Receiver Channel State Information Research Articles

Max-Min Fairness Precoder Design for Rate-Splitting Multiple Access: Impact of Imperfect Channel Knowledge

Rate-splitting multiple access (RSMA) is a key enabling technology for beyond 5G networks due to its robustness against imperfect channel knowledge. In this paper, we consider both the imperfect channel state information (CSI) at the receiver (CSIR) and imperfect CSI at the transmitter (CSIT) and propose a max-min fairness optimization framework relying on RSMA to guarantee each user's minimum level of quality of service (QoS). First, we formulate the max-min fairness optimization problem that has non-convexity. To transform the non-convex problem into a convex problem, we apply the semi-definite relaxation (SDR) and convex-concave procedure (CCP) to the proposed algorithm. From simulation results, we confirm that RSMA is still a robust scheme over conventional multiple access schemes for both imperfect CSIT and CSIR.

Deep Learning-Based Authentication Framework for Secure Terrestrial Communications in Next Generation Heterogeneous Networks

Smart Grid (SG) network is growing rapidly to improve the efficiency and reliability of the power supply. It will connect billions of devices to the internet in the near future. This increase in the number of internet-connected devices has led to an exponential increase in the market size of smart meters. These smart meters and devices will generate lakhs of gigabytes of data in upcoming years. To handle this massive amount of data flow, the Information and Communication Technology (ICT) of SG will experience huge advancements in terms of 5G and 6G wireless networks. These networks will provide higher data rates by utilizing the huge bandwidth spectrum of heterogeneous networks (HetNet). As the massive amount of data will be transmitted to various components of the smart grid using the internet, an open channel. Therefore, in addition to the need for high bandwidth and low latency, HetNet security has also become a prime concern. This paper presents an efficient approach to authenticate the smart devices in SG environment by using the channel state information (CSI) of the wireless links. Firstly, Low-Density Parity-Check (LDPC) codes are used to maintain the confidentiality and reliability of data transmission in the Advanced Metering Infrastructure (AMI) of SG. Then, a Convolution Neural Network (CNN)-based authentication framework is proposed to enhance the physical layer security (PLS) of terrestrial communications in next generation SG Hetnets. Further, the proposed framework is evaluated using received Channel State Information (CSI) values from smart meters placed at different locations, while also taking the scenario of active eavesdroppers into account. Experimental analysis reveals that the proposed CNN based authentication achieves 30.76 percent better authentication rate than existing DNN based authentication scheme. Further, the LDPC coded data transmission scheme reduces the bit error rate (BER) by 20 percent as compared to uncoded data transmission.

Low-Complexity LMMSE Receiver Design for Practical-Pulse-Shaped MIMO-OTFS Systems

Orthogonal time frequency space modulation (OTFS) scheme establishes reliable communication in a rapidly time-varying wireless channel with a high Doppler spread. We design a low-complexity linear minimum mean squared error (LMMSE) receiver for practical-pulse-shaped multiple-input multiple-output (MIMO)-OTFS systems. The proposed receiver exploits the inherent channel sparsity and the channel-agnostic structure of matrices involved in the LMMSE receiver, and has only a log-linear complexity. It provides exactly the same solution, and hence the same bit error rate (BER), as that of the conventional LMMSE receiver with a cubic order of complexity. We also derive, by using the Taylor series expansion and the results from random matrix theory, a tight closed-form approximation for the post-processing signal-to-noise-plus-interference ratio (SINR) expression of the proposed receiver. This expression is derived by assuming imperfect receive channel state information. We show using extensive numerical investigations that the derived SINR expression, when averaged over multiple channel realizations, accurately characterizes the BER of a MIMO-OTFS system.

Generalized Nearest Neighbor Decoding

It is well known that for Gaussian channels, a nearest neighbor decoding rule, which seeks the minimum Euclidean distance between a codeword and the received channel output vector, is the maximum likelihood solution and hence capacity-achieving. Nearest neighbor decoding remains a convenient and yet mismatched solution for general channels, and the key message of this paper is that the performance of nearest neighbor decoding can be improved by generalizing its decoding metric to incorporate channel state dependent output processing and codeword scaling. Using generalized mutual information, which is a lower bound to the mismatched capacity under independent and identically distributed codebook ensemble, as the performance measure, this paper establishes the optimal generalized nearest neighbor decoding rule, under Gaussian channel input. Several restricted forms of the generalized nearest neighbor decoding rule are also derived and compared with existing solutions. The results are illustrated through several case studies for fading channels with imperfect receiver channel state information and for channels with quantization effects.

