The proposed NHMD method is implemented for cylindrical devices belonging to different FPGA families with different antenna configurations (2 × 2, 4 × 4). The proposed NHMD method provides superior quality by combining multiple detectors. The simulation results confirm that the NHMD method uses low equipment as well as low power consumption and provides high efficiency without affecting BER performance. [ABSTRACT FROM AUTHOR]

In this paper, we consider a point-to-point MIMO system with the amplified-and-forward full-duplex relay that the source can communicate with destination through the relay. The optimization problem for this scenario is non-convex, and finding the hybrid beamforming matrices, is a significant challenge. Here we propose two methods to design hybrid beamforming matrices in a full-duplex relay scenario. In the first method, we separate the transmitter and receiver sides of the relay and formulate the optimization problems. In the second method, we designed the beamforming relay matrices in a joint manner and proposed an algorithm to find a nearly-optimum full-duplex relay to achieve higher performance. Simulation results show that the joint optimization method achieves higher spectral efficiency than the separation method (first method). In addition the impact of the number of RF chains, is carried out by simulation. The simulation demonstrates that the number of antennas in the relay has an optimum value for a fixed number of RF chains. [ABSTRACT FROM AUTHOR]

This research examines the performing of linear precoding techniques in downlink massive MIMO systems. The downlink massive MIMO systems, linear precoding techniques as combined to zero forcing (ZF) and matched filter (MF), truncated polynomial expansion (TPE) and regularized zero forcing (RZF). The output of massive MIMO downlinks is analyzed with linear precoding. The performing of sum rate precoding of signal-to-noise (SNR) ratio, as well as numerous transmitter-receiver antennas, is discussed, including defective CSI and inter-user interference. On the channel, the transmitter as entire state information. The data describes how a signal travels from the transmitter to the receiver, taking into account factors like as space scattering and power decay. They appearance that given a perfect chain, the performing analyzed of two linear precoding approaches, namely Zero Forcing (ZF) and Matched filter (MF) for downlink mMIMO. The results demonstrate ZF, higher BER and sum rate as comparing to MF schemes, as well as a comparison of RZF and TPE average achievable rates. In multi-user scenarios, Kalman-based hybrid precoding (analog/digital) as used in a downlink throughput of 5.14 Gbps and a uplink rate of 2.26 Gbps. The impact of beam steering capability on both base stations (BS) and 5G user equipment (UEs) is also investigated. Based on the simulation results, the suggested approach provides a significant increase in spectral efficiency of 10.53 bps/Hz with 10 channel routes. [ABSTRACT FROM AUTHOR]

A typical 5G multiple-input and multiple-output (MIMO) system must combine a high number of antennas at both the transmitter and receiver to realize spatial multiplexing capability. In this paper, a wideband 16- element indoor base station (BS) antenna array that can cover 3.3–6.0 GHz is proposed for 5G applications. A π-shaped monopole antenna is designed to cover the Lower band (LTE bands 42/43–N77–N78), the intermediate band (N79), and the higher band (LTE 46). The antenna elements are arranged in a limited space printed on a substrate take the Hexakaidecagon Polygon shape. As the antenna elements are arranged with good isolation, achieving good polarization diversity. The proposed BS array is simulated, fabricated, and tested. The typical results, S-parameters, antenna efficiency, and radiation patterns are investigated. Moreover, to validate the MIMO performances, a very low envelope correlation coefficient (ECC) below 0.02, high antenna efficiency of about 82–93.2% are achieved. The calculated ergodic channel capacity of the 16 × 16 MIMO system reached up to 85 bps/Hz. The proposed antenna array was compared to some other 5G MIMO indoor base station antennas. [ABSTRACT FROM AUTHOR]

By exploiting the carrier frequency offset (CFO) between a transmitter-receiver pair, this paper proposes a CFO-based physical layer authentication scheme for dynamic multiple-input-multiple-output (MIMO) systems. We first provide analytical modeling of dynamic CFO in such MIMO systems by jointly taking into account the intrinsic oscillator mismatch and Doppler frequency shift caused by node mobility, and employ the self-correlating and extended Kalman filtering techniques for the CFO estimation and prediction. By quantizing the difference between the estimated CFO and predicted one, we then apply the statistical signal processing techniques to develop a CFO-based physical layer authentication scheme for transmitter identity verification. With the help of tools from stochastic process and hypothesis testing theories, we further derive the analytical expressions for false alarm rate as well as detection rate to evaluate the performance of the proposed scheme. Finally, we provide extensive numerical results to demonstrate the efficiency of the proposed scheme. [ABSTRACT FROM AUTHOR]

This paper proposes two algorithms for hybrid (Analog–Digital) beamforming in a single-user millimeter-wave (mm-wave) multi-input multi-output (MIMO) systems under frequency selective channels. Hybrid architecture has a potential to reduce the number of radio frequency (RF) chains to far less than the number of antennas and, it results in low hardware complexity, power efficiency and cost-saving to the system. Since practical broadband systems are frequency selective in nature therefore, the challenging aspect of this problem is to have only one analog RF processing matrix at source and destination over the entire frequency band. To address this problem for spectral efficiency maximization, the first algorithm performs multi-linear singular value decomposition on different sub-carriers to derive the common analog combiner over the allocated frequency-spectrum. Then, a problem is formulated for designing the common analog precoder that attempts to extract the optimal phase values for gain maximization of the equivalent channel observed from baseband processing units at transmitter and receiver. To significantly reduce the computational complexity in comparison to the first algorithm, the second algorithm employs classification of beamforming vectors for gain maximization of the equivalent baseband channel over all sub-carriers to find the analog RF precoding/combining matrices. Digital baseband processing components are derived by diagonalizing the equivalent baseband channel corresponding to each frequency-carrier. Computational complexity of the second algorithm is significantly less than the several existing designs. Computer simulations reveal that the proposed algorithms show near-optimal performance under diverse scenarios of system configuration parameters. [ABSTRACT FROM AUTHOR]

