The evolution of 6G has brought distributed multi-input multi-output (D-MIMO) near-field communications into the spotlight, owing to their potential to significantly enhance wireless capacity and spectral efficiency. This study delves into exploring the optimal characteristics of distributed antenna deployment in D-MIMO systems through the optimization of access point (AP) placement and subarray topology. To guarantee the stability of system configuration, we derive an approximate ergodic sum rate with high accuracy under near-field spherical wavefront propagation that serves as the optimization criterion. Confronting the non-convex challenges, we adopt an approach integrating successive convex approximation (SCA), gradient descent, and alternating optimization methods, which enables us to attain a near-optimal solution with low complexity. Numerical simulations highlight the significant superiority of our proposal to traditional baseline approaches, revealing key characteristics and providing crucial insights for AP deployment and array layout optimization. In densely clustered user scenarios, APs should be deployed near the user aggregation centroid, which may not align with the geometric center. For dispersed user distributions, AP deployment positions should be adjusted more flexibly to regional statistical characteristics rather than confined to central points to accommodate specific user distribution features. Moreover, the array topology exhibits a pattern of alternating dense and sparse distribution, diverging from the attributes observed in centralized MIMO (C-MIMO) architectures, where a consistent medium density is flanked by regions of sparsity.

The beamfocusing property can be effectively utilized to enhance system performance in near-field communications. In this paper, the secure transmission for near-field extremely large-scale MIMO (XL-MIMO) communication systems is investigated, where the base station (BS) transmits private confidential information to legitimate users under the threat of a potential eavesdropper. To explore the unique characteristics of near-field physical layer security (PLS), a specific scenario involving a single legitimate user and a single eavesdropper is first considered. It is rigorously proved that 1) Artificial noise (AN) plays an essential role in near-field secure communications, facilitating the transformation of insecure systems into secure ones, and 2) allocating even a small portion of power for AN substantially improves security, compared with scenarios where AN is not employed. Additionally, for the general scenario with multiple legitimate users, a conventional scheme is initially introduced by employing semi-definite relaxation and successive convex approximation algorithms. Subsequently, an efficient low-complexity beamforming scheme incorporating AN is proposed to ensure secure transmission in the near-field region. Furthermore, the closed-form solution for optimal beamforming power allocation is derived. Extensive numerical results show that 1) the utilization of near-field beamfocusing exhibits significant performance gains in enhancing PLS in comparison with far-field communications, and 2) the proposed scheme achieves performance comparable to the high computational complexity conventional scheme, while significantly reducing computational complexity.

In the realm of fifth-generation new radio (5G-NR) communication technology, how to use limited resources and low-complexity algorithms to provide high transmission rates for massive multiple-input multiple-output (mMIMO) systems with differentiated service demands remains a challenge. This paper explores a novel scenario-specific beamforming design tailored to user distributions and propagation environments. The proposed method dynamically adjusts beam orientations and widths, enabling precise coverage of users’ active regions. To mitigate inter-beam interference in spatial multiplexing, we derive a strict orthogonality condition and propose a corresponding beam grouping strategy to enforce it. Furthermore, to address the nonconvex optimization problem of time-frequency-space resource allocation (RA), we build upon the idea of the greedy algorithm to balance transmission rate and computational complexity. Building on this foundation, we propose a traffic-aware RA strategy and introduce a novel beam selection criterion by incorporating both channel characteristics and user-specific traffic demands. These improvements jointly enhance the system’s utilization of time-frequency resources and spatial reuse capability. Simulation results validate the proposed algorithms, demonstrating notable improvements in computational efficiency, system adaptability, spectral efficiency, and average achievable rate.

