In this paper, we jointly consider the problems of constellation design and automatic modulation recognition (AMR) for color shift keying (CSK) and optical orthogonal frequency division multiplexing (OOFDM) in visible light communication (VLC) systems. Specifically, we conceive a solution based on the proposed enhanced complex-valued CSK (ECCSK) aided OOFDM (ECCSK-OOFDM) framework for multi-target-color communication (MTCC) scenarios. Firstly, we devise a complex-valued CSK constellation design method under given color/illumination constraints. The new method not only eliminates the color balance distortion issue, but also achieves a better normalized minimum Euclidean distance (NMED). Secondly, an expectation maximization (EM) based ECCSK constellation recognition algorithm is proposed, which enables the system to automatically identify the ECCSK constellation with unknown symbol timing offset (STO) and noise variance. Simulation results demonstrate the effectiveness of the new ECCSK constellation design method and the EM-based AMR algorithm. It shows that the proposed system can provide a performance close to the ideal benchmark scheme in MTCC scenarios.

Unmanned aerial vehicle (UAV) communication is expected to play an important role in many applications, including emergency services, remote surveillance and even daily logistics, thanks to its great advantages such as flexible deployment and mobility support. In this paper, we propose a multi-UAV-aided communication scheme supported by laser power transfer (LPT), where the quality-of-experience (QoE) requirements of user equipment (UE) is considered. Specifically, to improve the sum QoE, we first maximize the sum of average data rates (ADRs) of all UEs through an alternating optimization of UAVs' positions, UE-network association and LPT station (LPTS)-network association. Then, we devise an advanced Gale-Shapley rematching (GSRM) scheme to address the intractable 0-1 programming problem in UE/LPTS-network association. Moreover, an L2-norm polynomial (L2NP) programming method is designed to transform the L2NP of the LPT-based UAV positioning problem into a convex form. Finally, a redundant resource reallocation (RRR) algorithm is designed to recycle and reallocate the excessive transmit power and backhaul capacity of both the base station (BS) and the UAVs, to further maximize the number of UEs satisfying the QoE requirements. Simulation results show that the proposed UAV-aided communication scheme can help more UEs achieve their QoE requirements at a reduced power consumption compared with existing solutions.

Aeronautical communication (AC) is considered as one of the core technologies for future wireless networks. In practical AC scenarios, the communication links suffer from severe Doppler effect caused by the high mobility of the aerial user equipment (AUE) on the aircraft, resulting in a rapidly time-varying propagation channel. In addition, compared with conventional terrestrial communication systems, an AC system is usually expected to support a much wider cell coverage. In this case, the round trip delay (RTD) of signal transmissions becomes larger and more difficult to be estimated, thus making it challenging to design a reliable random access scheme for AC scenarios. To address the above-mentioned issues, in this paper, we propose a new random access preamble detection algorithm for AC systems. The proposed scheme employs short preamble formats and detects the preamble by exploiting a shifted partial combination mechanism. Thus, it is capable of offering a better detection performance and improved spectral efficiency (SE), while still maintaining a large coverage under high Doppler shifts. Furthermore, we design an RTD estimation approach based on the so-called dual-end correlation operation, which can help to achieve more robust RTD estimates. The superior performance of the proposed technique is verified through both simulations and lab experiments in an emulated challenging scenario, where as many as 30 AUEs traveling at a velocity of 1260 km/h within a cell radius of 200 km can be supported.

The family of aeronautical communication systems is considered as one of the core technologies for the beyond-the-fifth-generation (B5G) networks, thus attracting rapidly increasing attention from both industry and academia. In this paper, a new multiple-input multiple-output (MIMO) precoding scheme is proposed for aeronautical communication systems, where the transmit power for the aerial user equipment (UE) approaching the target cell is maximized based on the direction information. Specifically, we first transform the precoding optimization problem into a linear programming problem, and then develop two algorithms to derive the precoders for two transmission modes, namely the multi-stream and single-stream transmissions. For the multi-stream case, an algorithm based on manifold optimization is proposed, which guarantees the equal power allocation for each antenna. For the single-stream case, we derive a precoder by a numerically stable algorithm that extends the Newton-Raphson method. Simulation results show that the proposed precoding schemes can improve the link performance of the UEs with known directions, while ensuring that the performance of the UEs with unknown directions can still be close to that achievable by conventional schemes.

