Reconfigurable Intelligent Surface (RIS) technology is designed to improve channel propagation and, in turn, the performance of wireless communication systems. The extent of the improvement heavily relies on the phase shift optimization, a.k.a. passive beamforming design, at the RIS. This paper proposes novel approaches for simplifying this process in large RIS-aided multiple-input multiple-output (MIMO), a.k.a. MIMO-RIS, systems. More specifically, we derive two novel simplified closed-form approximations (CFAs) of the MIMO-RIS capacity expression in the large number of elements/antennas asymptotic regime and identify various scenarios for which they tightly approximate the classic MIMO-RIS capacity expression. We then design two novel simplified RIS phase optimization algorithms for lossless and practical metasurfaces with reduced computational complexity. We also demonstrate that, in certain practical scenarios, very simple guidelines can be used for setting the phases of MIMO-RIS systems. Numerical evaluations validate the accuracy of our CFAs and simplified RIS phase-shift optimization algorithms. They also show that our simplified approaches can deliver either similar or even better capacity performance than existing methods, especially for practical metasurfaces, in various scenarios.

With the anticipation of sixth-generation (6G) networks escalating, the integrated sensing and communication (ISAC) and millimeter-wave (mmWave) unmanned aerial vehicle (UAV) communications emerge as the key focus areas. This paper presents an innovative approach to ISAC waveform design tailored for mmWave UAV communications. The orthogonal chirp division multiplexing (OCDM), characterized by a brunch of orthogonal chirp signals, is firstly introduced in UAV scenarios to offer dual sensing and communication functionalities.We propose an holistic waveform design which incorporates OCDM with the state-of-the-art mmWave frequency-modulated continuous wave (FMCW) radar. Specifically, one subcarrier in OCDM is chosen as the dedicated sensing signal to facilitate the FMCW processing at the UAV receiver, while the rest of OCDM subcarriers can be used to enhance communication data rate. Such OCDM-FMCW scheme significantly reduces the required hardware complexity, particularly in analog-to-digital converter, which provides an energy-efficient ISAC solution for the resource-constraint UAVs. Simulation results demonstrate the effectiveness and superiority of the proposed scheme. It can surpass traditional methods like OFDM and OTFS, by trading off the sensing performance, communication performance, and hardware complexity.

The reflective elements on a reconfigurable intelligent surface (RIS) can be tuned to improve the propagation environment and, in turn, the system performance. However, RIS also brings challenges in terms of joint active and passive beamforming optimization. First, transmit beamforming has to be jointly designed with RIS to fully reap beamforming gain and signal-to-interference plus noise ratio (SINR) performance. Also, given that the number of beamforming options grows with the number of antennas/elements on the base station(BS)/RIS, it makes exhaustive search unpractical for multi-user (MU) multiple-input-multiple-output (MIMO) systems. In order to reduce the search overhead for joint BS and RIS beamforming optimization, we propose a novel joint active BS and passive RIS beamforming scheme based on a bespoke convolutional neural network (CNN) architecture. More specifically, we develop a fast converge and lightweight CNN with loss function designed based on the probability density function (PDF) of beams. By using this CNN, exhaustive search is only needed in data collection part to derive labels and no longer needed in prediction part. We also adopt a realistic blockage scenario to simulate non-stationary channels. Our proposed solution exhibits fast convergence speed, low neural network (NN) complexity and high prediction accuracy. Simulation results, based on benchmark dataset, show that our approach can significantly outperform comparable existing machine learning algorithms. It can achieve 70% shorter convergence time with around 91% beam prediction accuracy.

In the next generation of communication networks (i.e. 6G), metamaterial-based antenna designs, such as Reconfigurable Intelligent Surface (RIS), will be critical for improving wireless communication systems. This paper investigates the ergodic capacity of RIS-aided multiple input multiple outputs (MIMO) systems in the presence of a direct link between the transmitter and receiver. We obtain an exact expression for the ergodic capacity of the cooperative MIMO-RIS systems (along with the corresponding probability density function of the cooperative MIMO-RIS channel) assuming that the receiver is capable of treating the RIS and direct link contributions in the received signal separately. Furthermore, we demonstrate that in the absence of this capability, the resulting formula is a tight upper bound that becomes increasingly tighter with greater numbers of RIS elements. In addition, we pose a simplified capacity expression for large numbers of RIS elements, which provides further insights into the behaviour of the cooperative MIMO-RIS capacity. To gain more insights, we also include a high SNR approximation. Our simulation results confirm the correctness of our expressions and illustrate how the SNR and the number of RIS elements impact the ergodic capacity.