Simultaneously transmitting and reflecting reconfigurable intelligent surface (STAR-RIS) offers a promising solution to conquer the challenge of severe signal attenuation through buildings for seamless indoor-outdoor connectivity in 6G networks. This paper focuses on hybrid active-passive STAR-RIS assisted indoor-outdoor communications and delves into the comparative impact of diverse non-ideal factors on system performance, such as transceiver hardware impairments, imperfect channel state information (CSI), and STAR-RIS phase noise. Under these system imperfections, our objective is to maximize the minimum user rate by optimizing user grouping, non-orthogonal multiple access (NOMA) decoding order, power allocation coefficients, active beamforming, and transmission and reflection beamforming, thereby enhancing system robustness and user fairness. Given the complexity of the formulated problem, characterized by interwoven optimization variables, we propose a collaborative convex optimization iterative (CCOI) algorithm by blending successive convex approximation (SCA), semidefinite relaxation (SDR), Gaussian randomization, and convex upper bound approximation. This methodology is capable of adeptly striking a balance between system performance and computational efficiency. Simulation results demonstrate the significant advantages of our proposed CCOI algorithm and provides guiding insights on system design for various defects. Additionally, the hybrid active-passive STAR-RIS structure offers enhanced flexibility and effectively balances the performance trade-offs between conventional active and passive models.

The near-field spatial correlation for multiple-input multiple-output (MIMO) communications in multi-path fading channels is analyzed. Based on the general non-uniform spherical wave (NUSW) model, an analytical integral-form expression for near-field spatial correlation is derived, which generalizes the conventional uniform plane wave (UPW)-based far-field spatial correlation. Furthermore, by considering the specific von Mises-Fisher distribution of scatterer locations, a simplified closed-form near-field spatial correlation expression is derived. It is rigorously proved that 1) in contrast to the far-field spatial correlation, the near-field spatial correlation no longer exhibits spatial stationary property, and 2) the NUSW-based near-field spatial correlation model depends on the power location spectrum, which encompasses both the angles and distances of the scatterers. Next, the developed near-field spatial correlation can be utilized to derive a closed-form expression for the effective degrees of freedom (EDoF). Additionally, a correlation-based stochastic channel model is constructed for MIMO communications, from which an optimal transmission strategy is devised. Subsequently, the power allocation is optimized to achieve the maximum ergodic spectral efficiency. Numerical results validate 1) the significance of near-field spatial correlation modeling for MIMO communications, 2) near-field MIMO exhibits a higher EDoF than the conventional far-field counterpart, and 3) the constructed correlation-based stochastic channel model facilitates the derivation of an optimal transmission strategy, thereby maximizing ergodic spectral efficiency.

The channel characteristics of immersed tunnels play a crucial role in the design and optimization of electronic toll collection (ETC) communication systems in such environments. Due to the lack of channel characteristics for all-metal immersed tunnel environments, this paper conducts an in-depth study on channel measurement, channel modeling, and optimization of ETC systems within all-metal immersed tunnels. Using a channel measurement system based on the universal software radio peripheral (USRP), this study extracts multidimensional channel characteristic parameters from the measured data, such as path loss (PL), shadow fading (SF), K-factor (KF), root mean square delay spread (RMS DS), power angular spectrum (PAS), and azimuth angle spread (ASA). The unique characteristics of the all-metal tunnel are analyzed in comparison to tunnels made of other materials. To develop a comprehensive all-metal immersed tunnel channel model meeting the quasi-deterministic radio channel generator (QuaDRiGa) requirements, we employed ray tracing (RT) methods to supplement angle domain parameters. Subsequently, we used this channel model to aid in the design and optimization of ETC systems, addressing transaction failures and erroneous transactions within all-metal immersed tunnels by establishing optimization targets and constraints, resulting in optimal height, tilt angle, transmission power, and beamforming. The findings of this research not only enrich the channel scenarios in QuaDRiGa but also provide practical guidance for improving the performance of ETC systems.