An approach is proposed for the development of algorithms for orthogonal precoding to achieve the effect of full diversity in communication systems with a MIMO channel with linear processing on the receiving side. The developed algorithms can be used for any configuration of the MIMO channel and are implemented in the form of fast orthogonal transformation vectors of size each ( is the number of transmitting antennas), and the distribution of the transformed symbols of these vectors over different cycles and transmitting antennas. The results of modeling the proposed precoding algorithms are presented, which showed that their use allows obtaining a gain of 2–5 dB, depending on the configuration of the MIMO system. In this case, the number of operations in the implementation of a linear receiver increases only by , i.e., the complexity of the receiver remains virtually unchanged. [ABSTRACT FROM AUTHOR]

In Underwater communication, the main issues are channel variation, propagation delay, and multipath transmission path variation, attenuation of transmitted signal over a long-distance transmission. Even though continental communication is used in many places, underwater communication has recently been adopted in important places. The reason behind it is using audio waves instead of EM wave which has a low data rate. Hence, a novel underwater acoustic OFDM communication is introduced in this paper with the Polar Run Limited encoder (PRLE) scheme and compared with various existing methods. PRLE encodes the data on the transmitter side and at the receiver side with the help of the codebook, the original information is retrieved. The main concept of FWFT is it reduces size and complexity in order to achieve a high-performance UW-OFDM system. The proposed PRL decoding depends on the codebook information, hence the channel state information (CSI) is not needed for UW transmission. The simulation result shows that the BER value is reduced to 78% when compared with CRC followed convolution encoding method and complexity reduced by 21% compared with FFT based transform technique. As a result, this proposed system has achieved a less BER, low SNR, and low complexity system which can improve the MIMO system operation. [ABSTRACT FROM AUTHOR]

Fifth and future generation (5G and B5G) wireless networks aim to serve users with higher data rates and lower latency. Data traffic due to the rapid growth in communication has motivated the study of Multiple Input Multiple Output (MIMO) systems. They utilize multiple antennas in both transmitter and receiver sides. It is necessary to improve the existing technology to achieve fast and reliable communication. In this research work, a rectangular array antenna based hybrid beamforming in a massive MIMO model has been proposed to improve the spectral efficiency of the system. Thus channel capacity with small RF chains is used. To achieve the high signal strength in the main lobe, Chebyshev tapering has been used to suppress the side lobes signals. In this manner, the proposed Hybrid Beamforming for Massive Output MIMO has been realized with a small complexity and higher spectral efficiency. In this research work, the spectral efficiency of both proposed Hybrid and fully-digital beamforming with a different number of RF chains for a various number of antennas at the transmitter, the receiver side has been analyzed. From the simulation results, it has been observed that the proposed rectangular array antenna based Hybrid beamforming in a massive MIMO system reduces the computational complexity up to 99% as compared with conventional fully digital beamforming to achieve the same spectral efficiencies, which is a productive model for 5G wireless networks. [ABSTRACT FROM AUTHOR]

Massive multiple-input multiple-output (massive-MIMO) is a promising technology for next generation wireless communications systems due to its capability to increase the data rate and meet the enormous ongoing data traffic explosion. However, in non-reciprocal channels, such as those encountered in frequency division duplex (FDD) systems, channel state information (CSI) estimation using downlink (DL) training sequence is to date very challenging issue, especially when the channel exhibits a shorter coherence time. In particular, the availability of sufficiently accurate CSI at the base transceiver station (BTS) allows an efficient precoding design in the DL transmission to be achieved, and thus, reliable communication systems can be obtained. In order to achieve the aforementioned objectives, this paper presents a feasible DL training sequence design based on a partial CSI estimation approach for an FDD massive-MIMO system with a shorter coherence time. To this end, a threshold-based approach is proposed for a suitable DL pilot selection by exploring the statistical information of the channel covariance matrix. The mean square error of the proposed design is derived, and the achievable sum rate and bit-error-rate for maximum ratio transmitter and regularized zero forcing precoding is investigated over different BTS topologies with uniform linear array and uniform rectangular array. The results show that a feasible performance in the DL FDD massive-MIMO systems can be achieved even when a large number of antenna elements are deployed by the BTS and a shorter coherence time is considered. [ABSTRACT FROM AUTHOR]