The reflective elements on an intelligent reconfigurable surface (IRS) can be tuned to improve the propagation environment and, in turn, the system performance, provided reliable channel information. However, IRS also brings challenges in terms of channel estimation by creating a very large dimensional channel between the IRS and the transmitter/receiver. A channel size being proportional to the number of users, user equipments (UE) antennas, IRS phase shifters, base station (BS) antennas, in an IRS-aided multi-user (MU) multiple-input-multiple-output (MIMO) system. Estimating such a large channel implies a huge amount of training overheads when all IRS phase shifters are passive, or requires extra power consumption and prohibitive hardware complexity, when IRS phase shifters are active. To tackle these challenges, this paper proposes a practical channel estimation process, based on a realistic codebook design constraint, for optimizing the IRS reflective elements in a MU-MIMO scenario. More specifically, we propose two novel machine-learning based algorithms (i.e. a deep supervised and a deep reinforcement) for optimizing the reflective elements of a typical passive IRS as well as a reliable channel estimation technique for IRS. Deep Supervised network uses exhaustive search to try every reflection pattern to train the network while the reinforcement network uses Q-learning to get the best reward. Our two algorithms can use the imperfect estimated channel knowledge to optimize the IRS in terms of sum-rate or minimum rate among all users. Simulation results show that our practical algorithms can achieve sum-rate and minimum rate performances close to the theoretical ones.

On the one hand, the number of wireless personal devices (WPDs) owned by individuals has soared in the last five years. On the other hand, WPDs exposed their users to electromagnetic field (EMF) radiation that has been linked with possible adverse physiological effects. In this paper, we first provide a generic analytical framework for modelling the exposure generated by WPDs having two transmit antennas. Our model is based on reliable exposure data for different types of human dielectric properties; its accuracy is showcased via simulations. We then integrate this model in an optimization framework for minimizing the exposure, while meeting spectral efficiency (SE) requirements, by means of beamforming. Results show the existence of a trade-off between the specific absorption rate (SAR) and SE, such that our exposure minimization beamforming approach can reduce the exposure by at least 27% by trading-off only 1% of the SE when compared to the optimal SE-based beamforming approach. In addition, they also indicate that increasing the number of antennas at the receiver side can help to further reduce the exposure generated by WPDs.

This paper proposes a novel unipolar transceiver for visible light communication (VLC) by using orthogonal waveforms. The main advantage of our proposed scheme over most of the existing unipolar schemes in the literature is that the polarity of the real-valued orthogonal frequency division multiplexing (OFDM) sample determines the pulse shape of the continuous-time signal and thus, the unipolar conversion is performed directly in the analog instead of the digital domain. Therefore, our proposed scheme does not require any direct current (DC) biasing or clipping as it is the case with existing schemes in the literature. The bit error rate (BER) performance of our proposed scheme is analytically derived and its accuracy is verified by using Matlab simulations. Simulation results also substantiate the potential performance gains of our proposed scheme against the state-of-the-art OFDM-based systems in VLC; it indicates that the absence of DC shift and clipping in our scheme supports more reliable communication and outperforms the asymmetrically clipped optical-OFDM (ACO-OFDM), DC optical-OFDM (DCO-OFDM) and unipolar-OFDM (U-OFDM) schemes. For instance, our scheme outperforms ACO-OFDM by at least 3 dB (in terms of signal to noise ratio) at a target BER of 10-4, when considering the same spectral efficiency for both schemes.

Drone networks offer rapid network deployment to areas that can pose access difficulty. This paper investigates the deployment of multi-hop drone-based unmanned aerial vehicles networks with a focus on the self-organization aspect. When rescue drones carry out their rescue operations which may fly faraway from the gateway, relay drones are autonomously deployed to maintain connectivity. We study the multiple dedicated connections where each rescue drone is connected to the gateway via dedicated relay drones. We show that this approach lacks sharing of relay drones and thus requires more relay drones. We then propose a centralized greedy algorithm and a distributed solution to significantly reduce the number of relay drones. We show that while the distributed self-organized drones (DSOD) solution requires a slightly higher number of relay drones than the greedy algorithm, it eliminates the need for global message exchange which makes it attractive for practical use.