Analog MIMO Communication for One-Shot Distributed Principal Component Analysis

A fundamental algorithm for data analytics at the edge of wireless networks is distributed principal component analysis (DPCA), which finds the most important information embedded in a distributed high-dimensional dataset by distributed computation of a reduced-dimension data subspace, called principal components (PCs). In this paper, to support one-shot DPCA in wireless systems, we propose a framework of analog MIMO transmission featuring the uncoded analog transmission of local PCs for estimating the global PCs. To cope with channel distortion and noise, two maximum-likelihood (global) PC estimators are presented corresponding to the cases with and without receive channel state information (CSI). The first design, termed coherent PC estimator, is derived by solving a Procrustes problem and reveals the form of regularized channel inversion where the regulation attempts to alleviate the effects of both receiver noise and data noise. The second one, termed blind PC estimator, is designed based on the subspace channel-rotation-invariance property and computes a centroid of received local PCs on a Grassmann manifold. Using the manifold-perturbation theory, tight bounds on the mean square subspace distance (MSSD) of both estimators are derived for performance evaluation. The results reveal simple scaling laws of MSSD concerning device population, data and channel signal-to-noise ratios (SNRs), and array sizes. More importantly, both estimators are found to have identical scaling laws, suggesting the dispensability of CSI to accelerate DPCA. Simulation results validate the derived results and demonstrate the promising latency performance of the proposed analog MIMO

Optimal Beamforming for Secure Transmit in Practical Wireless Networks

In real communication systems, secure and low-energy transmit scheme is very important. So far, most of schemes focus on secure transmit in special scenarios. In this paper, our goal is to propose a secure protocol in wireless networks involved various factors including artificial noise (AN), the imperfect receiver and imperfect channel state information (CSI) of eavesdropper, weight of beamforming (BF) vector, cooperative jammers (CJ), multiple receivers, and multiple eavesdroppers, and the analysis shows that the protocol can reduce the transmission power, and at the same time the safe reachability rate is greater than our pre-defined value, and the analysis results are in good agreement with the simulation results. In this letter, the minimal transmit power is modeled as a non-convexity optimization that is general difficult. Our method is to transform it into a two-level non-convex problem. The outer is a univariate optimization that can be solved by the golden search algorithm. The inner is a convex optimization solved by using the CVX. The solutions are further used to improve the confidentiality rate of the system, and reduce the transmit power of the system and resource consumption in terms of the imperfect CSI. Simulations show the efficiency and robustness of the proposed protocol.

Low-Complexity ZF/MMSE MIMO-OTFS Receivers for High-Speed Vehicular Communication

Orthogonal time-frequency space (OTFS) scheme, which transforms a time and frequency selective channel into an almost non-selective channel in the delay-Doppler domain, establishes reliable wireless communication for high-speed moving devices. This work designs and analyzes low-complexity zero-forcing (LZ) and minimum mean square error (LM) receivers for multiple-input multiple-output (MIMO)-OTFS systems with perfect and imperfect receive channel state information (CSI). The proposed receivers provide exactly the same solution as that of their conventional counterparts, and reduce the complexity by exploiting the doubly-circulant nature of the MIMO-OTFS channel matrix, the block-wise inverse, and <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Schur</i> complement. We also derive, by exploiting the Taylor expansion and results from random matrix theory, a tight approximation of the post-processing signal-to-noise-plus-interference-ratio (SINR) expressions in closed-form for both LZ and LM receivers. We show that the derived SINR expressions, when averaged over multiple channel realizations, accurately characterize their respective bit error rate (BER) with both perfect and imperfect receive CSI. We numerically show the lower BER and lower complexity of the proposed designs over state-of-the-art exiting solutions.

Comments and Corrections to “Capacity of Multiple-Antenna Systems With Both Receiver and Transmitter Channel State Information”

The correspondence cited in the above article derived ergodic capacity of the coherent multiple-input multiple-output (MIMO) channel in independent and identically distributed (IID) Rayleigh fading. While the theoretical results are correct, several plots in the paper are incorrect. In this correspondence, we correct the plots. More importantly, the corrected plots present an interesting and compelling contrast between performances of the coherent MIMO systems with and without channel state information at the transmitter; whereas this view is somewhat limited in the above article because of flaws in the capacity curves.