One of the motivations towards the 5G cellular networks and beyond is the large increase in the supported data rate in both uplink and downlink. Deployment of small size cells, massive MIMO, wherein a large number of antennas are deployed at transmitters and receiver, are effective tools in these networks. Users under cell massive MIMO networks "mMIMO" can provide high data rate. However, the cell-edge user and users, under shadowing, can have a poor performance. Cell-Free networks can provide a satisfied data rate even for shadowed and cell-edge users. In this paper, cell-Free mMIMO networks are mathematically analyzed applying different cooperation mechanisms among the access points APs. Moreover, a new mathematical formula for the throughput, based on BER, is derived. Furthermore, closed formulas for the throughput-BER as well as energy efficiency (EE) performance are derived. Finally, the cognitive radio concept is proposed in order to limit the interference among users accessing the same resources in uplink. Simulation results show that the fully centralized cell-Free mMIMO network has a higher spectral efficiency and energy efficiency than the cellular mMIMO networks at different BER values especially when MMSE is applied. Furthermore, the cognitive radio theory can increase the SE and EE performance of the cell-Free networks when all cooperation mechanisms are applied. [ABSTRACT FROM AUTHOR]

Media-based modulation (MBM) is a novel modulation technique that can improve the spectral efficiency of the existing wireless systems. In MBM, multiple radio frequency (RF) mirrors are placed near the transmit antenna(s) and are switched ON/OFF to create different channel fade realizations. In such systems, additional information is conveyed through the ON/OFF status of RF mirrors along with conventional modulation symbols. A challenging task at the receiver is to detect the transmitted information symbols and extract the additional information from the channel fade realization used for transmission. In this paper, we consider a massive MIMO (mMIMO) system where each user relies on MBM for transmitting information to the base station, and investigate the problem of symbol detection at the base station. First, we propose a mirror activation pattern (MAP) selection based modified iterative sequential detection algorithm. With the proposed algorithm, the most favorable MAP is selected, followed by the detection of symbol corresponding to the selected MAP. Each solution is subjected to the reliability check before getting the update. Next, we introduce a K favorable MAP search based iterative interference cancellation (KMAP-IIC) algorithm. In particular, a selection rule is introduced in KMAP-IIC for deciding the set of favorable MAPs over which iterative interference cancellation is performed, followed by a greedy update scheme for detecting the MBM symbols corresponding to each user. Simulation results show that the proposed detection algorithms exhibit superior performance-complexity trade-off over the existing detection techniques in MBM-mMIMO systems. [ABSTRACT FROM AUTHOR]

Multiple-input multiple-output (MIMO) communications are believed as one of the key enabling technologies to fulfill the increasing requirements of future wireless networks. However, the asymptotic performance limits of MIMO vehicular ad hoc network (VANET) systems are not thoroughly investigated. All the related works on MIMO VANETs mainly focused on measurement and geometry based channel analyzing and modeling. In this paper, we present a framework for ergodic capacity analysis on MIMO communications among multi-antenna mounted vehicles. We model a Rayleigh fading channel with standard path-loss and lognormal shadowing, then adopt the tools of stochastic geometry to characterize the MIMO geocast channels. After analyzing the co-channel interference among MIMO geocast sessions, the upper and lower bounds on ergodic capacity of single link MIMO and MIMO geocast channels are derived with careful consideration of the important issues like antenna number, shadow fading, and transmission radius. Results reveal that ergodic capacity of MIMO VANETs can be significantly improved by appropriately mounting multiple transmit and receive antennas on vehicles. As the space for antenna mounting in a vehicle is rather limited, we further give a method to calculate the minimum number of antennas for each vehicle to guarantee the quality of service (QoS) requirements in safety oriented applications of IoV. [ABSTRACT FROM AUTHOR]

Millimeter-wave (mmWave) and massive multi-input–multi-output (mMIMO) communications are the most key enabling technologies for next generation wireless networks to have large available spectrum and throughput. mMIMO is a promising technique for increasing the spectral efficiency of wireless networks, by deploying large antenna arrays at the base station (BS) and perform coherent transceiver processing. Implementation of mMIMO systems at mmWave frequencies resolve the issue of high path-loss by providing higher antenna gains. The motivation for this research work is that mmWave and mMIMO operations will be much more popular in 5G NR, considering the wide deployment of mMIMO in major frequency bands as per 3rd generation partnership project. In this paper, a downlink multi-user mMIMO (MU-mMIMO) hybrid beamforming communication system is designed with multiple independent data streams per user and accurate channel state information. It emphasizes the hybrid precoding at transmitter and combining at receiver of a mmWave MU-mMIMO hybrid beamforming system. Results of this research work give the tradeoff between multiple data streams per user and required number of BS antennas. It strongly recommends for higher number of parallel data streams per user in a mmWave MU-mMIMO systems to achieve higher order throughputs. [ABSTRACT FROM AUTHOR]

In this paper, a Sparse Bayesian Learning (SBL) based channel estimation technique for frequency selective millimeter wave (mmWave) channel in the time domain approach is developed. Further, SBL based Kalman filter (SBL-KF) for time and frequency selective mmWave multiple-input multiple-output (MIMO) hybrid architecture is presented. Hybrid precoders and combiners are designed to estimate the channel of mmWave MIMO systems. The hybrid precoding technique provides low power consumption and high achievable rate performance at mmWave frequencies. mmWave channels are sparse in nature, and the sparse recovery problem is estimated using the channel estimation technique. A simulation result of SBL-KF is improved by 4 dB and 10 dB of SNR compared to the conventional SBL and Orthogonal Matching Pursuit based scheme, respectively. The proposed SBL-KF scheme provides low estimation error at smaller training overheads M = 50 compared to the other existing work. [ABSTRACT FROM AUTHOR]