The spatially-incoherent radiators in visible light communication (VLC) constrain the optical carrier to be only driven by a real electrical sub-carrier, which cannot be quadrature modulated as in classic RF-based communication systems. This, in turn, severely limits the transmission throughput of VLC systems. To overcome this technical challenge, a novel coherent transmission is proposed. As such, the optical carrier is only treated as a purely amplitude- modulated carrier capable of transmitting the quadrature modulated symbols. The ability of our novel coherent transmission to fully reconstruct the in-phase and quadrature parts is validated through analytical symbol error rate and Matlab simulations. Results also show that the proposed scheme, while remarkable in its simplicity, can improve both the spectral and energy efficiency of VLC systems, i.e. double the spectral efficiency and achieve more than 45% energy efficiency improvement, when compared to its existing counterpart.

In this paper, a novel low-complexity and spectrally efficient modulation scheme for visible light communication (VLC) is proposed. Our new spatial quadrature modulation (SQM) is designed to efficiently adapt traditional complex modulation schemes to VLC; i.e. converting multi-level quadrature amplitude modulation (M-QAM), to real-unipolar symbols, making it suitable for transmission over light intensity. The proposed SQM relies on the spatial domain to convey the orthogonality and polarity of the complex signals, rather than mapping bits to symbol as in existing spatial modulation (SM) schemes. The detailed symbol error analysis of SQM is derived and the derivation is validated with link level simulation results. Using simulation and derived results, we also provide a performance comparison between the proposed SQM and SM. Simulation results demonstrate that SQM could achieve a better symbol error rate (SER) and/or data rate performance compared to the state of the art in SM; for instance a Eb/Nogain of at least 5 dB at a SER of 10−4.

User fairness and spectrum efficiency are conflicting objectives in cellular system optimization given that users share limited spectrum resources. Users at the cell edge are more likely to be unfairly treated due to their disadvantageous locations, where they experience high path losses and strong interferences if co-channel transmission exists. In this paper, a cell edge boundary is obtained and dynamically updated for each scheduling period to divide the users into cell centre and cell edge users, a tailored scheduling scheme is then performed for each group of users accordingly. Simulation results show that the boundary helps the schedulers achieve better balance between spectrum efficiency and fairness while providing the best energy efficiency, especially for smaller cell sizes (e.g. urban macro cells).

Energy efficiency is a key enabler for the next generation of communication systems. Equally, resource allocation and cooperative communication are effective techniques for improving the communication system performance. In this paper, we propose an optimal energy-efficient joint resource allocation method for the multi-hop multiple-input-multiple-output (MIMO) amplify-and-forward (AF) system. We define the joint source and multiple relays optimization problem and prove that its objective function, which is not generally quasiconvex, can be lower bounded by a convex function. Moreover, all the minima of this objective function are strict minima. Based on these two properties, we then simplify the original multivariate optimization problem into a single variable problem and design a novel approach for optimally solving it in both the unconstraint and power constraint cases. In addition, we provide a sub-optimal approach with reduced complexity; the latter reduces the computational complexity by a factor of up to 40 with a near-optimal performance. We finally utilize our novel approach for comparing the optimal energy-per-bit consumption of multi-hop MIMO-AF and MIMO systems; the results indicate that MIMO-AF can help to save energy when the direct link quality is poor.

This paper proposes a low-complexity joint source and relay energy-efficient resource allocation scheme for the two-hop multiple-input-multiple-output (MIMO) amplify-and-forward (AF) system when channel state information is available. We first simplify the multivariate unconstrained energy efficiency (EE)-based problem and derive a convex closed-form approximation of its objective function as well as closed-form expressions of subchannel rates in both the unconstrained and power constraint cases. We then rely on these expressions for designing a low-complexity energy-efficient joint resource allocation algorithm. Our approach has been compared with a generic nonlinear constrained optimization solver and results have indicated the low-complexity and accuracy of our approach. As an application, we have also compared our EE-based approach against the optimal spectral efficiency (SE)-based joint resource allocation approach and results have shown that our EE-based approach provides a good trade-off between power consumption and SE.