Performance Analysis of Quantized Uplink Massive MIMO-OFDM With Oversampling Under Adjacent Channel Interference

Massive multiple-input multiple-output (MIMO) systems have attracted much attention lately due to the many advantages they provide over single-antenna systems. Owing to the many antennas, low-cost implementation and low power consumption per antenna are desired. To that end, massive MIMO structures with low-resolution analog-to-digital converters (ADC) have been investigated in many studies. However, the effect of a strong interferer in the adjacent band on quantized massive MIMO systems have not been examined yet. In this study, we analyze the performance of uplink massive MIMO with low-resolution ADCs under frequency selective fading with orthogonal frequency division multiplexing in the perfect and imperfect receiver channel state information cases. We derive analytical expressions for the bit error rate and ergodic capacity. We show that the interfering band can be suppressed by increasing the number of antennas or the oversampling rate when a zero-forcing receiver is employed.

SE Analysis for Mixed-ADC Massive MIMO Uplink With ZF Receiver and Imperfect CSI

This letter is on the multi-user massive multi-input multi-output (MIMO) uplink with the mixed analog-to-digital converter (ADC) architecture and the zero-forcing (ZF) receiver at the base station (BS). Under imperfect channel state information (CSI), a closed-form approximation of the spectral efficiency (SE) is derived for a general resolution profile. Further, simplified SE results are provided for two common asymptotic massive MIMO scenarios. In the SE analysis, to overcome the difficulty induced by the mixed-ADC structure, new techniques are developed in calculating the average noise powers caused by the CSI error and the quantization.

Robust Secure Beamforming for SWIPT-Aided Relay Systems With Full-Duplex Receiver and Imperfect CSI

This paper investigates an energy-constrained relay-assisted secure communication system in the presence of a legitimate source-destination pair and a passive eavesdropper with imperfect channel state information (CSI). The energy-constrained relay exploits a power splitting (PS) protocol to simultaneously harvest energy and decode information from the received signal from the source, and then forwards the confidential signal to the full-duplex (FD) destination while it simultaneously transmits artificial noise (AN) to confuse the passive eavesdropper. This robust beamforming design is developed by maximizing the secrecy rate under the constraints of energy harvesting (EH) requirement at the relay and AN transmit power at the destination. Specifically, we formulate the joint relay beamforming and PS ratio as well as the AN power optimization as a non-convex quadratically-constrained problem. In order to circumvent this non-convexity issue, we decompose the original problem into three subproblems which can be determined by the proposed semidefinite relaxation (SDR) and successive convex optimization methods. Furthermore, we derive closed-form expressions for the optimal solutions of each subproblem. Finally, the original non-convex problem can be solved through a convergence guaranteed iterative algorithm. Simulation results are provided to demonstrate the effectiveness and superior performance of the proposed robust design compared with the benchmark schemes.

Probability of Error in MMSE Detection For MIMO-FBMC-OQAM Systems

This work calculates closed-form symbol error rate (SER) expression for minimum mean square error (MMSE) detection in low-frequency selective multiple-input multiple-output (MIMO) filter bank multicarrier (FBMC) systems with offset quadrature amplitude modulation (OQAM). To achieve this aim, we first derive, by assuming perfect receive channel state information, the probability distribution function (PDF) of the post-processing signal-to-noise-plus-interference-ratio for MMSE combining in small MIMO-FBMC-OQAM systems. The PDF is then used to derive the closed-form SER expression. We show that the performance of the derived SER expression matches with its numerical counterpart.

SER Analysis of MMSE Combining For MIMO FBMC-OQAM Systems With Imperfect CSI

We derive post-processing signal-to-noise-plus-interference-ratio (PP-SINR) for minimum mean square error (MMSE) combining in multiple-input multiple-output (MIMO) filter bank multi-carrier (FBMC) systems based on offset quadrature amplitude modulation (OQAM). We show that the PP-SNR, derived by assuming imperfect receive channel state information, accurately characterizes the symbol error rate (SER) of MMSE combining in MIMO FBMC-OQAM systems. We numerically demonstrate the tightness of both PP-SINR and SER expressions.