In this study, optimum channel estimation in MIMO network is investigated by an integrated computing paradigm using Particle Swarm Optimization (PSO) and Nelder Mead Method (NMM). The efficacy of global optimization is exploited through PSO while for fine-tuning of channel coefficients, the strength of NMM as an efficient local optimization technique is utilized. Hybrid swarm intelligence framework is applied for square channel matrix having identical array elements at both transmitter and receiver end. Different signal–noise ratios are applied for analyzing the response of complex received signal from flat fading Additive White Gaussian Noise channel. Numerical simulations are done for evaluating Mean Square Error among true and estimated channel coefficients. Performance analysis is conducted not only for a single run of proposed hybrid swarm intelligence but also on extensive simulations on multiple independent trials to prove the worth of the scheme. [ABSTRACT FROM AUTHOR]

A position-aided fast beam training in mm-Wave multiuser MIMO systems (PAFBT) method is proposed, in the case of inexact position information. Position information can be used to compute the pointing direction and essentially eliminate the beam alignment overhead. But the incorrect position information will introduce the beam misalignment. To solve the estimated received nodes location uncertainty problem, a beam training scheme is conducted by transmitting the beams to cover critical areas of the received nodes to find out the best transmitter and receiver beams for establishing the links in mm-Wave multiuser MIMO systems. Mathematical and simulation analysis confirm the superiority of the proposed method over the conventional ones in performance. [ABSTRACT FROM AUTHOR]

In this study, nature inspired computing (NIC) techniques are designed for estimation of channel co-efficients in multi-inputs multi-output (MIMO) networks. NIC methods based on recently introduced variants of swarm intelligence are exploited as optimization mechanism for MIMO channel co-efficients estimation. In MIMO systems there is m input matrix s multiplied with channel matrix H and there is some addition of noise ν and this whole is equivalent to output matrix r. In this research work, the goal is to achieve an optimized channel co-efficient matrix of different orders with the help of various NIC based optimization techniques. Such that MIMO networks give output exactly matching with the information sent by the transmitter. Comparative studies for the parameter estimation of MIMO networks against the true values of the parameters is evaluated by taking different cases, based on variations in the order of channel matrix and SNRs values. Performance analysis of the proposed NIC variants is conducted for single preferred run. NIC computing is done for equal number of antennas on transmitter and receiver end making a square channel matrix H. Four cases are taken in this research work for checking the trend of received signal for noisy channel like rayleigh fading channel. In each case channel estimation is developed by taking channel matrix of orders 2 × 2, 3 × 3, 4 × 4 and 8 × 8. In each case there are five sub cases which are without noise and for different values of SNR such as 70 db, 60 db, 50 db and 40 db. [ABSTRACT FROM AUTHOR]

Training sequence is used in multiple antenna systems to estimate channel state information and mitigate channel distortion between transmitter and receiver. However, the training sequence or pilot must be limited to a certain size in order to reduce the impact of overhead loss due to limited channel coherence length in mobile users. In this paper, we proposed to use training size optimization in cell-free massive MIMO system. In addition, we proposed and compared the performance of different training size optimization algorithms, namely exhaustive search optimization, bisection optimization and min–max optimization, with each method has different level of calculation complexities. The results showed that in general, all of the 3 training length optimization methods improved the downlink rate compared to the conventional pilot length method. We also showed that the training optimization methods are more effective when the coherence length is small or the number of users is very large. In the case of large number of users or small coherence length, the exhaustive search has the best median downlink rate, followed closely by min–max optimum and finally the bisection method. Even though the exhaustive search optimization has the best downlink rate, we showed that the proposed reduce optimization complexity methods has significantly less calculation complexity. In addition, the median downlink rate performance of min–max optimization method is only slightly less than that of the exhaustive search method for various number of users and coherence length. [ABSTRACT FROM AUTHOR]

This paper analyzes the performance of quadrature spatial modulation (QSM) multiple-input multiple-output (MIMO) system in cooperative decode and forward (DF) networks over correlated and imperfect η-μ fading channels. QSM is a recently proposed propitious MIMO technique that promises significant advantages over conventional MIMO schemes including high spectral efficiency with single RF-chain transmitter and very low receiver complexity. In this study, DF cooperative communication system adopting QSM technique is presented and throughly analyzed. Single or multiple DF relays are placed between the source and the destination to cooperate in the transmission process. Only the relays that decode the signal correctly will participate in the retransmission process. The end to end performance of the considered system is analyzed over correlated and imperfect η-μ fading channels. The η-μ channel is a general fading distribution that includes some other well-known channels, such as Rayleigh and Nakagami-m, as spacial cases. Monte Carlo simulation results are presented to corroborate the accuracy of the conducted analysis. The impact of spatial correlation, imperfect channel estimation and the fading parameters η and μ on the overall performance is investigated and exhaustively discussed. [ABSTRACT FROM AUTHOR]

Recently, distributed transmit-antenna selection schemes have attracted great interest, since they capture the essential benefits of multi-antenna systems while reducing their cost, complexity, delay, and feedback overhead. In those distributed schemes, the antenna selection is based on local channel-state information, in contrast to their optimal centralized counterparts, which require knowing the channel state of all links. Herein, we design two such distributed schemes for a dual-hop variable-gain amplify-and-forward relaying system with one multi-antenna source, one single-antenna relay, and one single-antenna destination. The two schemes differ in the diversity method used at the destination, namely, selection combining or maximal-ratio combining, and in the selection rule accordingly. In addition to conceiving these new schemes, we analyze their outage performance. Since an exact analysis proves intractable, we tackle the outage probability in terms of lower-bound expressions and their asymptotes at high signal-to-noise ratio. Importantly, the derived bounds turn out to be almost indistinguishable from the true performance, assessed via simulation. Our results reveal that the proposed distributed schemes achieve the same diversity order of their optimal centralized counterparts and perform closely to these, specially when the relay is near the source or destination. [ABSTRACT FROM AUTHOR]