Optimization in mobile communications has mostly been performed based on spectral efficiency (SE). However, energy efficiency (EE) is fast becoming a key performance indicator, together with SE for designing future networks. In multi-cell communications, other-cell interference (OCI) coming from neighboring cells degrades both the SE and EE performances of the system. This paper presents an energy efficient precoding/power allocation algorithm for the downlink of the multi-cell multi-user multi-antenna channel, based on block diagonalization (BD). Each user employs an interference suppression filter while the precoder uses information about OCI plus noise covariance matrix to cancel interference and perform power allocation in an energy efficient manner. Simulation results show that our energy efficient BD scheme reduces the power consumption of the system and improves the EE in comparison with existing SE-based BD scheme.

Energy efficiency (EE) is becoming an important system design criterion to ensure that the next generation of communication networks is sustainable. Equally, cooperative communication and resource allocation are well-known techniques for improving the performance of communication systems. In this paper, we propose a low-complexity energy-efficient joint resource allocation method for the two-hop multiple-input-multiple-output (MIMO) amplify-and-forward (AF) system. We derive explicit formulations of the near-optimal energy-per-bit consumption, subchannels' power and rate for the unconstrained, total transmit power and sum-rate constrained EE optimization problems as well as detail how to solve these problems in a low-complexity manner. We then use our novel method for comparing the performances of two-hop MIMO-AF and MIMO systems in terms of EE. Our results indicate that the usage of a relay is only energy efficient when the quality of the direct link is very poor. We also show that the extra fixed power consumption induced by transmitting over two hops can seriously disadvantage MIMO-AF in terms of EE, but on the other hand, the usage of relay can be useful for downsizing the donor cell, which in turn provides EE gain.

Energy efficiency (EE) is becoming an important performance indicator for ensuring both the economical and environmental sustainability of the next generation of communication networks. Equally, cooperative communication is an effective way of improving communication system performances. In this paper, we propose a near-optimal energy-efficient joint resource allocation algorithm for multi-hop multiple-input-multiple-output (MIMO) amplify-and-forward (AF) systems. We first show how to simplify the multivariate unconstrained EE-based problem, based on the fact that this problem has a unique optimal solution, and then solve it by means of a low-complexity algorithm. We compare our approach with classic optimization tools in terms of energy efficiency as well as complexity, and results indicate the near-optimality and low-complexity of our approach. As an application, we use our approach to compare the EE of multi-hop MIMO-AF with MIMO systems and our results show that the former outperforms the latter mainly when the direct link quality is poor.

Energy efficiency (EE) is undoubtedly an important criterion for designing power-limited systems, and yet in a context of global energy saving, its relevance for power-unlimited systems is steadily growing. Equally, resource allocation is a well-known method for improving the performance of cellular systems. In this paper, we propose an EE optimization framework for the downlink of planar cellular systems over frequency-selective channels. Relying on this framework, we design two novel low-complexity resource allocation algorithms for the single-cell and coordinated multi-cell scenarios, which are EE-optimal and EE-suboptimal, respectively. We then utilize our algorithms for comparing the EE performance of the classic non-coordinated, orthogonal and coordinated multi-cell approaches in realistic power and system settings. Our results show that coordination can be a simple and effective method for improving the EE of cellular systems, especially for medium to large cell sizes. Indeed, by using a coordinated rather than a non-coordinated resource allocation approach, the per-sector energy consumption and transmit power can be reduced by up to 15% and more than 90%, respectively.

In this paper, the trade-off between energy efficiency (EE) and spectral efficiency (SE) is analyzed for both the uplink and downlink of the distributed multiple-input multiple-output (DMIMO) system over the Rayleigh fading channel while considering different types of power consumption models (PCMs). A novel tight closed-form approximation of the DMIMO EE-SE trade-off is presented and a detailed analysis is provided for the scenario with practical antenna configurations. Furthermore, generic and accurate low and high-SE approximations of this trade-off are derived for any number of radio access units (RAUs) in both the uplink and downlink channels. Our expressions have been utilized for assessing both the EE gain of DMIMO over co-located MIMO (CMIMO) and the incremental EE gain of DMIMO in the downlink channel. Our results reveal that DMIMO is more energy efficient than CMIMO for cell edge users in both the idealistic and realistic PCMs; whereas in terms of the incremental EE gain, connecting the user terminal to only one RAU is the most energy efficient approach when a realistic PCM is considered.

