Require Channel State Information Research Articles

Compressive sensing‐based low‐complexity detector for differential spatial modulation

Detection of differential spatial modulation (DSM) needs only the received symbols, unlike spatial modulation that requires channel state information at the receiver. The maximum likelihood (ML)-based DSM receiver, though works well for a small number of transmit antennas, is computationally prohibitive for higher number of antennas. The hard-limiter based ML (HL-ML) receiver has low search complexity in the higher signal-to-noise regions only. The authors propose a low-complexity detection technique using compressive sensing for DSM. The detection involves a two-step process, by first finding the antenna index number and then the M-ary phase-shift keying (MPSK) symbol transmitted from that antenna. After performing a correlation between the past and the present received symbol blocks, the index location of the largest elements of this operation reveals the order of antennas that were activated in a symbol duration. The MPSK symbol is found by a pseudo-inverse operation on the columns of the past and the present received symbol blocks, corresponding to the time index and antenna number, which is same as the above indices. The proposed receiver achieves a substantial reduction in computational complexity close to 63%, when compared to the HL-ML receiver and the performance penalty narrows down with higher order MPSK constellations.

Non-Coherent NOMA With Massive MIMO

By accommodating overlapping transmissions over non-orthogonal resources, non-orthogonal multiple access (NOMA) integrated with massive multiple-input multiple-output (MIMO) can boost spectral efficiency and obtain vast diversity for wireless multiuser systems. However, NOMA requires channel state information (CSI) at the receiver for coherent detection, resulting in unaffordable complexity in the channel estimation as the number of users goes large. Add to that, the introduction of massive MIMO makes the channel estimation even more challenging. In this letter, we propose a blind belief propagation (BP) detection for non-coherent NOMA with massive MIMO, where the transmitter of each user first performs differential modulation on PSK symbols, and then spreads its symbols using low-density spreading (LDS); the receiver of base station (BS) employs differential demodulation and then detects all users’ symbols using a blind BP detection without knowledge of CSI. Simulation results show that the proposed blind BP detection can not only support the overloaded users, but also achieve BER performance very close to that of point-to-point systems.

Performance Enhancement of OFDM System using Hybrid Channel Estimation with Pseudo Pilot

For high spectral efficiency and robustness against intersymbol interference (ISI), orthogonal frequency division multiplexing (OFDM) is the best suited technology for many applications such as digital audio broadcasting (DAB), wireless networks, digital video broadcasting (DVB) and LAN. For efficient recovery of the original transmitted signal we require the coherent demodulator as the frequency selective fading channels affects the transmitted signal in OFDM. At the receiver end for coherent demodulation we require channel state information (CSI), which is done by channel estimation. To find the channel characteristics which varies with time and frequency, a reference signal is transmitted with payload signal know as pilot or training sequence and technique or process is known as channel estimation. The use of pilots in the OFDM system leads to pilots overhead. So we propose a new technique which will reduces the transmission delay, reduce pilot overhead, increases transmission rate and improves the BER performance without any computational complexity, which is implemented using the Hybrid algorithm for channel based OFDM system. In this proposed technique, for the channel estimation in OFDM system over AWGN fading channel pseudo-pilots are used. At the transmitter end, pseudo-pilots are employed to breed bank of pseudo random symbol (PRS). In this OFDM system with pseudo-pilot the channel estimation is done by the Hybrid (LS + RLS) estimation approach to recover the original transmitted information. The performance of the proposed techniques and the weighted scheme are compared and verified using computerized simulation carried out using Matrix Laboratory (MATLAB) software.

Green Secure Communication Range-Angle Focusing Quadrature Spatial Modulation Using Frequency Modulated Diverse Retrodirective Array for mmWave Wireless Communications

Quadrature spatial modulation (QSM) using frequency modulated diverse retrospective array (FMD-RDA) is put forward to achieve green transmission paradigm shift from phased-array-based arrangement. Up to date, the QSM techniques have employed phased-array, but only angular focusing direction is possible without range focusing direction. On the other hand, millimeter-wave (mmWave) scheme is suggested as an alternative approach for fifth-generation because of large bandwidth spectrum. Therefore, this paper studies green secure communication range-angle focusing QSM FMD-RDA in mmWave wireless communication. In FMD-RDA, a small frequency increment is included across the RDA elements to decouple range-angle focusing. More importantly, an attractive advantage of using FMD-RDA is the automatic self tracking feature which alleviate transmitter/receiver's channel state information (CSI) requirement. To ensure secure transmission, we exploit physical layer security to degrade the channel quality of the eavesdropper. Furthermore, low complexity greedy detector is devised to retrieved the information bits at the receiver. We also derived pair-wise error probability, and analyze secrecy sum rate and energy transfer capability. The reported simulation results demonstrate that the proposed scheme is effective in improving the spectral efficiency with low complexity and no CSI requirement.