Massive multiple-input multiple-output (M-MIMO) aided positioning technologies have been recently recognized as promising solutions to fulfil the high accuracy requirement of indoor localization systems. In this paper, exploiting a distributed M-MIMO framework, we propose to employ a deep belief network (DBN) to analyze the received signal strengths (RSS) generated by a diffraction model, where the impact from interfering persons on the targeted user equipment (UE) is considered. Next, the preliminary DBN estimates are forwarded to a long-short term memory network (LSTMN), where the trajectory information of the targeted UE can be extracted based on much less historical trajectory information than existing solutions. Then, the three-dimension (3D) coordinates of the UE’s positions can be estimated with a back propagation neural network (BPNN) which combines the outputs of DBN and LSTMN. Finally, extensive simulation results are provided to demonstrate the effectiveness of the proposed BPNN scheme.

Among the proliferation of device-to-device (D2D) based caching schemes, the most popular content (MPC) caching and the largest content diversity (LCD) caching have recently gained research attention. By jointly exploiting the merits of both MPC, LCD and grouped caching strategies, in this paper, we propose a new multi-popularity multi-threshold grouped caching scheme for D2D communication (MMGC-D2D). Specifically, we first devise an optimal device grouping scheme aiming to improve the regional user fairness of grouped caching. Then, to maximize the gain of cache space and to minimize the outage probability of cached packets, we discuss in details a novel MPC-LCD threshold-based grouped caching placement optimization problem and its analytical property, while taking into account the packet request diversity (PRD). Simulations results show that the proposed scheme exhibits notable gains over existing methods.

Underwater wireless optical communication (UWOC) has been recently proposed for high-rate data services. In underwater scenarios, the channel conditions are complicated due to various effects of the water waves, such as absorption, scattering and turbulence, which exhibit different statistical properties with diverse water types. Such capricious phenomena make channel estimation (CE) and signal detection (SD) become challenging issues for high-rate and reliable transmissions. To address these challenges, we devise a deep learning (DL) based joint channel classification (CC), CE and SD scheme for UWOC systems. Different from existing systems, where CE is typically an independent and fundamental module, we combine CE with SD by utilizing a new deep neural network (DNN). Furthermore, the proposed scheme exploits the channel characteristics extracted through an offline training powered by a new robust DNN channel classifier (CC), which can identify and classify the water types online to produce optimized estimated combinational weights (ECW) for improving the CE/SD performances under time-varying UWOC channels. Simulation and experimental results demonstrate the superiority of the proposed system in terms of link performances in various UWOC channel environments.

In this paper, we propose a novel visible light positioning (VLP) scheme under multi-path propagation, which is a practical scenario that has not been well studied for VLP. The new scheme exploits the so-called dual-mode light-emitting diode (DM-LED) of different radiation lobe mode numbers at the transmitter and a photodiode at the receiver. Specifically, we devise a method that utilizes a radiation angle measurement approach for DM-LED, derive the Cramér-Rao lower bound (CRLB) of the estimated distance and analyze the characteristics of key parameters. In addition, two localization algorithms based on linear and nonlinear least squares methods are developed. Simulation results show that under the ideal light-of-sight scenario, the CRLB of the proposed VLP scheme can be close to that of the conventional received signal strength (RSS) aided VLP scheme. Furthermore, we implement the first ever prototype DM-LED lamp to validate the new DM-LED aided VLP system model. Both simulation and experiment results demonstrate that the proposed system outperforms its RSS-aided VLP counterpart in terms of positioning accuracy in the more realistic, and thus more challenging multi-path scenario, even with a tilting receiver.

In practical underwater visible light communication (UVLC) scenarios, the communication links inevitably suffer from many stochastic channel effects including multi-path dispersion, scattering, turbulence, etc., and/or from the mobility of the transceiver, therefore resulting in a time-varying, location dependent non-stationary propagation environment. Naturally, how to design a cost-efficient channel estimation (CE) for UVLC systems becomes a significant technical challenge, due to the complicated channel characteristics and implementational constraints in underwater environment. In this paper, we propose a class of Bayesian CE algorithms for fractionally-sampled optical orthogonal frequency division multiplexing (FS-OOFDM) assisted UVLC systems. The so-called Sherman-Morrison formula (SMF) based CEs (SMF-CEs) exploit the property of rank-one structure of the channel covariance and autocorrelation matrices in the delay domain, to achieve a superior performance at a modest computational complexity.