The beamforming performance of the uniform circular array (UCA) in near-field wideband communication systems is investigated. Firstly, the unique beam squint effect in near-field wideband UCA systems is analyzed in both the distance and angular domains. It is demonstrated that the generated beams at different frequencies are focused at different locations, resulting in significant beamforming loss. To alleviate this unique beam squint effect and facilitate beamfocusing, an energy-efficient beamforming scheme based on the true-time delay (TTD) architecture is proposed. Specifically, the phase shifters (PSs) and the time delay of TTDs are designed based on the analytical formula for beamforming gain. Additionally, the minimum number of TTDs required to achieve a predetermined beamforming gain while minimizing energy consumption is quantified. Numerical results show that the proposed beamforming scheme effectively eliminates the near-field beam squint and outperforms the conventional schemes in terms of spectral efficiency and energy efficiency.

In this paper, the design of non-uniform antenna topology for 3D massive MIMO arrays in near-field communications is investigated. Specifically, the near-field spherical wavefront radiation characteristics are considered to accurately model the variations of signal phase across array elements. Subsequently, the closed-form expressions of the per-user signal-to-interference noise ratio (SINR) and achievable sum rate for a multi-user MIMO system with maximum-ratio transmission (MRT) precoding are derived. The focus is on the maximization of the achievable sum rate by optimizing the non-uniform 3D antenna array topology. Since the optimization problem exhibits highly nonlinear and nonconvex characteristics, an enhanced particle swarm optimization (EPSO) algorithm is proposed to effectively solve it. Numerical results demonstrate the superiority of the proposed non-uniform 3D array topology in near-field communications for enhancing the achievable sum rate.

Precise parameter estimation is essential for developing effective channel models. However, jointly estimating the various channel parameters is a challenging problem as these parameters can only be extracted from comprehensive data collected during massive measurement activities. Traditional algorithms suffer from limited estimation accuracy due to high mobility and signal correlation. In this paper, we propose a low-complexity full-dimension parameter extraction algorithm. The method extends the forward-backward spatial smoothing technique to estimate two-dimensional (2-D) angle information in the uniform planar array (UPA), enhancing aperture size and providing higher resolution for coherent signals. Then, we provide a Doppler compensation technique to prevent the deterioration in complex amplitude estimation quality caused by large Doppler frequency in high-speed mobile environments. Moreover, the proposed algorithm is also applied to the fifth-generation new radio (5G-NR) system. To remedy power leakage in the channel impulse response (CIR), we propose an eigenvalue-assisted sampling point selection scheme. This scheme preserves sampling positions abundant in channel information to reduce computational complexity and eliminate most noise. Simulation and field tests show that the proposed algorithm achieves better performance with lower computational complexity compared to the existing algorithm.

The three-dimensional (3D) beamforming property of the uniform circular array (UCA) in near-field wideband communication systems is comprehensively analyzed in both the distance and angular domains. It is rigorously demonstrated that the beam focal point only exists at a specific frequency in wideband UCA systems, resulting in significant beamforming loss. To facilitate near-field beamfocusing and alleviate the beam squint effect, the true-time delay (TTD)-based beamforming architecture is exploited. In particular, two wideband beamforming optimization approaches leveraging TTD units are proposed. 1)Analytical approach: In this approach, the phase shifters (PSs) and the time delay of TTD units are designed based on the analytical formula for beamforming gain. Following this design, the minimum number of TTD units required to achieve a predetermined beamforming gain is quantified. 2)Joint-optimization approach: In this method, the PSs and the TTD units are jointly optimized under practical maximum delay constraints to approximate the optimal unconstrained analog beamformer. Specifically, an efficient alternating optimization algorithm is proposed, where the PSs and the TTD units are alternately updated using either the closed-form solution or the low-complexity linear search approach. Extensive numerical results demonstrate that 1) the proposed beamforming schemes effectively mitigate the beam squint effect, and 2) the joint-optimization approach outperforms the analytical approach in terms of array gain and achievable spectral efficiency.

