Multiple-input multiple-output (MIMO) systems have been widely acclaimed in order to provide high data rates. Recently Lattice Reduction (LR) aided detectors have been proposed to achieve near Maximum Likelihood (ML) performance with low complexity. In this paper, we develop the fixed point design of an iterative soft decision based LR-aided K-best decoder, which reduces the complexity of existing sphere decoder. A simulation based word-length optimization is presented for physical implementation of the K-best decoder. Simulations show that the fixed point result of 16 bit precision can keep bit error rate (BER) degradation within 0.3 dB for 8x8 MIMO systems with different modulation schemes.
Generalized spatial modulation (GenSM) aided millimeter wave (mmWave) multiple-input multiple-output (MIMO) has recently received substantial academic attention. However, due to the insufficient exploitation of the transmitter's knowledge of the channel state information (CSI), the achievable rates of state-of-the-art GenSM-aided mmWave MIMO systems are far from being optimal. Against this background, a novel analog precoding scheme is proposed in this paper to improve the spectral efficiency (SE) of conventional GenSM-aided mmWave MIMOs. More specifically, we firstly manage to lower-bound the…
This paper exploits the potential of physical layer security in massive multiple-input multiple-output (MIMO) aided two-tier heterogeneous networks (HetNets). We focus on the downlink secure transmission in the presence of multiple eavesdroppers. We first address the impact of massive MIMO on the maximum receive power based user association. We then derive the tractable upper bound expressions for the secrecy outage probability of a HetNets user.We show that the implementation of massive MIMO significantly improves the secrecy performance, which indicates that physical layer security could be …
This paper explores the potential of wireless power transfer (WPT) in massive multiple input multiple output (MIMO) aided heterogeneous networks (HetNets), where massive MIMO is applied in the macrocells, and users aim to harvest as much energy as possible and reduce the uplink path loss for enhancing their information transfer. By addressing the impact of massive MIMO on the user association, we compare and analyze two user association schemes. We adopt the linear maximal ratio transmission beam-forming for massive MIMO power transfer to recharge users. By deriving new statistical properties,…
Low-complexity precoding {algorithms} are proposed in this work to reduce the computational complexity and improve the performance of regularized block diagonalization (RBD) {based} precoding {schemes} for large multi-user {MIMO} (MU-MIMO) systems. The proposed algorithms are based on a channel inversion technique, QR decompositions{,} and lattice reductions to decouple the MU-MIMO channel into equivalent SU-MIMO channels. Simulation results show that the proposed precoding algorithms can achieve almost the same sum-rate performance as RBD precoding, substantial bit error rate (BER) performanc…
We propose a deep-learning approach for the joint MIMO detection and channel decoding problem. Conventional MIMO receivers adopt a model-based approach for MIMO detection and channel decoding in linear or iterative manners. However, due to the complex MIMO signal model, the optimal solution to the joint MIMO detection and channel decoding problem (i.e., the maximum likelihood decoding of the transmitted codewords from the received MIMO signals) is computationally infeasible. As a practical measure, the current model-based MIMO receivers all use suboptimal MIMO decoding methods with affordable …
Lattice reduction (LR) aided multiple-input-multiple-out (MIMO) linear detection can achieve the maximum receive diversity of the maximum likelihood detection (MLD). By emloying the most commonly used Lenstra, Lenstra, and L. Lovasz (LLL) algorithm, an equivalent channel matrix which is shorter and nearly orthogonal is obtained. And thus the noise enhancement is greatly reduced by employing the LR-aided detection. One problem is that the LLL algorithm can not guarantee to find the optimal basis. The optimal lattice basis can be found by the Korkin and Zolotarev (KZ) reduction. However, the KZ …
This letter investigates the secure communication in a reconfigurable intelligent surface (RIS)-aided multiuser massive multiple-input multiple-output (MIMO) system exploiting artificial noise (AN). We first derive a closed-form expression of the ergodic secrecy rate under spatially correlated MIMO channels. By using this derived result, we further optimize the power fraction of AN in closed form and the RIS phase shifts by developing a gradient-based algorithm, which requires only statistical channel state information (CSI). Our analysis shows that spatial correlation at the RIS provides an a…