This paper proposes a novel efficient precoding algorithm to maximize the rate of the cognitive link, where a pair of multiple-input multiple-output cognitive radio users shares the spectrum allocated to multiple primary users as long as the interference power is acceptable. In our method, the precoding vectors are firstly obtained by solving an unconstrained convex problem which is formulated by using the penalty function idea and has a closed-form solution. Then, power is allocated to different precoding vectors to satisfy both the transmit-power constraint and interference-power constraints through interior method. Moreover, an effective set of the penalty weights is presented. Our method has much lower complexity than the optimal solution and similar complexity to other low-complexity methods. Simulation results show that our method significantly outperforms the existing low-complexity methods and has almost the same performance as the optimal solution. [ABSTRACT FROM AUTHOR]

In this paper, we deal with the problem of acquiring the channel state information (CSI) at the transmitter in large-scale multiple input multiple output (MIMO) systems, so-called massive MIMO systems. Clearly, obtaining CSI plays a central role to provide high system performance. Even though, in frequency-division duplexed systems, acquiring this information requires a prohibitive amount of feedback, since it increases with the number of transmit antenna. In this work, we design an efficient transmit antenna selection strategy aware of the amount of required CSI for a point-to-multipoint transmission in massive MIMO systems. The proposed strategy provides high sum-rate with limited CSI feedback and limited computational complexity. Innovatively, the antenna selection in our strategy is performed in a decentralized fashion successively at the receiving users. Two schemes are proposed in this work to perform the antenna selection at each user. Next, taking into consideration that the large-scale MIMO transmitter suffers from imperfect knowledge of CSI, we design a new performance criterion. Computer simulations validate that, when the CSI is perfectly known, the proposed strategy is able to achieve high performance in terms of system sum-rate while a significant reduction in both CSI feedback overhead and computational complexity is observed. Moreover, assuming imperfect CSI, the new proposed criterion achieves higher performance when the estimation accuracy is low and at high SNR regime. [ABSTRACT FROM AUTHOR]

Very large multiple-input multiple-output (MIMO) technology has a potential of significantly improving the system performance of multi-cell time-division duplexing (TDD) networks, but in practice it is limited by pilot contamination. Different from the traditional channel estimation mean square error (MSE) expressions, the expressions that we derived have algebraic form, which no longer need hard matrix inversion as M, the number of the base station (BS) antennas, increasing. From them, we also found that the average transmitted power and length of training sequence almost does not help in enhancing the performance of MSE as $$M\rightarrow \infty $$ . Based on this, two pilot contamination reduction methods for the very large MIMO multi-cell TDD system were proposed. One is realized by grouping all the cells into two categories, using orthogonal pilots between these two types of cells or aligning the uplink pilot time slot of the cells in one category with the downlink data time slot of those cells in the neighboring categories. The other is to find the optimal division of pilot sequence length and the set of all users's pilot transmission slots allocation through BSs's coordination. The effectiveness of our proposed methods are verified via both theoretical analysis and numerical results. [ABSTRACT FROM AUTHOR]

In this paper, the closed-form parameterizations to the Pareto boundary for the two-user multiple-input single-output interference channel are studied. Firstly, for the equivalent channel model with each transmitter having only two antennas, the weighted sum-rate maximization (WSRMax) problem is reformulated with newly defined angle variables. Then, a centralized weighted leakage-plus-noise-to-signal ratio minimization (WLNSRMin) algorithm is proposed to find a locally optimal weighted sum-rate point. Each step of the algorithm is solved by evaluating closed-form expressions. A distributed algorithm is also given to avoid the exchange of the channel state information (CSI) between transmitters. Numerical results show that the centralized WLNSRMin algorithm converges to a local optimum of the WSRMax problem after a few iterations and the distributed algorithm achieves a performance very close to that of the centralized algorithm with only local CSI. [ABSTRACT FROM AUTHOR]

Multiple input multiple out (MIMO) cognitive radio offer the spatial degree of freedom that can be used to share the spectrum with less interference via Precoding Technique. Many precoding techniques in the literature assume that the underlying hardware is ideal. In the practical case, hardware adds many impairments at both the transmitter and receiver side. Such hardware impairments degrade the performance of the MIMO system. This impairment introduces additional interference to the primary user in minimum interference precoder of MIMO cognitive radio and spoils the objective of the precoder. This paper analyzes the performance of the cognitive radio with minimum interference MIMO precoding in the presence of hardware impairment. Detecting the presence of hardware impairment and its exact variance is required to mitigate the impairment by prewhitening. In general all prewhitening work, it is assumed that the transmitter knows the presence of impairments and the exact variance of it. This work presents support vector machine (SVM) based hardware impairment detection technique on the real-time acquired data by using national instruments, vector signal generator (VSG) 5673. The VSG is configured in 2 × 2 MIMO setup to acquire the transmitter data without impairment and with injected impairment like DC offset, phase noise, I/Q gain imbalance, quadrature skew and frequency offset. After detecting the presence of hardware impairment by SVM, the variance of the data is calculated using Error Vector Magnitude (EVM) to enable prewhitening. The results show that the detection of hardware impairment can be possible with 100% of accuracy and the prewhitening scheme completely removes the impact of it. [ABSTRACT FROM AUTHOR]