Energy efficiency (EE) is emerging as a key design criterion for both power limited, i.e. mobile devices, and power-unlimited, i.e. cellular networks, applications. Whereas, resource allocation is a well-known technique for improving the performance of communication systems. In this paper, we design a simple and optimal EE-based resource allocation method for the orthogonal multi-user channel by adapting the transmit power and rate to the channel condition such that the energy-per-bit consumption is minimized. We present our EE framework, i.e. EE metric and node power consumption model, and utilize it for formulating our EE-based optimization problem with or without constraint. In both cases, we derive explicit formulations of the optimal energy-per-bit consumption as well as optimal power and rate for each user. Our results indicate that EE-based allocation can substantially reduce the consumed power and increase the EE in comparison with spectral efficiency-based allocation.

In this paper, we propose a novel closed-form approximation of the Energy Efficiency vs. Spectral Efficiency (EE-SE) trade-off for the uplink/downlink of distributed multipleinput multiple-output (DMIMO) system with two cooperating base stations. Our closed-form expression can be utilized for evaluating the idealistic and realistic EE-SE performances of various antenna configurations as well as assessing how DMIMO compares against MIMO system in terms of EE. Results show a tight match between our closed-form approximation and the Monte-Carlo simulation for both idealistic and realistic EESE trade-off. Our results also show that given a target SE requirement, there exists an optimal antenna setting that maximizes the EE. In addition, DMIMO scheme can offer significant improvement in terms of EE over the MIMO scheme.

Until recently, link adaptation and resource allocation for communication system relied extensively on the spectral efficiency as an optimization criterion. With the emergence of the energy efficiency (EE) as a key system design criterion, resource allocation based on EE is becoming of great interest. In this paper, we propose an optimal EE-based resource allocation method for the scalar broadcast channel (BC-S). We introduce our EE framework, which includes an EE metric as well as a realistic power consumption model for the base station, and utilize this framework for formulating our EE-based optimization problem subject to a power as well as fairness constraints. We then prove the convexity of this problem and compare our EE-based resource allocation method against two other methods, i.e. one based on sum-rate and one based on fairness optimization. Results indicate that our method provides large EE improvement in comparison with the two other methods by significantly reducing the total consumed power. Moreover, they show that near-optimal EE and average fairness can be simultaneously achieved over the BC-S channel.

Because of its simplicity, amplify-and-forward (AF) is one of the most popular cooperative relaying technique. Relays are used in cooperative communication to improve reliability, coverage or spectral efficiency of cell-edge users. However, relays tend to increase the interferences seen by users of adjacent cells, particularly by the cell-edge users, when used in multi-cell systems. In this paper, we propose a low-complexity precoding scheme to mitigate the effect of other-cell interference (OCI) in cooperative communication. The scheme is designed by taking into account the interference plus noise covariance matrix of each user for mitigating the interference at each receiver by means of precoding at the relay node. Simulation results show the effectiveness of the proposed scheme, both in terms of sum-rate and computational complexity, when compared to other existing OCI-aware precoding algorithms for AF.

Along with spectral efficiency (SE), energy efficiency (EE) is becoming one of the key performance evaluation criteria for communication system. These two criteria, which are conflicting, can be linked through their trade-off. The EE-SE trade-off for the multi-input multi-output (MIMO) Rayleigh fading channel has been accurately approximated in the past but only in the low-SE regime. In this paper, we propose a novel and more generic closed-form approximation of this trade-off which exhibits a greater accuracy for a wider range of SE values and antenna configurations. Our expression has been here utilized for assessing analytically the EE gain of MIMO over single-input single-output (SISO) system for two different types of power consumption models (PCMs): the theoretical PCM, where only the transmit power is considered as consumed power; and a more realistic PCM accounting for the fixed consumed power and amplifier inefficiency. Our analysis unfolds the large mismatch between theoretical and practical MIMO vs. SISO EE gains; the EE gain increases both with the SE and the number of antennas in theory, which indicates that MIMO is a promising EE enabler; whereas it remains small and decreases with the number of transmit antennas when a realistic PCM is considered.

Energy savings are becoming a global trend, hence the importance of energy efficiency (EE) as an alternative performance evaluation metric. This paper proposes an EE based resource allocation method for the broadcast channel (BC), where a linear power model is used to characterize the power consumed at the base station (BS). Having formulated our EE based optimization problem and objective function, we utilize standard convex optimization techniques to show the concavity of the latter, and thus, the existence of a unique globally optimal energy-efficient rate and power allocation. Our EE based resource allocation framework is also extended to incorporate fairness, and provide a minimum user satisfaction in terms of spectral efficiency (SE). We then derive the generic equation of the EE contours and use them to get insights about the EE-SE trade-off over the BC. The performances of the aforementioned resource allocation schemes are compared for different metrics against the number of users and cell radius. Results indicate that the highest EE improvement is achieved by using the unconstrained optimization scheme, which is obtained by significantly reducing the total transmit power. Moreover, the network EE is shown to increase with the number of users and decrease as the cell radius increases.