In this paper, we address the problem of optimal power allocation at the relay in two-hop secure communications under practical conditions. To guarantee secure communication during the long-distance transmission, the massive MIMO (M-MIMO) relaying techniques are explored to significantly enhance wireless security. The focus of this paper is on the analysis and design of optimal power assignment for a decode-and-forward (DF) M-MIMO relay, so as to maximize the secrecy outage capacity and minimize the interception probability, respectively. Our study reveals the condition for a nonnegative the s…
Intelligent reflecting surfaces (IRSs) enable multiple-input multiple-output (MIMO) transmitters to modify the communication channels between the transmitters and receivers. In the presence of eavesdropping terminals, this degree of freedom can be used to effectively suppress the information leakage towards such malicious terminals. This leads to significant potential secrecy gains in IRS-aided MIMO systems. This work exploits these gains via a tractable joint design of downlink beamformers and IRS phase-shifts. In this respect, we consider a generic IRS-aided MIMO wiretap setting and invoke f…
This work is devoted to solve the problem of estimating the carrier frequency offset, phase offset, amplitude, and SNR between two mmWave transceivers. The Cramér-Rao Lower Bound (CRLB) for the different parameters is provided first, as well as the condition for the CRLB to exist, known as Regularity Condition. Thereafter, the problem of finding suitable estimators for the parameters is adressed, for which the proposed solution is the Maximum Likelihood estimator (ML).
In order to meet the demands of future innovative applications, many efforts have been made to exceed the limits predicted by Shannon's Theory. Besides the investigation of beyond-Shannon metrics such as security, latency, and semantics, another direction is to jointly design the transceiver and the environment by utilizing the intelligent reflecting surface (IRS). In this paper, we consider the analysis and design of IRS-aided multiple-input multiple-output (MIMO) secure communications, which has attracted much research attention but still in its infancy. For example, despite their importance…
In future sixth-generation (6G) mobile networks, the Internet-of-Everything (IoE) is expected to provide extremely massive connectivity for small battery-powered devices. Indeed, massive devices with limited energy storage capacity impose persistent energy demand hindering the lifetime of communication networks. As a remedy, wireless energy transfer (WET) is a key technology to address these critical energy supply issues. On the other hand, cell-free (CF) massive multiple-input multiple-output (MIMO) systems offer an efficient network architecture to realize the roll-out of the IoE. In this ar…
In this paper, we propose a novel joint caching and massive multiple-input multiple-output (MIMO) transmission scheme, referred to as \emph{cache-aided massive MIMO}, for multi-cell downlink transmission to multiple cache-enabled receivers. With the proposed scheme, users who have cached (a portion of) the files that they request are offloaded and, hence, (partially) inactive during downlink transmission. The other users either benefit from the cache-enabled offloading for mitigating pilot contamination or exploit the cached but unrequested files to cancel interference during uplink channel es…
Due to the high cost and low energy efficiency of the dedicated radio frequency (RF) chains, the number of RF chains in a millimeter wave (mmWave) multiple-input multiple-output (MIMO) system is usually limited from a practical point of view. In this case, the maximum number of independent data streams is also restricted by the number of RF chains, which consequently leads to limiting the potentially attainable spatial multiplexing gain. In order to address this issue, in this paper, a novel generalized spatial modulation (GenSM) aided mmWave MIMO system is proposed, which enables the transmis…
We propose an improved soft-aided decoding scheme for product codes that approaches the decoding performance of conventional soft-decision TPD with only a 0.2 dB gap while keeping the complexity and internal decoder data flow similarly low as in hard decision decoders.
The main difficulty concerning optimizing the mutual information (MI) in reconfigurable intelligent surface (RIS)-aided communication systems with discrete signaling is the inability to formulate this optimization problem in an analytically tractable manner. Therefore, we propose to use the cutoff rate (CR) as a more tractable metric for optimizing the MI and introduce two optimization methods to maximize the CR, assuming perfect knowledge of the channel state information (CSI). The first method is based on the projected gradient method (PGM), while the second method is derived from the princi…
We propose a novel soft-aided low-complexity decoder for product codes based on dynamic reliability scores and error-and-erasure decoding. We observe coding gains of up to 1.2 dB compared to conventional hard-decision decoders.