Aeronautical communication (AC) has recently attracted increasing research interests because of the growing demand of on-board data transmission. However, in this high-mobility scenario, channel estimation (CE) is a challenge due to the large Doppler shift effect. In this paper, a new CE algorithm exploiting the a priori delay information is proposed for AC systems. Specifically, the proposed algorithm approximates the channel based on the basis expansion model (BEM) and estimates two salient paths according to the sparse characteristic of aeronautical channels. As a result, the computational complexity of the CE can be effectively reduced. Furthermore, noting that the delay depends on the geographical paths, a coarse estimation is firstly performed to obtain the delay. Then, while such an a priori delay is used as a coarse estimate, the accurate delay is detected by the peak value indices (PVI) of the instantaneous signal frequency correlation (SFC) at the receiver. Simulation results validate that the proposed scheme outperforms the traditional BEM algorithms, even at a user equipment (UE) mobility of as high as 1020m/s.

Recently, visible light communication (VLC) has attracted increasing research interests, thanks to its notable advantages including for example abundant spectra, simultaneous illumination and communication, radiation-free deployment, etc. Benefitting from the widely availability of light emitting diode (LED), the VLC systems employing LED arrays are ready to exploit the multiple-input multiple-output (MIMO) technologies, where a high degree-of-freedom in, for example, the precoding design can be utilized for system performance enhancement. In this paper, we propose a new precoding scheme for multiuser (MU) MIMO-VLC systems, where the classical block diagonalization precoding (BDP) technique is applied based on the properties of the LED’s dynamic range. The resultant weight-adjusted BDP (WA-BDP) scheme generates an interference-free matrix by the traditional BDP approach, and then tunes the weights of the LEDs such that improved channel gains can be obtained. We verify the theoretical analysis by simulation results, which demonstrate the superiority of the proposed scheme in terms of the bit error rate (BER) performance.

Device-to-device (D2D) based packet caching technologies recently attract increasing attention, thanks to their great potentials to facilitate network traffic offloading. Despite the many popular issues arising in the D2D caching area, one of the new perspectives, namely the competition due to the packet request diversity originating from various D2D user equipment (UE) groups is not sufficiently investigated. In this work, we analyze several key aspects of the competition for packet allocation among diverse packet requests. Firstly, we study the impact from diverse group proportions on the system throughput and the packet allocation fairness. Particularly, the novel group separation index (GSI) is introduced, which helps to reflect the packet allocation fairness. We derive and analyze both the upper and lower bounds of GSI. Secondly, we investigate how the concentration levels of diverse packet requests may affect the system performance, such as the impact from the caching size limit on packet allocation. Thirdly, we derive the average energy consumption metric using the binomial point process based network model, which facilitates a comprehensive evaluation of the competition among UE groups. Finally, simulations validate our proposed analysis method, which may provide important design hints for improving existing D2D caching schemes.

In this paper, the new family of spherical color-shift keying (SCSK) constellations is proposed for visible light communication (VLC) systems. Specifically, the constant-intensity constraint (CIC) for conventional color-shift keying (CSK) schemes, which originates from the requirement of non-flickering illumination, confines the constellation symbols on a two-dimensional (2D) plane of the three-dimensional (3D) intensity space. To fully utilize the potential degree of freedom offered by the 3D intensity space, we propose to expand the envelope of CSK constellations by replacing the constant intensity with a new spherical intensity constraint, aiming to maximize the minimum Euclidean distance (MED). More explicitly, we design the robust SCSK constellations with and without white color balance (CB), respectively. Particularly, we transform the constellation design problem to the so-called spherical circle packing (SCP) problem, which is resolved based on the spherical quasi-physical (SQP) model. Then, we propose the so-called spherical heuristic quasi-physical algorithm (SHQPA) integrating the binary search algorithm (BSA) and the configuration update algorithms (CUA) to obtain the optimal SCSK constellations. Furthermore, we also study the corresponding bit-to-symbol mapping rules for the generated SCSK constellations. Simulation results show that the new family of SCSK constellations outperforms the conventional CSK counterparts.