Stochastic Cooperative Communications Using a Geometrical Probability Approach for Wireless Networks

In cooperative communications, signals are relayed to increase transmission range and user throughput. However, selection and coordination of relay stations (RSs) usually require channel state information (CSI) and control signaling, resulting in high system overhead, latency, and complexity. In this paper, we propose a cooperation scheme for wireless networks, called stochastic cooperative communications based on geometrical probability (SCCGP). SCCGP has a low operational overhead and provides link capacity guarantee statistically. For cellular networks, a base station selects randomly a number of RSs in a hexagonal cell that have a fixed amplification factor, and the target user employs selective combining on the signal copies from multiple relaying paths. For ad hoc networks, the RSs are selected randomly in the circular area between a pair of communicating stations. Using a geometrical probability approach and the Cassini oval model, we derived the distribution functions of the cascaded path loss over a random two-hop relaying path, average received signal-to-noise ratio, and link capacity over multiple relaying paths. Furthermore, we transform the distribution functions into closed forms by using Taylor expansions. The mathematical proof and numerical results have shown that the closed-form distribution functions are valid and can be used to analyze the capacity of SCCGP and determine the minimum number of random RSs needed to satisfy an outage requirement. The SCCGP scheme can improve the user capacity considerably without the need of much coordination and CSI among the RSs. The derived distribution functions of the cascaded path loss over random two-hop paths can also be used in the interference management in multi-source-destination systems and other problems.

Massive MIMO multi-pair two-way half-duplex AF FDD relaying: channel estimation

We consider two-way amplify-and-forward FDD massive multi-input-multi-output (MIMO) relaying system, where multiple half-duplex (HD) user-pairs exchange information via a shared HD relay equipped with massive MIMO. To design and study the performance of these systems, we require channel state information in uplink as well as in downlink. For the uplink of the system model, we use conventional low-complexity MMSE estimator for the channel estimation, wherein the number of orthogonal pilots required for uplink channel estimation are of the order of the number of users. However, in the massive MIMO relay systems, the downlink channel estimation becomes challenging, because of increased pilot overhead in proportion to the number of antennas at the relay and employing conventional channel estimation approaches will result in poor spectral efficiency. The massive MIMO channels exhibits sparse structure in the angular domain, due to limited scattering environment. We exploit this channel sparsity to reduce the pilot overhead by performing sparse Bayesian learning-based downlink channel estimation. Furthermore, practical massive MIMO systems are built with low-cost hardware components which makes the massive MIMO system prone to hardware impairments like phase and quantization errors. In this paper, we numerically analyze the effect of hardware impairments on the two-way multi-pair half-duplex massive MIMO relay systems.

Sub-System SVD Hybrid Beamforming Design for Millimeter Wave Multi-Carrier Systems

In this paper, the hybrid beamforming design for multiple-input multiple-output orthogonal frequency-division multiplexing systems is studied over the indoor millimeter wave (mm-wave) channels. Under practical hybrid beamforming constraints for multi-carrier systems and the study of sub-systems, we propose the sub-system SVD (SS) hybrid beamforming design. To alleviate the complexity problem of channel estimation, reduction of the amount of the required channel state information (CSI) is also studied based on the statistical properties of indoor mm-wave channels. The SS hybrid beamforming algorithm is then extended to the limited feedback SS (LSS) scheme in which the transmit beamformers are designed based on limited information fed back from the receiver. A fast codeword selection algorithm is also developed to reduce the search complexity of the LSS algorithm. The simulation results show that our SS algorithm achieves the performance level of traditional full-digital beamforming with low complexity and the LSS algorithm has better performance and lower complexity than the previous algorithm, even if the amount of CSI is greatly reduced.