Diversity order is an important measure for the performance of communication systems over MIMO fading channels. In this paper, we prove that in MIMO multiple access systems (or MIMO point-to-point systems with V-BLAST transmission), lattice-reduction-aided decoding achieves the maximum receive diversity (which is equal to the number of receive antennas). Also, we prove that the naive lattice decoding (which discards the out-of-region decoded points) achieves the maximum diversity.
In this paper, we investigate relay selection for cooperative multiple-antenna systems that are equipped with buffers, which increase the reliability of wireless links. In particular, we present a novel relay selection technique based on switching and the Max-Link protocol that is named Switched Max-Link. We also introduce a novel relay selection criterion based on the maximum likelihood (ML) principle denoted maximum minimum distance that is incorporated into. Simulations are then employed to evaluate the performance of the proposed and existing techniques.
This letter investigates the joint active and passive beamforming optimization for intelligent reflecting surface (IRS) aided multiuser multiple-input multiple-output systems with the objective of maximizing the weighted sum-rate. We show that this problem can be solved via a matrix weighted mean square error minimization equivalence. In particular, for the optimization of the passive IRS beamforming, we first propose an iterative algorithm with excellent performance based on the manifold optimization. By using the matrix fractional programming technique to obtain a more tractable object funct…
In this work, we consider the problem of reduced latency of low-density parity-check (LDPC) codes with iterative detection and decoding (IDD) receiver in multiuser multiple-antenna systems. The proposed knowledge-aided IDD (KA-IDD) system employs a minimum mean-square error detector with refined iterative processing and a reweighted belief propagation (BP) decoding algorithm. We present reweighted BP decoding algorithms, which exploit the knowledge of short cycles in the graph structure and reweighting factors derived from the expansion of hypergraphs. Simulation results show that the proposed…
Lattice reduction-aided decoding features reduced decoding complexity and near-optimum performance in multi-input multi-output communications. In this paper, a quantitative analysis of lattice reduction-aided decoding is presented. To this aim, the proximity factors are defined to measure the worst-case losses in distances relative to closest point search (in an infinite lattice). Upper bounds on the proximity factors are derived, which are functions of the dimension $n$ of the lattice alone. The study is then extended to the dual-basis reduction. It is found that the bounds for dual basis red…
Massive multiple-input multiple-output (MIMO) systems use antenna arrays with a large number of antenna elements to serve many different users simultaneously. The large number of antennas in the system makes, however, the channel state information (CSI) acquisition strategy design critical and particularly challenging. Interestingly, in the context of massive MIMO systems, channels exhibit a large degree of spatial correlation which results in strongly rank-deficient spatial covariance matrices at the base station (BS). With the final objective of analyzing the benefits of covariance-aided upl…
In this paper we present a novel method for decoding multiple input - multiple output (MIMO) transmission, which combines sphere decoding (SD) and zero forcing (ZF) techniques to provide near optimal low complexity and high performance constant time modified sphere decoding algorithm. This algorithm was designed especially for large number of transmit antennas, and allows efficient implementation in hardware. We do this by limiting the number of overall SD iterations. Moreover, we make sure that matrices with high condition number are more likely to undergo SD.