In this paper, a novel visible light positioning (VLP) system is proposed. The new system includes multiple dual-mode light-emitting diode (DM-LED) lamps with different radiation lobe mode numbers (RLMN) and a user device equipped with a photodiode (PD). Specifically, a method utilizing a radiation angle measurement (RAM) approach for DM-LED is devised, and the characteristics of key system parameters are studied, taking into account multi-path reflections in practical indoor VLP scenarios. Furthermore, two localization algorithms based on linear and nonlinear least squares methods are developed. Simulation results show that the proposed system significantly outperforms its conventional counterpart in terms of positioning accuracy under the challenging multi-path scenario.

This paper proposes multilevel Reed-Solomon (MRS) codes and their iterative multistage soft decoding (IMSD) for visible light communication (VLC), realizing both high decoding performance and transmission spectrum efficiency. The proposed IMSD algorithm decodes the MRS codes level-by-level through iterating either hard decisions or extrinsic information of RS coded bits. Each level RS decoding is realized by cascading the adaptive belief propagation (ABP) algorithm that produces the extrinsic information and the Berlekamp-Massey (BM) algorithm that estimates the codeword. The earlier level decoding provides better a priori information for the later ones. A complexity reducing IMSD (CR-IMSD) algorithm is also proposed to facilitate the decoding. This paper further investigates a joint design of color-shift keying (CSK) constellation and the MRS code, optimizing the decoding performance. The CSK constellation is designed by considering both the set partitioning (SP) criterion and the harmonic mean of constellation's minimum squared Euclidean distance (MSED). The MRS codes are further designed using the capacity and the equal error probability rules. Our simulation results show that the IMSD algorithm achieves significant iterative decoding gains. The performance of the designed MRS code is 0.3 dB away from the capacity limit at the bit error rate (BER) of 10-9.

Among the numerous channel estimation (CE) techniques in the literature, pilot-aided channel estimation (PACE) has been widely employed, with the aid of various interpolation methods for reducing pilot overhead. Conventional linear interpolation (LI), polar linear interpolation (PLI) and adaptive polar linear interpolation (APLI) methods are easy to implement, but naturally result in residual interpolation errors at high signal-to-noise ratios (SNR). In this paper, we propose an effective origin optimisation aided APLI CE (EOO-APLI-CE) method, which outperforms existing schemes of similar complexity, through both inheriting the benefits offered by conventional APLI and further reducing the residual error floors. Moreover, the proposed real-time EOO-APLI-CE scheme can adapt to any channel model, without the need of channel-model-specific optimisation required, for example, by the conventional APLI method. Last but not least, it maintains a complexity as low as the traditional LI method.

Colour shift keying (CSK) and optical orthogonal frequency division multiplexing (OOFDM) are among the promising high-rate transmission technologies for visible light communication (VLC). Existing methods that combine CSK and OOFDM typically assume the use of conventional CSK constellations such as those defined by the IEEE 802.15.7 standard. However, such a straightforward CSK-OOFDM combination distorts the colour balance and the modulated VLC signal is therefore no longer white. In this paper, we design optimised CSK constellations that work in the complex domain under a given colour constraint. Simulation results demonstrate the effectiveness of the new design method, which not only produces new constellations with an improved normalised minimum Euclidean distance (NMED) compared with the traditional counterparts, hence improves the achievable bit error rate (BER) performance, but also eliminates the colour balance distortion issue of conventional CSK-OOFDM systems.

Applying sociality-aware (SA) device-to-device (D2D) user equipment (UE)-to-network (UE-NW) relay can help to improve UEs' accessibility to the network, thus increasing the network coverage and capacity. In this context, one key issue is the design of the relay helper UE (HUE) selection procedure. However, few existing studies jointly consider the diverse impacts from various design criteria on the performance of HUE selection. In this paper, the sociality-aware D2D UE-NW relay selection (RS) issue is formulated as a constrained multi-objective binary integer linear programming (MOBILP) problem, which can be solved by the proposed SA-D2D-RS method. Specifically, the new solution jointly exploits the fuzzy analytic hierarchy process (FAHP) and the entropy weight generation method that provides both subjective and objective preferences in decision making. Simulation results validate the superiority of the proposed scheme through realistic social data traces, and demonstrate its high access ratio as well as system throughput.