Orthogonally Precoded Massive MIMO for High Mobility Scenarios

Massive multiple-input multiple-output (MIMO) systems are of high interest for ultra-reliable low-latency communication (URLLC) links. They provide channel hardening, i.e. reduced channel variations, due to the large number of transmit antennas which exploit spatial diversity by beam-forming. Massive MIMO requires channel state information (CSI) on the base station side. For time-varying vehicular communication channels the CSI acquired during the uplink phase will be outdated for the following downlink phase, leading to reduced spatial channel hardening. We investigate a combination of massive MIMO with general orthogonal precoding (OP) to compensate this effect. OP uses two-dimensional precoding sequences in the time-frequency domain and provides channel hardening by exploiting time- and frequency diversity. We show that the combination of massive MIMO and OP is beneficial for time-varying communication channels. While the spatial channel hardening of massive MIMO decreases, the time-frequency channel hardening of OP increases with larger time-variance of the communication channel. An iterative receiver algorithm for massive MIMO with OP as well as a detailed analysis of the channel hardening effect is presented. We demonstrate a BER reduction by more than one order of magnitude for a velocity of 50 km/h = 16.6 m/s using the orthogonal frequency division multiplexing (OFDM) based 5G new radio (NR) physical layer.

Double-Sided Massive MIMO Transceivers for mmWave Communications

We propose practical transceiver structures for double-sided massive multiple-input-multiple-output (MIMO) systems. Unlike standard massive MIMO, both transmit and receive sides are equipped with high-dimensional antenna arrays. We leverage the multi-layer filtering architecture and propose novel layered transceiver schemes with practical channel state information requirements to simplify the complexity of our double-sided massive MIMO system. We conduct a comprehensive simulation campaign to investigate the performance of the proposed transceivers under different channel propagation conditions and to identify the most suitable strategy. Our results show that the covariance matrix eigenfilter design at the outer transceiver layer combined with maximum eigenmode transmission precoding/minimum mean square error combining at the inner transceiver layer yields the best achievable sum rate performance for different propagation conditions and multi-user interference levels.

Neural Network Detection of Data Sequences in Communication Systems

We consider detection based on deep learning, and show it is possible to train detectors that perform well without any knowledge of the underlying channel models. Moreover, when the channel model is known, we demonstrate that it is possible to train detectors that do not require channel state information (CSI). In particular, a technique we call a sliding bidirectional recurrent neural network (SBRNN) is proposed for detection where, after training, the detector estimates the data in real-time as the signal stream arrives at the receiver. We evaluate this algorithm, as well as other neural network (NN) architectures, using the Poisson channel model, which is applicable to both optical and molecular communication systems. In addition, we also evaluate the performance of this detection method applied to data sent over a molecular communication platform, where the channel model is difficult to model analytically. We show that SBRNN is computationally efficient, and can perform detection under various channel conditions without knowing the underlying channel model. We also demonstrate that the bit error rate (BER) performance of the proposed SBRNN detector is better than that of a Viterbi detector with imperfect CSI as well as that of other NN detectors that have been previously proposed. Finally, we show that the SBRNN can perform well in rapidly changing channels, where the coherence time is on the order of a single symbol duration.

An Efficient Transmit Power Control Strategy for Underlay Spectrum Sharing Networks With Spatially Random Primary Users

With the ever-increasing spectrum requirements for transmitting explosively growing mobile data, spectrum-efficient solutions need to be integrated into future mobile networks. Spectrum sharing enables the primary system to share licensed spectrum with the secondary system. Thus, it is conceived as an appealing solution for improving spectrum usage to eliminate the spectrum supply-demand gap. In this paper, we develop an efficient transmit power control strategy for underlay spectrum sharing networks with spatially Poisson-distributed primary users. A distinguishing feature of the proposed strategy is that it only requires channel state information and location information of a few primary users close to the secondary transmitter, rather than those for all primary users. Furthermore, we evaluate the outage performance of the secondary system and the interference situation of the primary system under this kind of transmit power control strategy. Numerical results demonstrate that the proposed transmit power control strategy can achieve near-optimal outage performance compared to the perfect power control strategy, while reducing the control complexity and the feedback burden significantly at the same time.