In a multi-input multi-output (MIMO) full-duplex network, where an in-band full-duplex infrastructure node communicates with two half-duplex mobiles supporting simultaneous up- and downlink flows, the inter-mobile interference between the up- and downlink mobiles limits the system performance. We study the impact of leveraging an out-of-band side channel between mobiles in such network under different channel models. For time-invariant channels, we aim to characterize the generalized degrees-of-freedom ( GDoF) of the side-channel-assisted MIMO full-duplex network. For slow-fading channels, we focus on the diversity-multiplexing tradeoff (DMT) of the system with various assumptions as to the availability of channel state information at the transmitter (CSIT). The key to the optimal performance is a vector bin-and-cancel strategy leveraging Han-Kobayashi message splitting, which is shown to achieve the system capacity region to within a constant bit. We quantify how the side channel improve the GDoF and DMT compared to a system without the extra orthogonal spectrum. The insights gained from our analysis reveal (i) the tradeoff between spatial resources from multiple antennas at different nodes and spectral resources of the side channel and (ii) the interplay between the channel uncertainty at the transmitter and use of the side channel. [ABSTRACT FROM AUTHOR]

This paper studies the impact of channel error on the achievable rate of symmetrical K-user multiple-input multiple-output linear interference alignment (IA) networks. The upper and lower bounds of the achievable sum rate are derived analytically with the assumption of orthonormal transmit precoders and receive filters designed from imperfect channel state information (CSI) over both the uncorrelated and correlated channels. For uncorrelated channels, quite tight lower and upper bounds are obtained. The impact of channel error on the degrees of freedom (DoF) and the DoF persistence conditions are also investigated. Results show that the DoF of IA networks persists only if the channel error decreases in an order higher than the signal-to-noise ratio. For correlated channel, the lower and upper bounds for one realization of IA are derived. The derived upper bound can be used to characterize the achievable rate approximately. Simulation results indicate that the achievable rate of IA network is influenced significantly by CSI uncertainty. The obtained analytical bounds provide an intuitive way to show the impact of channel error on the achievable rate and thus can help practical systems deign. [ABSTRACT FROM AUTHOR]

This paper addresses the self-interference (SI) cancellation at baseband for full-duplex MIMO communication systems in consideration of practical transmitter imperfections. In particular, we develop a subspace-based algorithm to jointly estimate the SI and intended channels and the nonlinear distortions. By exploiting the covariance and pseudo-covariance of the received signal, we can increase the dimension of the received signal subspace while keeping the dimension of the signal subspace constant, and hence, the proposed algorithm can be applied to most of full-duplex MIMO configurations with arbitrary numbers of transmit and receive antennas. The channel coefficients are estimated, up to an ambiguity term, without any knowledge of the intended signal. A joint detection and ambiguity identification scheme is proposed. Simulation results show that the proposed algorithm can properly estimate the channel with only one pilot symbol and offers superior SI cancellation performance. [ABSTRACT FROM AUTHOR]

Ina wireless ad hoc network, single-antenna nodes can cooperate in their transmissions to create a virtual multiple-input multiple-output (MIMO) channel for maximizing the spatial multiplexing gain. However, implementing virtual-MIMO transmission can result in overwhelming overhead, such as channel state information (CSI) feedback and local data exchange, as the number of cooperating nodes increases. To suppress this overhead, we apply the principle of virtual-MIMO transmission to CSI feedback and design a novel framework for supporting parallel feedback streams, called virtual-MIMO feedback. Building on this feedback framework, we optimize virtual-MIMO transmission techniques and quantify their throughput gains in the presence of CSI and local-exchange overhead. To be specific, the outage capacities of these virtual-MIMO techniques are analyzed, and the corresponding bandwidth allocation for local data exchange and long-range transmission is optimized in a way to maximize overall spectral efficiency. Finally, the improvement of spectral efficiency in proposed virtual-MIMO feedback and transmission is demonstrated by the simulation results. [ABSTRACT FROM AUTHOR]

The objective of this paper is to use the recently proposed galaxy-based search optimization algorithm to enhance the capacity of a multiple input multiple output (MIMO) system with rectangular arrays at both communication ends (transmitter and receiver). This new optimization tool has been recently introduced and is a metaheuristic technique inspired by the dynamics of galactic arm spirals. It is characterized by its robustness, immunity to local optima trapping, relative fast convergence and ease of implementation. The idea is to extend the results obtained for the one-dimensional array geometry to the two-dimensional case. The purpose is to find out which array geometrical dimensions produce the highest capacity value. Compared to the linear array case, promising capacity values are found using the two-dimensional arrays which suggests their deployment in future MIMO communication systems. [ABSTRACT FROM AUTHOR]