Indoor location based service (LBS) has become one of the key enablers for the mobile internet era. The challenging indoor localisation problem may be solved by the emerging visible light positioning (VLP) techniques which exploit light-emitting diode (LED) to transmit beacon signals. In this paper, we propose a general VLP system which invokes an imaging receiver, an off-the-shelf LED lamp and a commercial user equipment (UE) employing a rolling shutter aided complementary metal-oxide semiconductor (CMOS) based image sensor (CIS). Particularly, we design an asynchronous framework based on Miller coding, which efficiently solves the synchronisation problem. Furthermore, we provide a detailed analysis on a discrete Fourier transform (DFT) aided LED flicker frequency detection algorithm. Extensive measurement and simulation results are also offered.

Device-to-device (D2D) multicast retransmissions in cellular networks helps to improve spectral efficiency and to offload traffic. Existing methods have revealed the relationship between the number of relays and resource utilisation efficiency on retransmissions in terms of relay selection and clustering. However, few studies consider the impact from the lost packets on resource utilisation, which is however important for improving the overall efficiency of D2D systems. In this paper, we first formulate a general resource efficiency optimisation problem in D2D multicast retransmission scenario, where the lost-packet diversity (LPD) of remote user equipments (UE) and link quality of D2D links are jointly considered. Then, we propose an efficient near-optimal algorithm to solve the new optimisation problem. Simulation results validate the benefits of the proposed algorithm which provides a near-optimal performance at low complexity.

In this paper, we present a new equalizer based on probabilistic neural networks (PNN) for visible light communication (VLC) systems. While traditional artificial neural networks (ANN) type equalizers have to identify the distribution of the received signal, in our method kernel density estimation (KDE) is exploited to obtain the probability density function (PDF) of the states of the received signal, which reduces the computational complexity, especially when severe inter symbol interference (ISI) exists and when the number of signal states in the observation space increases. Then the constructed PDF is used to find the optimal Bayes solution at the receiver. Moreover, the decision feedback (DF) mechanism is utilized for further performance enhancements. The simulated bit error rate (BER) performances of the presented PNN based equalizers are compared with linear equalizer (LE) and conventional decision feedback equalizer (DFE). Simulation results demonstrate that the PNN-based equalizer without and with DF outperform LE and conventional DFE, respectively, thanks to the employment of KDE.

Visible light communication-based schemes utilizing LED identifiers are among the most popular candidate solutions for indoor localization applications. In this paper, we design a comprehensive imaging visible light positioning system, which exploits off-the-shelf LED lamps and commercial user equipment employing a rolling shutter aided CMOS image sensor. More specifically, we first introduce an asynchronous oversampled multi-image detection scheme inspired by the rationale of Miller coding, which efficiently solves the synchronization problem in transmissions of LED identifiers. Then, a discrete Fourier transform aided LED flicker frequency detection algorithm is detailed for robust single-image detection. Furthermore, we extend the proposed method to a space-time-multiplexing framework, which improves the overall transmission rate and solves the problem of detecting the user's moving direction. The notable advantages of the new solution are demonstrated through both practical measurements and computer simulations, exhibiting a robust transmit distance beyond three meters for continuous frames.

Visible light communication (VLC) is considered as a potential candidate of five generation (5G) technologies and thus attracts increasing research interest recently. Optical orthogonal frequency division multiplexing (O-OFDM) has been proposed for VLC systems to eliminate the multi-path interference, while also facilitating frequency domain equalisation (FDE). In comparison to conventional radio frequency (RF) based wireless communication, there has been limited considerations on channel estimation (CE) for VLC, where the indoor optical wireless channel model differs from the traditional RF case. In this paper, we present a new channel estimation algorithm for indoor downlink (DL) VLC systems that exploits historical information in an adaptive and efficient way. The proposed scheme is capable of offering superior performance at the cost of modest complexity under practical scenarios. Detailed theoretical analysis is provided along with extensive numerical results, demonstrating the effectiveness of the proposed CE approach.