In this paper, we derive a generic closed-form approximation (CFA) of the energy efficiency-spectral efficiency (EE-SE) trade-off for the uplink of coordinated multi-point (CoMP) system and demonstrate its accuracy for both idealistic and realistic power consumption models (PCMs). We utilize our CFA to compare CoMP against conventional non-cooperative system with orthogonal multiple access. In the idealistic PCM, CoMP is more energy efficient than non-cooperative system due to a reduction in power consumption; whereas in the realistic PCM, CoMP can also be more energy efficient but due to an improvement in SE and mainly for cell-edge communication and small cell deployment.

Cooperative communication is an effective approach for increasing the spectral efficiency and/or the coverage of cellular networks as well as reducing the cost of network deployment. However, it remains to be seen how energy efficient it is. In this paper, we assess the energy efficiency of the conventional Amplifyand- forward (AF) scheme in an in-building relaying scenario. This scenario simplifies the mutual information formulation of the AF system and allows us to express its channel capacity with a simple and accurate closed-form approximation. In addition, a framework for the energy efficiency analysis of AF system is introduced, which includes a power consumption model and an energy efficiency metric, i.e. the bit-per-joule capacity. This framework along with our closed-form approximation are utilized for assessing both the channel and bit-per-joule capacities of the AF system in an in-building scenario. Our results indicate that transmitting with maximum power is not energy efficient and that AF system is more energy efficient than point-to-point communication at low transmit powers and signal-to-noise ratios.

In this paper, we propose a tight closed-form approximation of the Energy Efficiency vs. Spectral Efficiency (EE-SE) trade-off for the uplink of a linear cellular communication system with base station cooperation and uniformly distributed user terminals. We utilize the doubly-regular property of the channel to obtain a closed form approximation using the Marčenko Pasture law. We demonstrate the accuracy of our expression by comparing it with Monte-Carlo simulation and the EE-SE trade-off expression based on low-power approximation. Results show the great tightness of our expression with Monte-Carlo simulation.We utilize our closed form expression for assessing the EE performance of cooperation for both theoretical and realistic power models. The theoretical power model includes only the transmit power, whereas the realistic power model incorporates the backhaul and signal processing power in addition to the transmit power. Results indicate that for both power models, increasing the number of antennas leads to an improvement in EE performance, whereas, increasing the number of cooperating BSs results in a loss in EE when considering the realistic power model.

Amplify-and-forward (AF) is one of the most popular and simple approaches for transmitting information over a cooperative multi-input multi-output (MIMO) relay channel. In cooperative communication, relays are employed for improving the coverage or enhancing the spectral efficiency, especially of cell-edge users. However, in a multi-cell context, the use of relays will also lead to an increase in the level of interference that is experienced by cell-edge users of neighboring cells. In this paper, two novel precoding schemes are proposed for mitigating this adverse effect of cooperative communication. They are designed by taking into account the effect of interference coming from neighboring cells, i.e. other cell-interference (OCI), in order to maximize the sum-rate of cell-edge users. Our novel OCI-aware precoding schemes are compared against non OCI-aware techniques and results show the large performance gain in terms of sum-rate that our schemes can achieved, especially for large numbers of users and/or antennas in the multi-cell system.

Coordinated multi-point (CoMP) architecture has proved to be very effective for improving the user fairness and spectral efficiency of cellular communication system, however, its energy efficiency remains to be evaluated. In this paper, CoMP system is idealized as a distributed antenna system by assuming perfect backhauling and cooperative processing. This simplified model allows us to express the capacity of the idealized CoMP system with a simple and accurate closed-form approximation. In addition, a framework for the energy efficiency analysis of CoMP system is introduced, which includes a power consumption model and an energy efficiency metric, i.e. bit-per-joule capacity. This framework along with our closed-form approximation are utilized for assessing both the channel and bit-per-joule capacities of the idealized CoMP system. Results indicate that multi-base-station cooperation can be energy efficient for cell-edge communication and that the backhauling and cooperative processing power should be kept low. Overall, it has been shown that the potential of improvement of CoMP in terms of bit-per-joule capacity is not as high as in terms of channel capacity due to associated energy cost for cooperative processing and backhauling.