We propose a novel optimization-based decoding algorithm for LDPC-coded massive MIMO channels. The proposed decoding algorithm is based on a proximal gradient method for solving an approximate maximum a posteriori (MAP) decoding problem. The key idea is the use of a code-constraint polynomial penalizing a vector far from a codeword as a regularizer in the approximate MAP objective function. The code proximal operator is naturally derived from code-constraint polynomials. The proposed algorithm, called proximal decoding, can be described by a simple recursion consisting of the gradient descent …
The 3D MIMO code is a robust and efficient space-time coding scheme for the distributed MIMO broadcasting. However, it suffers from the high computational complexity if the optimal maximum-likelihood (ML) decoding is used. In this paper we first investigate the unique properties of the 3D MIMO code and consequently propose a simplified decoding algorithm without sacrificing the ML optimality. Analysis shows that the decoding complexity is reduced from O(M^8) to O(M^{4.5}) in quasi-static channels when M-ary square QAM constellation is used. Moreover, we propose an efficient implementation of t…
Caching is an effective technique to improve user perceived experience for content delivery in wireless networks. Wireless caching differs from traditional web caching in that it can exploit the broadcast nature of wireless medium and hence opportunistically change the network topologies. This paper studies a cache-aided MIMO interference network with 3 transmitters each equipped with M antennas and 3 receivers each with N antennas. With caching at both the transmitter and receiver sides, the network is changed to hybrid forms of MIMO broadcast channel, MIMO X channel, and MIMO multicast chann…
Lenstra-Lenstra-Lovasz (LLL) algorithm, which is one of the lattice reduction (LR) techniques, has been extensively used to obtain better basis of the channel matrix. In this paper, we jointly apply Seysen's lattice reduction algorithm (SA), instead of LLL, with the conventional linear precoding algorithms. Since SA obtains more orthogonal lattice basis compared to that obtained by LLL, lattice reduction aided (LRA) precoding based on SA algorithm outperforms the LRA precoding with LLL. Simulation results demonstrate that a gain of 0.5dB at target BER of 10^-5 is achieved when SA is used inste…
In this paper, we study a multi-user multiple-input-multiple-output secrecy simultaneous wireless information and power transfer (SWIPT) channel which consists of one transmitter, one cooperative jammer (CJ), multiple energy receivers (potential eavesdroppers, ERs), and multiple co-located receivers (CRs). We exploit the dual of artificial noise (AN) generation for facilitating efficient wireless energy transfer and secure transmission. Our aim is to maximize the minimum harvested energy among ERs and CRs subject to secrecy rate constraints for each CR and total transmit power constraint. By i…
Intelligent reflecting surfaces (IRSs) are promising enablers for high-capacity wireless communication systems by constructing favorable channels between the transmitter and receiver. However, general, accurate, and tractable outage analysis for IRS-aided multiple-input-multiple-output (MIMO) systems is not available in the literature. In this paper, we first characterize the mutual information (MI) of IRS-aided MIMO systems by capitalizing on large random matrix theory (RMT). Based on this result, a closed-form approximation for the outage probability is derived and a gradient-based algorithm…
Reconfigurable intelligent surface (RIS) is envisioned to be a promising green technology to reduce the energy consumption and improve the coverage and spectral efficiency of massive multiple-input multiple-output (MIMO) wireless networks. In a RIS-aided MIMO system, the acquisition of channel state information (CSI) is important for achieving passive beamforming gains of the RIS, but is also challenging due to the cascaded property of the transmitter-RIS-receiver channel and the lack of signal processing capability of the passive RIS elements. The state-of-the-art approach for CSI acquisition…
The application of hybrid precoding in millimeter wave (mmWave) multiple-input multiple-output (MIMO) systems has been proved effective for reducing the number of radio frequency (RF) chains. However, the maximum number of independent data streams is conventionally restricted by the number of RF chains, which leads to limiting the spatial multiplexing gain. To further improve the achievable spectral efficiency (SE), in this paper we propose a novel generalized spatial modulation (GenSM) aided mmWave MIMO system to convey an extra data stream via the index of the active antennas group, while no…
In this paper, we consider the problem of iterative detection and decoding (IDD) for multi-antenna systems using low-density parity-check (LDPC) codes. The proposed IDD system consists of a soft-input soft-output parallel interference (PIC) cancellation scheme with linear minimum mean-square error (MMSE) receive filters and two novel belief propagation (BP) decoding algorithms. The proposed BP algorithms exploit the knowledge of short cycles in the graph structure and the reweighting factors derived from the hypergraph's expansion. Simulation results show that when used to perform IDD for mult…