Over-the-Air Computation for IoT Networks: Computing Multiple Functions With Antenna Arrays

Over-the-air computation combines communication and computation efficiently by utilizing the superposition property of wireless channels, when Internet of Things (IoT) networks focus more on the computed functions than the individual messages. In this paper, we study the computation of multiple linear functions of Gaussian sources over-the-air using antenna arrays at both the IoT devices and the IoT access point (AP). The key challenges in this paper are the intranode interference of multiple functions, the nonuniform fading between different IoT devices and the massive channel state information (CSI) required at the IoT AP. We propose a novel transmitter design at the IoT devices with zero-forcing beamforming to cancel the intranode interference and uniform-forcing power control to compensate the nonuniform fading. In order to avoid massive CSI requirement, receive antenna selection is adopted at the IoT AP and a corresponding signaling procedure is proposed utilizing the “OR” property of the wireless channel. The performance of the proposed transceiver design is analyzed. The closed-form expression for the mean squared function error (MSFE) outage is derived. Due to the complexity of the expression, an asymptotic analysis of the MSFE outage is further provided to demonstrate the diversity order in terms of the transmit power constraint and the number of IoT devices. Simulation results are presented to show the performance of the proposed design.

Joint Interference Suppression and Multiuser Detection Schemes for Multi-Cell Wireless Relay Communications: A Three-Cell Case

To cope with the interference problem in three-cell wireless relay systems, this paper proposes two schemes that perform interference suppression and multiuser detection. The proposed schemes do not require channel state information (CSI) feedback, and their computational complexity is much less than that of the maximum likelihood detection (MLD), which is considered in the optimal detection scheme. Of the two proposed schemes, the minimum mean-square error (MMSE)-based scheme estimates the weight coefficients for the interference suppression under the MMSE criterion. The other proposed scheme, the recursive least squares (RLS)-based scheme, directly estimates the weight coefficients using the RLS algorithm. The RLS-based scheme only requires two preamble sequences, whereas both the MMSE-based schemes and the MLD require the knowledge of all the three preamble sequences. Therefore, the RLS-based scheme can be considered more feasible. Moreover, computer simulations results and theoretical average bit error rate (BER) upper bounds of orthogonal frequency-division multiplexing transmission under three-cell and frequency-selective fading conditions were provided. It was observed that simulation results are consistent with theoretical upper bounds and that the RLS-based scheme achieves a BER performance that is identical to that of the MMSE-based scheme with perfect CSI while requiring much less computational complexity than the MLD.

Noncoherent IR-UWB Receiver Using Massive Antenna Arrays for Wireless Sensor Networks

Noncoherent impulse radio ultrawideband (UWB) receivers do not require channel state information and are also robust against pulse shape distortions. However, their performance is suboptimal, especially at low signal-to-noise ratios. In this article, we propose simple noncoherent UWB receivers for wireless sensor network applications using massive antenna arrays. Two receivers are proposed: based on instantaneous received UWB signal energy and based on weighted instantaneous received UWB signal energy. The proposed receivers use the law of large numbers resulting from the massive receiver arrays and utilize the large degrees of freedom available in a UWB multipath channel. Furthermore, the proposed receivers do not require training symbols for the estimation of decision threshold. Both these receivers outperform the existing noncoherent receivers as verified using simulation results on the standardized IEEE 802.15.4a UWB multipath channel.

Performance Evaluation of a Selection Combining Scheme for the Hybrid FSO/RF System

In this paper, an alternative implementation for the hybrid free-space optical (FSO)/radio frequency (RF) wireless communication system without requiring channel state information is presented. The proposed hybrid system transmits the same data with the same data rate over both links simultaneously. The well-known diversity selection combining scheme is implemented to combine the received signals in the electrical domain. New closed-form expressions for the average bit error rate and outage probability are derived in order to trace the system's performance over various channel turbulence conditions. The analysis of the proposed system's performance clearly indicates that the proposed system is advantageous as it exploits the complementary properties of the FSO and RF channels, even in strong turbulence conditions. In addition, the performance comparison demonstrates the proposed system's superior performance compared with the FSO-only system.