In this paper, we investigate the optimization of non-uniform planar array (NUPA) for massive multi-input multi-output (MIMO) near-field wireless communications with line-of-sight (LOS) channels. In particular, the NUPAs at both the transmitter and receiver are misaligned placed with certain placement angles. Our focus is on the maximization of the system channel capacity, by optimizing the antenna elements position in the transmit/receive NUPAs. With the near-field spherical wave channel modeling, and by taking into account the geometric structure relationship of the arrays, the mathematically expression of channel capacity with this NUPA deployment is derived. Then, the relationship between the eigenvalues and the misaligned angles is analyzed, which further reveals the effect of the misalignment angle on the channel capacity. We show that channel capacity under specific transmission distance is related to the offset angle but irrelevant to the placement angles. Numerical results demonstrate that our theoretical analysis are consistent with the simulation results and the superiority of our optimized NUPA topology in system capacity.

Reconfigurable intelligent Surface (RIS) are often proposed as a means for restoring non-line-of-sight (NLoS) links in wireless communication. In this paper, we propose a joint design strategy for multi-RIS deployment locations and passive beamforming in multi-RIS assisted multi-BS networks with blockages. To ensure a stable network topology and low feedback overhead, the ergodic capacity is analyzed using Jensen’s inequality and the binomial expansion theorem, and then maximized as a performance metric. Taking into account the minimum spacing constraint for multi-RIS in real-world scenarios, we optimize the multi-RIS deployment locations using a genetic algorithm, where a Markov chain model can be applied to obtain the global optimal solution. Additionally, we implement the passive beamforming design for multi-RIS using the Riemannian conjugate gradient (RCG) method based on manifold space. Numerical results demonstrate the superiority of our proposed deployment strategy over the benchmark deployment schemes.

Beamforming (BF) often requires the base station (BS) to master precise angle information from the uplink channel impulse response (CIR). Based on the three-dimensional (3D) wireless multipath channel in the fifth generation (5G) new radio (NR) system, we can easily obtain the channel frequency response (CFR) of the orthogonal frequency division multiplexing (OFDM) structure using the sounding reference signal (SRS). However, when CFR is converted into CIR by the inverse fast Fourier transform (IFFT), the phenomenon of leakage will occur. In this paper, we combine the time-delay and spatial domains to design an algorithm for analyzing ultra-high-resolution paths in the presence of coherent sources and energy leakage. And we theoretically expound the advantages of using leaked CIR instead of CFR to extract angle information. The experimental results show that the proposed algorithm can perfectly construct the power angle spectrum (PAS) and reconstruct the CIR in beam domain based on the data received by the uplink at the BS. The original CIR in beam domain received by the BS further verifies the correctness of our results.

Monitoring of critical frequency variation in the ionospheric F2 layer (foF2) has lately received considerable attention for the frequency selection in skywave communication. Currently, both the deep learning and machine learning model have made a striking accomplishment in comprehending the ionosphere. In this letter, we utilize an Informer architecture to predict the foF2 parameter under the two scenarios in terms of the quiet space weather and storm events. The Informer method applied the past and present foF2 samples to capture time sequence processing characteristics, trained and tested for 2017–2018 years’ measurement samples at Beijing, China (40.3°N, 116.2°E). It is evident from the results that the Informer performed better than International Reference Ionosphere 2016, Elman network, long short-term memory (LSTM), and bidirectional LSTM models. The Informer models extensively captured the correlation within the foF2 sequence features and better predicted it in storm events.

Integrating massive MIMO and simultaneous wireless information and power transfer (SWIPT) technology over the Rician fading channel is an effective method to achieve green communication under 5G background. This paper investigates system that the base station (BS) transmits both wireless energy and information simultaneously to the users. The users send pilots by utilizing the harvested energy from the BS to estimate the channel state, and then obtain the downlink channel state through the channel’s reciprocity to complete uplink and downlink information transmission. We propose an iterative algorithm to jointly optimize the downlink transmitting power of the BS and the power splitting (PS) ratios for minimizing the sum of transmitting power with uplink and downlink signal-to-interference-plus-noise ratio (SINR) constraints. Simulation results prove that the proposed algorithm outperforms over existing related algorithms in terms of transmitting power.