In this paper, we propose a novel indoor multi-user (MU) multiple-input multiple-output (MIMO) optical orthogonal frequency division multiplexing (OOFDM) aided visible light communication (VLC) system. By using light-emitting diodes (LEDs) for both illumination and data transmission, the system employs imaging receiver (ImR) to reduce the MIMO channel correlation. Moreover, a new photodetector selection (PDS) technique is invoked, which helps to further mitigate the channel correlations across the multiple PDs of the same user equipment (UE) or those between the UEs. Through both analytical study and numerical simulations, the bit error rate (BER) performances are evaluated. It is shown that our proposed design can enhance the VLC system's performance, especially when UEs are extremely close.

Optical spatial modulation (OSM) follows the concept of spatial modulation (SM) and inherits the latter's benefits such as inter-channel interference (ICI) avoidance, etc. However, it suffers in high optical channel correlation in typical indoor multiple-input multiple-output (MIMO) visible light communication (VLC) environment. In this paper, we incorporate colour shift keying (CSK) modulation standardised in the IEEE 802.15.7 standard for high speed VLC into an OSM VLC system, resulting in a new hybrid CSK-OSM-VLC scheme. By separating the data bit stream to independent CSK and OSM bit streams, the hybrid system avoids the use of higher-order single modulation for satisfying a certain data rate requirement. Furthermore, it also enjoys the advantages from both the spatial gain provided by OSM and the increased data rates by CSK, as compared to the individual conventional CSK or OSM VLC systems. The said benefits are demonstrated through extensive computer simulations and performance comparisons.

Visible light communication (VLC) networks can provide high‐rate transmissions with advantages such as high security, low power consumption and so on. Multiple users get access to the VLC network according to the carrier sense multiple access with collision avoidance (CSMA/CA) mechanism defined by IEEE 802.15.7 media access control layer specifications. In this study, the authors propose an energy efficient medium access scheme to improve the performance of IEEE 802.15.7 CSMA/CA mechanism under unsaturated traffic conditions. Aiming at reducing the power consumed on unnecessary waiting and at improving the channel utilisation efficiency, they first apply a successive transmission scheme on the node, which has completed one successful transmission and gets the chance of transmitting the next packet without backoff delay period according to the network condition. Then, a dynamic contention window is exploited to mitigate the collisions, where they derive the optimal minimum contention window based on throughput analysis. The power consumption can be reduced with improved throughput, when both the traffic load and the number of nodes in the network are taken into account. Simulation results demonstrate that the authors’ proposed scheme outperforms the IEEE 802.15.7 CSMA/CA scheme with respect to the average power consumption, system throughput and packet dropping probability.

Abstract To effectively reduce the inter‐relay interference (IRI) in two‐path successive relaying, two beamforming schemes are proposed in this paper, utilizing multiple‐antenna relay nodes. Specifically, the two cooperation nodes perform receive combining of the source signal and transmit beamforming of the relayed signal alternately in the successive relaying process. As a result, the IRI between them can be effectively suppressed, thanks to the additional degree of freedom provided by the multiple‐input multiple‐output inter‐relay channel. In the first beamforming scheme, the source‐to‐destination signal‐to‐interference‐plus‐noise ratios (SINR) of separate paths are maximized with approximation, leading to a minimum variance distortionless response beamformer under the high SINR condition. To further improve the system performance, noting that the received SINRs of the two paths have impact on each other due to the mutual coupling of the beamformers, the sum of mean squared errors from these two transmission paths is minimized in the second scheme. Based on this performance criterion, a suboptimal beamformer design is developed numerically through cyclic minimization of the sum of mean squared error cost function. Simulation results demonstrate the superiority of both proposed beamforming schemes in terms of symbol error rate and the achievable system rate, in particular, at high IRI levels. Copyright © 2016 John Wiley & Sons, Ltd.

The achievable performance of successive relay system will significantly degrade, if severe inter- relay interference (IRI) exist. In this paper, two beamforming methods are proposed for mitigating the IRI inflicted by multiple-input multiple-output (MIMO) assisted two-path successive relay nodes. More specifically, we exploit the additional degree of freedom offered by the spatial domain during the alternate transmission process across consecutive time slots in the relay system. The first method aims to maximize the source-to-destination signal- to-interference-plus-noise ratios (SINR) of separate transmission paths with the aid of a minimum variance (MV) beamformer under the high SINR condition. The second method constitutes a near- optimum beamformer design attempts to minimize the sum of mean squared errors (MSEs) at the destination node by exploiting the mutual coupling of SINRs received from the different transmission paths. Numerical results prove the benefits of our proposed beamforming schemes, especially under the presence of high IRI.