Differential spatial modulation for high-rate transmission systems

This paper introduces a new differential spatial modulation (DSM) scheme which subsumes both the previously introduced DSM and high-rate spatial modulation (HR-SM) for wireless multiple input multiple output (MIMO) transmission. By combining the codeword design method of the HR-SM scheme with the encoding method of the DSM scheme, we develop a high-rate differential spatial modulation (HR-DSM) scheme equipped with an arbitrary number of transmit antennas that requires channel state information (CSI) neither at the transmitter nor at the receiver. The proposed approach can be applied to any equal energy signal constellations. The bit error rate (BER) performance of the proposed HR-DSM schemes is evaluated by using both theoretical upper bound and computer simulations. It is shown that for the same spectral efficiency and antenna configuration, the proposed HR-DSM outperforms the DSM in terms of bit error rate (BER) performance.

An acquisition scheme for communications in multi-antenna sensor networks with low signal to noise ratio

Recent results show that multiple antenna communications can improve the energy efficiency of wireless communications. These techniques are thus attractive for use in wireless sensor networks. In particular, diversity techniques can be used to improve the acquisition of wireless links, especially for low signal-to-noise ratio (SNR) situations. This paper presents an acquisition scheme well suited for wireless sensor networks such as low-power wide-area networks (LPWAN) with multiple antenna sensor nodes. The scheme exploits a differentially encoded preamble and receive diversity in order to detect signals at very low SNR without requiring channel state information. We show that it achieves a better trade-off between the probability of acquisition false alarm and failed acquisition than single-antenna communications. Therefore, it enables networks with larger node separation at given transmission power, such as in LPWANs. The scheme's performance is thoroughly analysed theoretically and verified by simulations.

Design of a Capacity-Approaching Chaos-Based Multiaccess Transmission System

As an enhanced version of Walsh-code-based multiaccess differential chaos shift keying (DCSK-WC), the differentially DCSK-WC (DDCSK-WC) benefits from better error performance and stronger robustness against inter-symbol interference in multipath fading channels. In this paper, the Bahl–Cocke–Jelinek–Raviv (BCJR) decoding algorithm is applied in the detection of DDCSK-WC to form DDCSK-WC-BCJR. Theoretical analyses and simulation results demonstrate that the BCJR detector achieves a significant performance gain with respect to the conventional generalized-maximum-likelihood detector, while retaining the hardware complexity almost unchanged. To further improve the performance, protograph-based low-density-parity-check channel codes are incorporated into the DDCSK-WC-BCJR system so as to construct a serial concatenated coding scheme. However, the capacity-approaching protograph code in additive white Gaussian noise (AWGN) channels performs poorly in the DDCSK-WC-BCJR system over multipath fading channels. To tackle this problem, a new protograph code is designed with the help of a modified extrinsic information transfer analysis. The proposed code has decoding thresholds gap within 1.0 dB way from to the system capacity limits. Besides, the performance superiority of the protograph-coded DDCSK-WC-BCJR architecture is illustrated over a practical UWB channel. More importantly, the proposed scheme does not require channel state information as in uncoded-DCSK schemes, which makes it extremely promising for low-cost and low-complexity wireless communication applications.

Performance Evaluation of Downlink Multi-Beam Massive MIMO with Simple Transmission Scheme at Both Base and Terminal Stations

Multi-beam massive multiple-input–multiple-output (MIMO) configurations that utilize high-power beam selection in the analog parts and blind algorithms such as the constant modulus algorithm (CMA), which do not require channel state information (CSI), in the digital parts, have been proposed in the literature to improve the transmission rates and efficiency. In this paper, we evaluate the transmission performance in the downlink, with simple control at the base station (BS) and user terminal (UTs), for massive MIMO transmissions. Through computer simulations, it is shown that the analog multi-beam selection at the BS and the application of CMA at the UT with two antennas can effectively realize transmissions with high-order modulation schemes. In addition, the weight update switching by the CMA is proposed in order to obtain fast and stable performance with a realistic data size.

A novel scheme inspired by the compute-and-forward relaying strategy for the multiple access relay channel

This paper proposes a novel scheme for the slow block fading Gaussian multiple access relay channel inspired by the compute-and-forward (CoF) relaying strategy. The CoF relaying strategy exploits interference to obtain significantly higher rates between users in a network by decoding linear functions of the transmitted messages. Unlike other approaches in the literature, our approach is valid for any number of transmitters and, most importantly, it only requires channel state information at the receiver side, while it still attains similar or higher rates than the other approaches found in the literature.