This paper is investigating and comparing three channel models for the fifth generation (5G) wireless communications: the quasi deterministic radio channel generator (QuaDRiGa), the NYUSIM developed by New York University (NYU) and the more general 5G (MG5G) channel model. The three channel models employ different approaches to model the time non-stationary characteristics of the 5G wireless communications, such as the geometry-based drifting modeling and cluster birth-death methodology. Simulations are carried out using the three channel models to analyze the statistical properties including angle power spectrum (APS), power delay profile (PDP), temporal autocorrelation function (ACF), and spatial cross-correlation function (CCF). Simulation results show that the calculation of angular parameters contributes to the performance of APS, generation approaches of path powers and cluster parameters have significant impact on PDP performance, the performance of ACF and CCF varies mainly due to the calculations of path delays and angle spreads for the three channel models in urban macrocell (UMa) mobile NLOS environments.

For partially-connected massive multiple-input multiple-output (MIMO) millimeter wave (mmWave) communications, an iterative precoding and combining algorithm is proposed to maximize the system spectrum efficiency. At the transmitter, the optimal unconstrained full digital precoder is firstly determined as a benchmark by singular value decomposition (SVD) of the channel matrix, and then resolved to achieve the hybrid analog and digital precoding in an iterative manner. Specifically, the initially formulated non-convex matrix decomposition problem is decomposed into a series of convex optimization sub-problems, with the amplitude of each element in the analog matrix restricted and the phase increment in adjacent iteration processes varies only in a small range. Moreover, with the unconstrained linear minimum mean square error (MMSE) combiner as the benchmark, similar iterations can be executed at the receiver. Numerical results show that the proposed algorithm acquires superior spectrum efficiency than the other classical scheme with partially-connected architecture. Furthermore, in spite of much lower hardware complexity and power consumption, the performance of our algorithm is almost identical to that of the full digital scheme as well as other mechanisms with fully-connected structure.

Orbital angular momentum (OAM) supplies a new degree of freedom for the electromagnetic (EM) wave, which can be used to increase communication capacity. The amplitude of the OAM wave is null in the center of the beam and the distribution of the electric field intensity is not uniform, so the study of the optimal receiving location of single OAM wave is necessary. Furthermore, in order to efficiently receive OAM waves with different OAM modes simultaneously on single receiving antenna, the common reception sampling region of multi-mode OAM waves should also be studied. However, few experiments study the region of multi-mode OAM waves. Here, concentric circular arrays are proposed to generate OAM waves with different OAM modes. Based on theoretical formulations of its radiation fields in the cylindrical coordinate system, its transmission and reception characteristics would be analyzed. Basically, the common reception sampling region of multi-mode OAM waves can be confirmed by calculating function formulas of the upper and lower boundaries of the region or analyzing amplitudes and phases of the axial ratio of optimal receiving location of multiple OAM waves. Numerical results show that methods of confirming the region are feasible and simple. When other parameters besides frequency are the same and the optimal receiving location of certain OAM mode wave at certain frequency is known, optimal receiving locations of certain OAM mode wave at other frequencies can be confirmed easily, according to the formula related to the optimal receiving location and frequency.

For the design and performance evaluation of potential massive multiple input and multiple output (MIMO) related algorithms, accurate channel models are indispensable. Spherical wavefront and array non-stationarity due to physically large antenna array are two new characteristics specific to massive MIMO propagation. In this paper, spherical wavefront effects can be well characterized by a predefined two-dimensional multi-confocal ellipse scattering geometry as in reference [1] and a 9- state Markov process is developed to capture the channel behaviors by array non-stationarity. Meanwhile, the associated approach to derive the state transition probabilities of the Markov process based on the outfield measurements is detailed. Finally, simulation results verify the validity of our proposal.