Achieving Spatial Scalability for Coded Caching via Coded Multipoint Multicasting

The coded caching scheme proposed by Maddah-Ali and Niesen (MAN) critically hinges on the ability of the system to deliver a common coded multicast message from a server to all users in the system at a fixed rate, independent of the number of users. In order to apply this paradigm to a spatially distributed wireless network, it is important to make sure that such a common multicast rate does not vanish, as the number of users in the network and/or the network area increase. This paper starts from a variant of the MAN scheme successively proposed for the so-called combination network , where the multicast message is further encoded by a maximum distance separable (MDS) code, and the MDS-coded blocks are sent to multiple spatially distributed single-antenna edge nodes (ENs), transmitting at a fixed rate with no channel state information. The users have multiple antennas. They obtain receiver channel state information from the standard downlink pilots and can select to decode a desired number of EN transmissions while either nulling or treating as noise the others. The system is reminiscent of the so-called evolved Multimedia Broadcast Multicast Service , since the fundamental underlying transmission mechanism is multipoint multicasting , where each user can independently (in a user-centric manner) decide which EN to decode, without any explicit association of users with ENs. We study the performance of the proposed system when users and ENs are distributed according to homogeneous Poisson point processes in the plane, and the propagation is affected by Rayleigh fading and distance-dependent pathloss. Our analysis allows the optimization of the PHY parameters (PHY coding rate at the ENs and MDS coding rate) for given MAN scheme parameters. The proposed scheme achieves full spatial scalability in the following sense: for an extended network with arbitrary constant ratio of users per EN and area $A = O(N_{\mathrm{ E}})$ , where $N_{\mathrm{ E}}$ denotes the number of ENs, the system achieves a per-user delivery rate that does not vanish as $N_{\mathrm{ E}}\rightarrow \infty $ .

Interleaving Channel Estimation and Limited Feedback for Point-to-Point Systems With a Large Number of Transmit Antennas

We introduce and investigate the opportunities of multi-antenna communication schemes whose training and feedback stages are interleaved and mutually interacting. Specifically, unlike the traditional schemes, where the transmitter first trains all of its antennas at once and then receives a single feedback message, we consider a scenario, where the transmitter instead trains its antennas one by one and receives feedback information immediately after training each one of its antennas. The feedback message may ask the transmitter to train another antenna; or, it may terminate the feedback/training phase and provide the quantized codeword (e.g., a beamforming vector) to be utilized for data transmission. As a specific application, we consider a multiple-input single-output system with $t$ transmit antennas, a short-term power constraint $P$ , and target data rate $\rho $ . We show that for any $t$ , the same outage probability as a system with perfect transmitter and receiver channel state information can be achieved with a feedback rate of $R_{1}$ bits per channel state and via training $R_{2}$ transmit antennas on average, where $R_{1}$ and $R_{2}$ are independent of t , and depend only on $\rho $ and $P$ . In addition, we design variable-rate quantizers for channel coefficients to further minimize the feedback rate of our scheme.

WiStep

Inspired by the emerging WiFi-based applications, in this paper, we leverage ubiquitous WiFi signals and propose a device-free step counting system, called WiStep. Based on the multipath propagation model, when a person is walking, her torso and limbs move at different speeds, which modulates wireless signals to the propagation paths with different lengths and thus introduces different frequency components into the received Channel State Information (CSI). To count walking steps, we first utilize time-frequency analysis techniques to segment and recognize the walking movement, and then dynamically select the sensitive subcarriers with largest amplitude variances from multiple CSI streams. Wavelet decomposition is applied to extract the detail coefficients corresponding to the frequencies induced by feet or legs, and compress the data so as to improve computing speed. Short-time energy of the coefficients is then calculated as the metric for step counting. Finally, we combine the results derived from the selected subcarriers to produce a reliable step count estimation. In contrast to counting steps based on the torso frequency analysis, WiStep can count the steps of in-place walking even when the person's torso speed is null. We implement WiStep on commodity WiFi devices in two different indoor scenarios, and various influence factors are taken into consideration when evaluating the performance of WiStep. The experimental results demonstrate that WiStep can realize overall step counting accuracies of 90.2% and 87.59% respectively in these two scenarios, and it is resilient to the change of scenarios.