In amplify-and-forward (AF) type relaying assisted orthogonal frequency division multiplexing (OFDM) systems, channel estimation (CE) is a challenging task due to the increased frequency selectivity caused by the cascaded source-to-relay-to-destination$(S\rightarrow R\rightarrow D)$multipath channel. Typically, such cascaded channels result in severe time dispersion. Consequently, it requires additional pilot overhead for CE as well as longer cyclic prefix (CP) for eliminating the inter-symbol interference (ISI), which will inevitably reduce the achievable diversity provided by cooperative transmissions. In this letter, a three-step CE scheme is proposed without the need of increasing pilot overhead. Furthermore, by reconstructing the CP at the relay node, the CP length does not necessarily need to be extended for the cascaded channel. Simulation results demonstrate the effectiveness of our proposed scheme even in severely time-dispersive multipath fading channels.

Linear Dispersion Codes (LDCs) have recently attracted numerous research interests. Thanks to their efficient spreading of data across both the time and spatial domains, LDCs are capable of achieving a desired Diversity-Multiplexing Trade-off (DMT) in Multiple Input Multiple Output (MIMO) broadband wireless access systems. This paper proposes a novel LDC design method, which relies on the unitary matrix theory combined with a Genetic Algorithm (GA) aided optimization procedure. The proposed design provides a flexible framework, where new LDCs attaining higher data rates and better error resilience than a number of classic MIMO schemes can be generated.

Linear dispersion codes (LDCs) are capable of achieving a good trade-off between link throughput and link robustness in multiple input multiple output (MIMO) broadband wireless access systems. This is thanks to their efficient spreading of data across both time and space domains. This paper proposes a novel LDC design method utilising the unitary matrix theory along with a genetic algorithm (GA). The proposed design framework can produce LDCs attaining higher data rates and better error protection than various well-known MIMO schemes, such as the Alamouti space-time code and spatial multiplexing (SM).

The combination of multiple-input multiple-output (MIMO) technology and orthogonal frequency division multiplexing (OFDM) has been considered as an attractive solution for the next generation wireless communication networks. In comparison with single-input single-output (SISO) systems, channel estimation in the MIMO scenario becomes more challenging, owing to the increased number of independent transmitter-receiver links to be estimated. In this paper, we introduce an enhanced iterative channel estimation method, which is capable of providing genetically optimized channel information for uplink multi-user MIMO OFDM receivers, approaching the optimal benchmark arrangement utilizing perfect channel knowledge. The effectiveness of the proposed scheme is demonstrated by a range of numerical results under realistic scenarios.

Despite the assistance of well-recognized hot technologies such as Multiple-Input Multiple-Output (MIMO) and Orthogonal Frequency Division Multiplexing (OFDM), cell-edge mobile users still suffer significant performance degradation in uplink, thus restricting the system coverage. In the context of the European B3G/4G WINNER system, we propose a hybrid solution which takes the advantages of both Genetic Algorithm (GA) and turbo processing, resulting in an enhanced MIMO OFDM receiver. Simulation results show that the proposed scheme is capable of achieving a good link performance, whilst improving the robustness of the multi-links and thus the cell coverage.

This overview portrays the evolution of orthogonal frequency division multiplexing (OFDM) research. The amelioration of powerful multicarrier OFDM arrangements with multiple-input multiple-output (MIMO) systems has numerous benefits, which are detailed in this treatise. We continue by highlighting the limitations of conventional detection and channel estimation techniques designed for multiuser MIMO OFDM systems in the so-called rank-deficient scenarios, where the number of users supported or the number of transmit antennas employed exceeds the number of receiver antennas. This is often encountered in practice, unless we limit the number of users granted access in the base station's or radio port's coverage area. Following a historical perspective on the associated design problems and their state-of-the-art solutions, the second half of this treatise details a range of classic multiuser detectors (MUDs) designed for MIMO-OFDM systems and characterizes their achievable performance. A further section aims for identifying novel cutting-edge genetic algorithm (GA)-aided detector solutions, which have found numerous applications in wireless communications in recent years. In an effort to stimulate the cross pollination of ideas across the machine learning, optimization, signal processing, and wireless communications research communities, we will review the broadly applicable principles of various GA-assisted optimization techniques, which were recently proposed also for employment in multiuser MIMO OFDM. In order to stimulate new research, we demonstrate that the family of GA-aided MUDs is capable of achieving a near-optimum performance at the cost of a significantly lower computational complexity than that imposed by their optimum maximum-likelihood (ML) MUD aided counterparts. The paper is concluded by outlining a range of future research options that may find their way into next-generation wireless systems.