For the design, performance evaluation, and optimization of potential 3-D multiple input and multiple output (3-D MIMO) algorithms, an accurate stochastic channel model is indispensable. Simultaneously, it is desirable for the new 3-D MIMO channel model to be a further expansion of already well developed 2-D MIMO channel models to allow easy implementation and facilitate possible $3^{rd}$ generation partnership project standardization. This paper first shows our recent outfield channel measurement campaigns in urban macrocell scenarios with a planar antenna array and a crown-shaped antenna array installed on the base station and the user sides, respectively. A comprehensive methodology from the statistical analysis perspective to characterize the 3-D MIMO channel, particularly, in the elevation domain, is then elaborated upon. The framework of the new approach coincides with mainstream parametric stochastic models. Moreover, it is observed that, by recalculating the statistics of the large scale parameters as well as their cross-correlation matrix to rectify existent non-positive definite problem, adding distance dependent elevation angular spread and introducing a mixture of Von Mises Fisher distributions to describe the interdependence between azimuth and elevation, the accuracy of current standardized 3-D channel models can be improved upon. Finally, numerical results verify the validity of our proposal.

This paper proposes a selective AF-OFDM (Amplify-and-Forward, Orthogonal Frequency Division Multiplexing) relaying protocol, in which selective relaying policy is adequately utilized to improve the spectrum efficiency of cooperative multi-carrier transmission, and addresses the power minimization problem subject to a target quality of service (QoS) constraint for corresponding battery-operated systems. By transforming the original power minimization issue into a two-stage problem, i.e., a power loading subproblem and a selective relaying policy decision subproblem, an energy efficient power control (PC) technique is proposed. Specifically, the binary selective relaying policies are determined for each subcarrier based upon channel state information (CSI), while power loading can be mathematically solved by employing standard Lagrange techniques, leading to analytical solutions for individual transmit powers at the source and the relay. In order to further improve the energy efficiency, an independent \emph{min-min} relay selection policy is investigated by making use of available diversity of the multiple-relay channel. Numerical results illustrate the superiority of the proposed selective AF-OFDM relaying protocol and validate the efficiency of our proposed algorithms. It is shown that with PC, the proposed selective AF-OFDM relaying can significantly reduce the system power consumption, and the \emph{min-min} relay selection policy is more appropriate than the conventional \emph{max-min} strategy for our transmission protocol.

This manuscript develops an improved AF-OFDM (Amplify-and-Forward, Orthogonal Frequency Division Multiplexing) scheme where selective relaying policy is fully utilized to promote the spectrum efficiency of cooperative transmission, and presents an achievable rate maximizing resource allocation strategy subject to a sum-power constraint. The high computational complexity for optimization necessitates our investigation of suboptimal approaches. The proposed centralized algorithms can be implemented in a step-by-step manner. Specifically, the binary selective relaying policies are first decided for each subcarrier according to instantaneous or statistical channel state information. Then, relay selection might be conducted by those subcarriers who would like to choose a relay to assist their data transmission from network achievable rate maximization perspective, and finally power loading can be mathematically solved by employing standard Lagrange techniques. Numerical results are shown to illustrate the benefits of the improved AF-OFDM cooperative protocol with optimized resource allocation.

Wireless world initiative new radio (WINNER) delivers a 3D cross-polarized channel model for B3G/4G system designs. Comprehensive radiation characteristics of polarized antenna are crucial in generating channel coefficients. Being currently supported within WINNER channel model, field patterns are technically obtained by chamber measurement. However, in some channel related performance analysis scenarios, design insight can be crystallized better by starting the derivations with theoretical co-pol and cross-pol components. Specifically, these two components are mathematically linked with field patterns through the proposed polarization projection algorithm. In this paper, we focus on revealing the physical significance of polarization transform between the antenna plane and the propagation plane. In practice, it makes retrieving the field patterns by electromagnetic computation possible. Meanwhile, the impact imposed by distinct antenna orientations is geometrically illustrated and consequently incorporated into the proposed algorithm. The result is analytically verified by the closed-form expression of the dipole field pattern and we find that its 2D degenerative case is aligned with that defined in 3GPP TR 25.996. The benefit is to significantly reduce the cost on generating channel coefficients in WINNER channel simulations.