A Near BER-Optimal Decoding Algorithm for Convolutionally Coded Relay Channels With the Decode-and-Forward Protocol

Relay-assisted communication has been shown to be an effective technique to improve the reliability and throughput of real-world wireless communication networks. It enables single-antenna users to form a virtual antenna array without installing multiple antennas at the transmitter or the receiver. This paper re-examines the decoding problem in the convolutionally coded relay channel with the classical decode-and-forward protocol. By tackling the challenge of modeling the error propagation effect at the relay, a near BER-optimal decoding (NBOD) algorithm at the destination is derived, assuming the availability of perfect receiver channel state information. Its decoding complexity is linear in the information block length, while the exact BER-optimal decoding algorithm with a sub-exponential complexity is still unknown. The major approximation involved in the derivation of the NBOD algorithm is the pairwise error probability approximation that causes a practically insignificant degradation from the optimal BER performance. Our simulation result confirms that the proposed NBOD algorithm can perform close to the maximum likelihood performance bound on BER in the three-node one-way relay channel scenario. In addition, we have further extended the proposed algorithm for more general single-source single-destination decode-and-forward-based relay networks. Simulation results further verify that the proposed NBOD algorithm can outperform existing decoding algorithms based on maximal-ratio combining and selective decode-and-forward in various relay channel scenarios at the cost of higher complexity.

Cutset Bounds on the Capacity of MIMO Relay Channels

We analyze the ergodic capacity of multiple-input multiple-output (MIMO) Rayleigh-fading relay channels. We first derive the probability density function of a sum of independent complex central Wishart matrices—called the central hyper-Wishart matrix —and its joint eigenvalue density. We then derive a trace representation for the max-flow min-cut upper bound on the ergodic capacity of general full-duplex MIMO relay channels where each communicating node is equipped with $ N$ antennas and has access only to respective receive channel state information. We also establish the Schur monotonicity theorem for this cutset bound as a functional of the signal-to-noise ratios (SNRs) of three communication links. We further characterize the exact ergodic capacity in the regularity SNR regime where the upper and lower bounds coincide.

Minimum Energy to Send $k$ Bits Over Multiple-Antenna Fading Channels

This paper investigates the minimum energy required to transmit $k$ information bits with a given reliability over a multiple-antenna Rayleigh block-fading channel, with and without channel state information (CSI) at the receiver. No feedback is assumed. It is well known that the ratio between the minimum energy per bit and the noise level converges to −1.59 dB as $k$ goes to infinity, regardless of whether CSI is available at the receiver or not. This paper shows that the lack of CSI at the receiver causes a slowdown in the speed of convergence to −1.59 dB as $k\to \infty $ compared with the case of perfect receiver CSI. Specifically, we show that, in the no-CSI case, the gap to −1.59 dB is proportional to $((\log k) /k)^{1/3}$ , whereas when perfect CSI is available at the receiver, this gap is proportional to $1/\sqrt {k}$ . In both cases, the gap to −1.59 dB is independent of the number of transmit antennas and of the channel’s coherence time. Numerically, we observe that, when the receiver is equipped with a single antenna, to achieve an energy per bit of −1.5 dB in the no-CSI case, one needs to transmit at least $7\times 10^{7}$ information bits, whereas $6\times 10^{4}$ bits suffice for the case of perfect CSI at the receiver.

On Secrecy Performance of Multiantenna-Jammer-Aided Secure Communications With Imperfect CSI

In this paper, secure communication aided by a multiantenna cooperative jammer is investigated. Under very practical but adverse assumptions, i.e., no instantaneous jammer–eavesdropper channel state information (CSI) and imperfect instantaneous jammer–receiver CSI, the residual interference from the jammer to the legitimate receiver appears, even with spatial beamforming. Then, this paper analyzes the impact of imperfect CSI on the function of cooperative jamming and derives closed-form expressions of multiple secrecy performance metrics, including ergodic secrecy rate, secrecy outage capacity, and interception probability. Interestingly, it is found that two antennas at the jammer is always optimal. Furthermore, some insights are obtained through asymptotic analysis, e.g., the secrecy performance is saturated as the source transmit power increases, the ergodic secrecy rate is a linear function of CSI feedback bits in the region of high transmit power at the source/jammer, and interception probability is independent of transmit power at the source and is a decreasing function of transmit power at the jammer. Finally, theoretical claims are validated by simulation results.