In Multi-Input Multi-Output (MIMO) systems, Maximum-Likelihood (ML) decoding is equivalent to finding the closest lattice point in an N-dimensional complex space. In general, this problem is known to be NP hard. In this paper, we propose a quasi-maximum likelihood algorithm based on Semi-Definite Programming (SDP). We introduce several SDP relaxation models for MIMO systems, with increasing complexity. We use interior-point methods for solving the models and obtain a near-ML performance with polynomial computational complexity. Lattice basis reduction is applied to further reduce the computati…
Location-aided beam alignment has been proposed recently as a potential approach for fast link establishment in millimeter wave (mmWave) massive MIMO (mMIMO) communications. However, due to mobility and other imperfections in the estimation process, the spatial information obtained at the base station (BS) and the user (UE) is likely to be noisy, degrading beam alignment performance. In this paper, we introduce a robust beam alignment framework in order to exhibit resilience with respect to this problem. We first recast beam alignment as a decentralized coordination problem where BS and UE see…
This paper investigates the performance of reconfigurable intelligent surface (RIS)-aided massive multiple-input multiple-output (MIMO) systems with direct links, and the phase shifts of the RIS are designed based on the statistical channel state information (CSI). We first derive the closed-form expression of the uplink ergodic data rate. Then, based on the derived expression, we use the genetic algorithm (GA) to solve the sum data rate maximization problem. With low-complexity maximal-ratio combination (MRC) and low-overhead statistical CSI-based scheme, we validate that the RIS can still br…
The optimal design of the energy-efficient multiple-input multiple-output (MIMO) aided uplink ultra-reliable low-latency communications (URLLC) system is an important but unsolved problem. For such a system, we propose a novel absorbing-Markov-chain-based analysis framework to shed light on the puzzling relationship between the delay and reliability, as well as to quantify the system energy efficiency. We derive the transition probabilities of the absorbing Markov chain considering the Rayleigh fading, the channel estimation error, the zero-forcing multi-user-detection (ZF-MUD), the grant-free…
Reconfigurable intelligent surface (RIS) has recently drawn intensive attention due to its potential of simultaneously realizing high spectral and energy efficiency in a sustainable way. This paper focuses on the design of efficient transmission methods to maximize the uplink sum throughput in a RIS-aided multi-user multi-input multi-output (MU-MIMO) system. To provide an insightful basis, the channel capacity of RIS-aided MU-MIMO is theoretically analyzed. Then, the conventional transmission schemes based on orthogonal multiple access are presented as the baseline. From the information-theore…
We consider channel estimation for high-speed railway communication systems, where both the transmitter and the receiver are equipped with large-scale antenna arrays. It is known that the throughput of conventional training schemes monotonically decreases with the mobility. Assuming that the moving terminal employs a large linear antenna array, this paper proposes a position-aided channel estimation scheme whereby only a portion of the transmit antennas send pilot symbols and the full channel matrix can be well estimated by using these pilots together with the antenna position information base…
Currently for the nt x nr MIMO channel, any explicitly constructed space-time (ST) designs that achieve optimality with respect to the diversity multiplexing tradeoff (DMT) are known to do so only when decoded using maximum likelihood (ML) decoding, which may incur prohibitive decoding complexity. In this paper we prove that MMSE regularized lattice decoding, as well as the computationally efficient lattice reduction (LR) aided MMSE decoder, allows for efficient and DMT optimal decoding of any approximately universal lattice-based code. The result identifies for the first time an explicitly co…
Intelligent reflecting surface (IRS) is a promising technology to extend the wireless signal coverage and support the high performance communication. By intelligently adjusting the reflection coefficients of a large number of passive reflecting elements, the IRS can modify the wireless propagation environment in favour of signal transmission. Different from most of the prior works which did not consider any cooperation between IRSs, in this work we propose and study a cooperative double-IRS aided multiple-input multiple-output (MIMO) communication system under the line-of-sight (LoS) propagati…
Nagoya Institute of Technology（名古屋工业大学）；RIKEN Center for Advanced Intelligence Project（理化学研究所先进智能项目中心）；Osaka City University（大阪市立大学）