This manuscript deals with the modeling, analysis, and measurement of a small scale fading (SSF) mobile radio channel. The physics of SSF are first reviewed to reveal the generating mechanisms of channel selectivity. A stochastic channel model is then derived as a function of time, antenna array displacement and frequency, which falls in the category of tapped delay line model. Specifically, the taps can be represented as a combination of a possible line of sight or dominant reflected path and a Gaussian distributed component comprised of unresolvable scattered paths. After that, general analytical solutions are provided for the 3D temporal-spectral-spatial correlations of SSF via the exploitation of channel statistical properties. We show that this function can be expressed as the product of three low order temporal, spectral and spatial correlations individually under appropriate assumptions on the associated wireless propagation environment. This will definitely facilitate the derivations of the closed form expression regarding the correlation function of SSF. From engineering perspective, this analysis can be utilized to develop network correlation maps for example. Finally, out field measurement results verify the validity of our theoretical analysis.

Two-path or successive relaying, which aims to establish two relay links transmitting different information symbols in adjacent time slots, has recently emerged as an attractive wireless communication protocol to improve the spectral efficiency in half-duplex cooperative systems. In this paper, we investigate power allocation and relay selection techniques for amplify-and-forward two-path successive relaying networks. Our approach is based on the maximization of the received SNR subject to a total power budget consumed by the source and the relay assisting this specific transmission. Two scenarios including with and without direct link are considered here. We show that the main problem has a closed-form solution and only requires a few amounts of feedback bits to be broadcasted. Numerical results reveal that the proposed approaches are more insensitive to the inter-relay interference and robust to channel estimation errors; meanwhile, they perform better than the existing schemes. Copyright © 2013 John Wiley & Sons, Ltd.

ABSTRACT We investigate the problem of precoding optimization in an amplify‐and‐forward multiple‐input‐multiple‐output relay system. Most reported works on this problem focus chiefly on the design of relay precoder without simultaneously optimizing the direct link. In this paper, we propose a method for joint source/relay precoder design, taking both direct and relay links into account. Our design is based on maximizing the mutual information (MI) under limited transmission power constraints at the source and relay, respectively. We first formulate a constrained optimization problem before relaxing the original cost function for tractability and derive a MI lower bound. This elaborate bound can asymptotically approach the exact expression of MI in an iterative fashion. In contrast to previous strategies, we then prove that the optimal structure of the source and relay precoders jointly convert the multiple‐input‐multiple‐output relay channel into a bank of single‐input‐single‐output relay channels without having to assume a beamforming structure to simplify the derivation. Specifically, the linear precoding design problem degenerates into power loading among multiple single‐input‐single‐output relay channels. Applying standard Lagrange technique results in a scalar convex optimization, and it can be readily solved by iterative water filling. Numerical examples demonstrate that the proposed scheme, either exploiting partial or full channel state information, significantly outperforms the existing methods. Copyright © 2012 John Wiley & Sons, Ltd.

This paper presents a resource allocation strategy for maximizing the lifetime of amplify-and-forward (AF) dualhop cooperative OFDM networks. The high computational complexity for optimization necessitates our study of suboptimal approaches. Our centralized scheme is implemented in two steps. Specifically, during each transmission interval, source-relay selection and subcarrier pairing can be decided according to channel state information of the relay links and residual energy information at each terminal. Next, energy-aware power loading can be solved by employing standard Lagrange techniques. Numerical examples verify the effectiveness of our proposal.