We generally emphasize that the zeroforcing (ZF) technique backed by an appropriate medium access control (MAC) protocol can be used to address the inevitable hidden terminal (HT) problem in multi-user multiple input multiple output (MU-MIMO) wireless local area network (WLAN) settings. However, to address the implementation-specific requirements of MU-MIMO WLANs, such as fairness in client access and throughput of the network, we propose a fairness and a throughput-aware ZF precoding in our design at the physical layer (PHY). This precoding scheme not only solves the HT problem but also meets the fairness and the throughput requirements of MU-MIMO WLANs. Besides, we design a MAC layer protocol, supportive to PHY, which decides transmission opportunities (TXOPs) among access points (APs) based on the available degrees of freedom (DoF). We make a mandatory provision in our design that APs should have a sufficient DoF. This can ensure collision-free transmission whenever APs/transmitters transmit in the HT scenario. Additionally, we design an improved channel sounding process for MU-MIMO WLANs with a less signaling overhead than IEEE802.11ac. We demonstrate the feasibility of our PHY in a USRP2/GNU Radio testbed prototype in the lab settings. It is found that our PHY improves the SNR and effective SNR of the received signal from about 5 to 11 dB in the HT scenario. The performance of our MAC design is checked with simulation studies in a typical six-antenna AP and clients scenario. We observe that our MAC protocol has a slightly higher signaling overhead than traditional ready to send/clear to send (RTS/CTS) due to design constraints; however, the signaling time overheads are reduced by 98.67 μs compared to IEEE802.11ac. Another interesting aspect to highlight is the constant Throughput gain of four to five times that of the traditional RTS/CTS. Our MAC protocol obtains this gain as early as 98.67 μs compared to IEEE802.11ac. [ABSTRACT FROM AUTHOR]

The reliability of on-body communications is a major requirement for many applications. This paper introduces a novel method to enable effective on-body communications, making use of several on-body antennas to create a virtual MIMO system. Strategies for the selection of the best wearable antenna placements based on appropriated metrics, with examples for a 2 × 2 MIMO system, are given. The model includes a statistical description of the antenna-user coupling, the channel variability due to body dynamics, as well as the scattered propagation environment. The channel model assumes that the received signal results from the contribution of one on-body component and of several environment multipath ones. The comparison in system performance between a street and inside an office shows that multipath in large environments is negligible compared to the on-body component (at the selected frequency of 2.45 GHz). The best performance is obtained when the sink (receiver) nodes are on the front and back of the body, and data sensors (transmitters) are on the head, with a relative capacity gain over SISO of roughly 2. [ABSTRACT FROM AUTHOR]

For multiple-input multiple-output cognitive radio systems, we propose an optimal single transmit and receive antenna selection scheme which maximizes the signal-to-interference-and-noise ratio. Considering peak interference power constraint, peak transmit power constraint, and interference from primary transmitter to cognitive receiver, we theoretically derive the exact system outage probability. It is shown that the theoretical results match simulation results. [ABSTRACT FROM AUTHOR]

This paper studies the channel identifiability for Multiple-Input Multiple-Output Space-Time Block Code (MIMO-STBC) systems using the noncircular complex Fast Independent Component Analysis (nc-FastICA) algorithm. In contrast to the previous blind MIMO-STBC channel estimation methods in literature, the method proposed in this paper is more suitable for non-cooperative scenario since it needs less prior knowledge and does not require any modification of the transmitter. The main contribution of the paper consists in the theoretical proof that, although the sources among different antennas of MIMO-STBC systems are not independent, they can be retrieved from the received data by directly using nc-FastICA algorithm in most cases. The conclusion is also demonstrated by simulation. This shows that the classical nc-FastICA algorithm can be applied to a wider range of situations rather than strictly independent sources. [ABSTRACT FROM AUTHOR]

This paper addresses the problem of designing joint optimum precoder and decoder for multiple-input multiple-output communication system. Conventionally, most of the joint precoder and decoder designs are based on the sum power constraint (SPC) at the transmitter and perfect channel state information (CSI). However, in practice, per-antenna power constraint is more realistic as the power at each transmit antenna is limited individually by the linearity of the power amplifier. Further, the estimate of CSI cannot be obtained perfectly by any methods. Under imperfect CSI, the aim is to design jointly optimum precoder and decoder subject to a power constraint that jointly meets both per-antenna and SPCs. The objective function is formulated into an optimization problem that minimizes the mean square error in estimating the transmitted signal. The simulation results show that the proposed scheme has a near-optimum performance under practical constraints. [ABSTRACT FROM AUTHOR]

In this paper, a novel multiple antenna system framework, which combines smart antennas (SA) with multiple-input-multiple-output (MIMO) at the transmitter, is proposed. The downlink capacity of the single-user SA-MIMO wireless systems is investigated. The joint optimization problem corresponding to the capacity is deduced. After that, upper bounds of the capacity are given in general case and in the case of equal power allocation, respectively. Furthermore, in the case of equal power allocation and the same direction of departure from one transmit smart antenna to all antenna arrays at the receiver the closed-form expression of the capacity is obtained. Some numerical results are given to show that smart antennas can bring significant capacity gain for the MIMO systems due to the smart antennas gain, without additional spatial degrees of freedom, especially at high SNR with strong correlation among the MIMO channel links or at low SNR. [ABSTRACT FROM AUTHOR]

Multiple Input Multiple Output (MIMO) systems employ multiple antennas to provide high spectral efficiency and wireless link reliability thanks to multipath diversity and space multiplexing. This technology is now being implemented into wireless standards such as 802.11n, as well as the 4th generation cellular networks. In this paper we present results of an extensive simulation research in which we compare three receiver models for MIMO WLAN 802.11n system. We investigate maximum-likelihood, zero-forcing and Vertical Bell Laboratories Layered Space Time receivers. Performance of these receivers for a range of 802.11n environments, i.e. for several channel models and different number of transmitter and receiver antennas is evaluated. The results of the comparison highlight the benefits of MIMO technology and show to what extent it is possible to improve the MIMO 802.11n system performance increasing the receiver complexity. [ABSTRACT FROM AUTHOR]