The paper presents a deep learning-aided iterative detection algorithm for massive overloaded MIMO systems. Since the proposed algorithm is based on the projected gradient descent method with trainable parameters, it is named as trainable projected descent-detector (TPG-detector). The trainable internal parameters can be optimized with standard deep learning techniques such as back propagation and stochastic gradient descent algorithms. This approach referred to as data-driven tuning brings notable advantages of the proposed scheme such as fast convergence. The numerical experiments show that …
In this paper, we first propose interference alignment (IA) scheme for uplink transmission of multiple-input-mulitple-output (MIMO) cellular network with a help of relay which operates in halfduplex mode. The proposed scheme only requires global channel state information (CSI) knowledge at relay and no transmitter beamforming and time extension is required at user equipment (UE), which differs from the conventional IA schemes for cellular network. We derive the feasibility condition of the proposed scheme for the general network configuration and analyze the degrees-of-freedom (DoF) performanc…
Recently, rate-$1/ω$ zero-terminated and tail-biting convolutional codes (ZTCCs and TBCCs) with cyclic-redundancy-check (CRC)-aided list decoding have been shown to closely approach the random-coding union (RCU) bound for short blocklengths. This paper designs CRCs for rate-$(ω-1)/ω$ CCs with short blocklengths, considering both the ZT and TB cases. The CRC design seeks to optimize the frame error rate (FER) performance of the code resulting from the concatenation of the CRC and the CC. Utilization of the dual trellis proposed by Yamada \emph{et al.} lowers the complexity of CRC-aided serial l…
Intelligent reflecting surfaces (IRSs) are promising enablers for next-generation wireless communications due to their reconfigurability and high energy efficiency in improving poor propagation condition of channels, e.g., limited scattering environment. However, most existing works assumed full-rank channels requiring rich scatters, which may not be available in practice. To analyze the impact of rank-deficient channels and mitigate the ensued performance loss, we consider a large-scale IRS-aided MIMO system with statistical channel state information (CSI), where the double-scattering channel…
We consider a reconfigurable intelligent surface (RIS)-aided massive multi-user multiple-input multiple-output (MIMO) communication system with transceiver hardware impairments (HWIs) and RIS phase noise. Different from the existing contributions, the phase shifts of the RIS are designed based on the long-term angle informations. Firstly, an approximate analytical expression of the uplink achievable rate is derived. Then, we use genetic algorithm (GA) to maximize the sum rate and the minimum date rate. Finally, we show that it is crucial to take HWIs into account when designing the phase shift…
Although the sphere decoder (SD) is a powerful detector for multiple-input multiple-output (MIMO) systems, it has become computationally prohibitive in massive MIMO systems, where a large number of antennas are employed. To overcome this challenge, we propose fast deep learning (DL)-aided SD (FDL-SD) and fast DL-aided $K$-best SD (KSD, FDL-KSD) algorithms. Therein, the major application of DL is to generate a highly reliable initial candidate to accelerate the search in SD and KSD in conjunction with candidate/layer ordering and early rejection. Compared to existing DL-aided SD schemes, our pr…
We consider the uplink of a cloud radio access network (C-RAN), where massive MIMO remote radio heads (RRHs) serve as relays between users and a centralized baseband unit (BBU). Although employing massive MIMO at RRHs can improve the spectral efficiency, it also significantly increases the amount of data transported over the fronthaul links between RRHs and BBU, which becomes a performance bottleneck. Existing fronthaul compression methods for conventional C-RAN are not suitable for the massive MIMO regime because they require fully-digital processing and/or real-time full channel state inform…
We consider unsourced random access with MIMO receiver - a crucial communication scenario for future 5G/6G wireless networks. We perform a projection-based decoder analysis and derive energy efficiency achievability bounds when channel state information is unknown at transmitters and the receiver (no-CSI scenario). The comparison to the maximum-likelihood (ML) achievability bounds by Gao et al. (2023) is performed. We show that there is a region where the new bound outperforms the ML bound. The latter fact should not surprise the reader as both decoding criteria are suboptimal when considering…
This paper investigates a reconfigurable intelligent surface (RIS)-aided multi-user multiple-input multiple-output (MIMO) system by considering only the statistical channel state information (CSI) at the base station (BS). We aim to maximize its sum-rate via the joint optimization of beamforming at the BS and phase shifts at the RIS. However, the multi-user MIMO transmissions and the spatial correlations make the optimization cumbersome. For tractability, a deterministic approximation is derived for the sum-rate under a large number of the reflecting elements. By adopting the approximate sum-r…