In this contribution, a nonlinear hybrid detection scheme based on a novel soft-information assisted genetic algorithm (GA) is proposed for a turbo convolutional (TC) coded space division multiplexing (SDM) aided orthogonal frequency division multiplexing (OFDM) system. Our numerical results show that the performance of the currently known GA-assisted system can be improved by about 2 dB with the aid of the GA's population-based soft solution, approaching the optimum performance of the soft-information assisted maximum likelihood (ML) detection, while exhibiting a lower complexity, especially in high-throughput scenarios. Furthermore, the proposed scheme is capable of achieving a good performance even in the so-called overloaded systems, where the number of transmit antennas is higher than the number of receiver antennas

Multiple-input-multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) systems have recently attracted substantial research interest. However, compared to single-input-single-output (SISO) systems, channel estimation in the MIMO scenario becomes more challenging, owing to the increased number of independent transmitter-receiver links to be estimated. In the context of the Bell layered space-time architecture (BLAST) or space division multiple access (SDMA) multi-user MIMO OFDM systems, none of the known channel estimation techniques allows the number of users to be higher than the number of receiver antennas, which is often referred to as a "rank-deficient" scenario, owing to the constraint imposed by the rank of the MIMO channel matrix. Against this background, in this paper we propose a new genetic algorithm (GA) assisted iterative joint channel estimation and multi-user detection (GA-JCEMUD) approach for multi-user MIMO SDMA-OFDM systems, which provides an effective solution to the multi-user MIMO channel estimation problem in the above-mentioned rank-deficient scenario. Furthermore, the GAs invoked in the data detection literature can only provide a hard-decision output for the forward error correction (FEC) or channel decoder, which inevitably limits the system's achievable performance. By contrast, our proposed GA is capable of providing "soft" outputs and hence it becomes capable of achieving an improved performance with the aid of FEC decoders. A range of simulation results are provided to demonstrate the superiority of the proposed scheme.

Multiple-input-multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) systems have recently attracted substantial research interest. However, compared to single-input-single-output (SISO) systems, channel estimation in the MIMO scenario becomes more challenging, owing to the increased number of independent transmitter-receiver links to be estimated. In the context of the Bell layered space-time architecture (BLAST) or space division multiple access (SDMA) multi-user MIMO OFDM literature, no channel estimation technique allows the number of users to be higher than the number of receiver antennas, which is often referred to as an "overloaded" scenario. In this contribution we propose a new genetic algorithm (GA) assisted iterative joint channel estimation and multi-user detection approach for MIMO SDMA-OFDM systems, which exhibits a robust performance in the above-mentioned overloaded scenario. Furthermore, GA-aided multi-user detection (MUD) techniques found in the literature can only provide a hard-decision output, while the proposed GA is capable of providing "soft" outputs, hence achieving an improved performance with the aid of channel decoders. Finally, a range of simulation results are provided to demonstrate the superiority of the proposed scheme

In this contribution, a nonlinear hybrid detection scheme based on a novel soft-information assisted genetic algorithm (GA) is proposed for a turbo convolutional (TC) coded space division multiplexing (SDM) aided orthogonal frequency division multiplexing (OFDM) system. Our numerical results show that the performance of the currently known GA-assisted system can be improved by about 2 dB with the aid of the GA's population-based soft solution, approaching the optimum performance of the soft-information assisted maximum likelihood (ML) detection, while exhibiting a lower complexity, especially in high-throughput scenarios. Furthermore, the proposed technique is capable of achieving a good performance even in the so-called overloaded systems, where the number of transmit antennas is higher than the number of receiver antennas