Layered Steered Space-Time Codes (LSSTC) is a recently proposed multiple-input multiple-output system that combines the benefits of vertical Bell Labs space-time (VBLAST) scheme, space-time block codes and beamforming. We suggest a new downlink scheme employing LSSTC with asymmetric power allocation, by assuming that the user feeds the BS with the average signal-to-noise ratio per VBLAST layer through the uplink feedback channel. The motivation behind proposing such a system is to enhance the error performance by assigning power to the layers in an optimal manner. We refer to the system proposed as the optimal power allocation LSSTC (OPA-LSSTC). Our analysis is general such that it includes asymmetric layered systems in which each layer may have different number of antennas and also the power can be assigned to layers asymmetrically. [ABSTRACT FROM AUTHOR]

This paper proposes a rotation and scaling based transformation method to simplify the (quasi-)maximum-likelihood (ML) detectors (such as QRD-M, sphere decoding (SD), etc.) for the square quadrature amplitude modulation (S-QAM) modulated multiple-input and multiple-output (MIMO) systems with no performance degradation. The key idea of the simplification is to utilize the symmetric shape of the S-QAM constellation so that after rotation and scaling, real multiplication and addition with certain constellation points in symbol replica generation simply transform into bit shifting or even vanish. As an illustrative example, the QRD-M detector is employed in this work. By using the proposed method, the number of real multiplications of the symbol replica generation required for the QRD-M detector is reduced by 50% and 25% for 4-QAM and 16-QAM, respectively. The numbers of real addition reduction is twice the amount of multiplication. The underlying principle of the proposed rotation and scaling transformation can be straightforwardly extended to amplitude and phase-shift keying (APSK) modulated MIMO systems employing the QRD-M, SD, list sequential sphere decoder (LISS), list sphere decoding (LSD), and the full ML detectors. [ABSTRACT FROM AUTHOR]

In the Alamouti-coded multiple-input multiple-output relay systems, we consider selecting two transmit antennas from all available antennas, at the source and relay respectively, to maximize received signal-to-noise ratio (SNR) at the destination. Since the optimal antenna selection rule is intractable, we propose three suboptimal antenna selection rules (rule one, two and three). While these rules all select two best antennas at the relay to maximize the SNR of relay-destination link. They have different selection criteria at the source. Rule one maximizes the SNR of source-relay link but ignores source-destination link. Oppositely, rule two maximizes the SNR of source-destination link but ignores source-relay link. Rule three considers both links together. We derive the closed-form outage probability expressions of rule one and two, and find an upper bound for the outage probability of rule three. The analysis results show that rule one and two cannot achieve full diversity order, and rule three can. Simulation results verify the analysis results. [ABSTRACT FROM AUTHOR]

Multiple-input multiple-output (MIMO) diversity systems with maximum ratio transmission at the transmitter and selection combining at the receiver (MRT/SC) are presented to obtain the tradeoff between the system performance and receiver complexity. Closed-form expressions for average symbol error rate (SER) in single-user scenario and average capacity in multi-user scenario are derived to get the performance of MIMO MRT/SC systems under independent and identically distributed (i.i.d.) Rayleigh fading. Our study shows that performance of MIMO MRT/SC systems outperforms that of MIMO space-time block coding systems. The analytical results are compared with the simulation results and a good agreement is obtained. [ABSTRACT FROM AUTHOR]

This paper studies the capacity issue of adaptive multiple-input-multiple-output (MIMO) transmissions with channel state information (CSI) feedback over a time-varying channel which is modeled as time-correlated blocks. The CSI is estimated at the receiver and fed back periodically to the transmitter to enable adaptive transmissions. With the objective to maximize the ergodic capacity, a CSI-feedback strategy is proposed based on the optimization of following two parameters. (1) The bit number for the quantization of each CSI and (2) the time interval to refresh the CSI. The first parameter determines the accuracy of the quantization and the latter one deal with the time variation of the channel. The optimization is conducted under a given feedback-capacity constraint i.e., the maximum number of feedback bits per block is fixed in average. A theoretical result is derived and numerical results are presented to show the effectiveness of the proposed strategy. [ABSTRACT FROM AUTHOR]

Typical, large-scale as well as small-scale, in-room office scenarios are analyzed by broadband measurements with a fast MIMO channel sounder. A strong Line-of-Sight (LOS) signal component was always present, and the antenna arrays were arranged in particular ways to construct LOS channel matrices of different channel eigenvalue profiles. In this context, we particularly aim at investigating the practical relevance of high-rank LOS MIMO channel construction approaches in the presence of multipath signals. Statistical results are presented assuming the positions of transmitter and receiver being spatial random variables. To this end, new and appropriate performance measures are introduced in order to separate variations in receive power from alterations of the channel eigenvalue profile (CEP). Contrarily to widespread assumptions, the results show high spectral efficiencies also in deterministic LOS channels, as suboptimal eigenvalue profiles hardly occurred. This result seem to be widely independent from the antenna arrangement. Additionally, we investigate the impact of the transmission bandwidth on the variations of the spectral efficiency, showing broadband systems to be superior. Finally, we end up in several hints on related aspects of system design. [ABSTRACT FROM AUTHOR]