This paper investigates the multiuser interference mitigation for the uplink of an orthogonal frequency division multiple access system in a doubly selective fading channel. The proposed algorithm squeezes the interference of subcarrier k into 2τ+1 neighboring subcarriers by preprocessing the received signal and yields a banded structure interference matrix. Specifically, the value of τ mainly depends on the carrier frequency offsets and determines the squeezing depth which in turn influences the receiver implementation complexity. Simulation results show that the bit error rate performance of our proposed algorithm approaches the existing full length minimum mean square error equalizer with a significant reduction on complexity.

Multicarrier transmission over time varying frequency selective fading channels is investigated and a model for such a transmission scheme with emphasis on Multiple Input Multiple Output Orthogonal Frequency Division Multiplexing (MIMO-OFDM) systems is developed. The fast fading can destroy the orthogonality of subcarriers and cause serious InterCarrier Interference (ICI), thus leading to significant performance degradation that becomes severe as Doppler shift increases. To tackle this problem, a frequency domain iterative ICI mitigation algorithm is mathematically derived. By fully exploiting the separation property of Channel Transfer Function (CTF) matrix, ICI can be iteratively subtracted from received symbols and then Parallel Interference Cancellation (PIC) detection is performed to suppress multistream interference among different antennas. In particular, the complexity of the proposed strategy can be drastically reduced by restricting the interference computation to limited eighteen adjacent subcarriers, whereas the performance loss is quite minor. Simulation results illustrate that this scheme can effectively alleviate the impairment of ICI and asymptotically approach the ICI free performance at low-to-moderate Signal-to-Noise Ratio (SNR).

We investigate the problem of precoding optimization in an amplify-and-forward (AF) multiple-input-multiple-output (MIMO) relay system. Most reported works on this problem focus chiefly on the design of relay precoder without simultaneously optimizing the direct link. In this paper, we propose a method for joint source/relay precoder design, taking both direct and relay links into account. Our design is based on maximizing the mutual information (MI) under limited transmission power constraints at the source and relay, respectively. We first formulate a constrained optimization problem before relaxing the original cost function for tractability and derive a MI lower bound which asymptotically approaches the exact expression of MI in an iterative fashion. In contrast to previous strategies, we then prove that the optimal structure of the source and relay precoders jointly convert the MIMO relay channel into a bank of single-input-single-output (SISO) relay channels without having to assume a beamforming structure to simplify the derivation. Specifically, the linear precoding design problem degenerates into power loading among multiple SISO relay channels. Applying standard Lagrange technique results in a scalar convex optimization which can be readily solved by iterative water filling. Numerical examples demonstrate that the proposed scheme, either exploiting partial or full channel state information (CSI), significantly outperforms the existing methods.

Multiple input multiple output (MIMO) transceivers can potentially increase overall network throughput via spatial reuse of spectrum by allowing multiple simultaneous communications. Efficient use of MIMO technique in wireless ad hoc networks still meets challenges especially for upper layer protocols. In this paper we propose a cross-layer strategy of allowing the data stream and routing control stream transmitting concurrently with different antennas of the MIMO system. Implementing on the ad hoc on-demand distance vector (AODV) protocol, simulation results show that the strategy of queuing different type of packets obviously decreases the duration of route establishment, especially when the network is suffering heavy traffic load.

Multiple-input multiple-output (MIMO) antennas combined with orthogonal frequency division multiplexing (OFDM) are very attractive for high data rate communications. However, MIMO-OFDM systems are very vulnerable to time selective fading as channel time variation destroys the orthogonality among subcarriers, causing serious intercarrier interference (ICI). In this paper, we employ optimal frequency domain partial response coding (PRC) in MIMO-OFDM systems over frequency selective, fast fading channels to mitigate ICI. We focus on deriving, via an analytical approach, a tractable, closed-form expression of carrier-to-interference ratio (CIR) to quantify the impact of time selective fading and demonstrate the effectiveness of PRC in mitigating ICI in MIMO-OFDM systems. From the numerical results, PRC can effectively increase CIR and the improvement is proportional to the number of subcarriers and the coding length.