Coordination between two or more multiple access channel (MAC) receivers can enlarge the achievable rate region of the whole system. This paper focuses on coordination by sharing the codebooks of the users between the receivers of MACs. We first define the achievable rate region of the time invariant multiple coordinated MAC (MCMAC) and subsequently derive its achievable rate region. We later express the achievable rate region in terms of the dominating points. We base our numerical analysis on the two-user two-receiver Gaussian coordinated MAC and make comparison with the interference channel, full cooperation and the individual MAC performance analysis. It is observed that this approach though suboptimal is less complex in comparison with full cooperation and that the MCMAC rate region is at least equal to the rate region of the uncoordinated approach. Over several channel states, the rate region of MCMAC exceeds that of the uncoordinated approach.

In this paper, we consider the precoding problem in the nonregenerative dual hop multi-input multi-output (MIMO) relay system. We propose a joint beamforming and power allocation method for a limited feedback system where a codebook-based beamformer is considered for each hop. The destination node selects the optimal beamforming codeword by relying on full channel knowledge of both source-relay and relay-destination channels for each hop from the code book and also compute the optimal power allocation coefficients for each substream. The index of the codewords and a quantized version of the power allocation coefficients are conveyed back to the source and relay nodes. The source and relay use the selected beamforming matrices and power allocation values to precode the data stream. In order to demonstrate the effectiveness of the proposed method, the performance of our joint beamforming and power allocation method is compared with previous codebook-based algorithms.

The mutual information (MI) of multiple-input multiple-output (MIMO) system over Rayleigh fading channel is known to asymptotically follow a normal probability distribution. In this paper, we first prove that the MI of distributed MIMO (DMIMO) system is also asymptotically equivalent to a Gaussian random variable (RV) by deriving its moment generating function (MGF) and by showing its equivalence with the MGF of a Gaussian RV. We then derive an accurate closed-form approximation of the outage probability for DMIMO system by using the mean and variance of the MI and show the uniqueness of its formulation. Finally, several applications for our analysis are presented.

Amplify-and-forward (AF) is one of the most common and simple approaches for transmitting information over a cooperative multi-input multi-output (MIMO) relay channel. It has recently been demonstrated that the spectral efficiency of AF scheme can be maximized by using the relay as a smart precoder. However, source node precoding has not been included in the overall maximization problem. In this paper, we propose a joint precoder design at the relay and source nodes for maximizing the cooperative mutual information (MI), i.e., the combination of direct and relay link MI, and thus, for further improving the spectral efficiency of AF scheme. In addition, we provide an algorithm for performing our joint precoding technique. Performance analysis indicates that our novel precoding algorithm outperforms other existing AF precoding methods in various link configurations.

Amplify-and-forward (AF) is one of the most popular and simple approaches to transmit information over a cooperative multi-input multi-output (MIMO) relay channel. In this paper, we propose three novel power allocation methods for the downlink of cooperative multi-user MIMO AF system, which are designed to maximize the weighted sum-rate (WSR) of the cooperative system, by considering two different levels of channel state information (CSI). We design efficient precoding algorithms at the relay by assuming that either only the receive CSI or both receive and transmit CSI is available at the relay. Results show the performance improvement that our schemes can achieve in terms of sum-rate and WSR metrics.

Decode-and-forward (DF) is one of the most popular approach to transmit information over a cooperative relay channel. In DF, information coming from different sources is simply combined regardless of their respective link qualities, and thus DF is not optimized for any propagation conditions. In this paper, we propose a novel transmit cooperation scheme that exploits asymmetric link qualities by using layered higher order modulation. A partial forwarding approach is followed by taking advantage of the layered structure: one part of the information is forwarded by a relay for increasing the robustness of the direct link and the rest of the information flows through the boosted direct link. Moreover, our scheme is based on a distributed serially concatenated encoding structure that can accommodate iterative decoding to further improve its performance. The complexity of our scheme is seemingly identical to DF scheme. Performance evaluation shows that our scheme provides a better spectral efficiency in asymmetric propagation conditions than DF scheme for both non-iterative and iterative decoding.

The log-normal probability distribution has been commonly used in wireless communications to model the shadowing and, recently, the small-scale fading for indoor ultrawideband (UWB) communications. In this paper, a tight closed-form approximation of the ergodic capacity over log-normal fading channels is derived. This expression can be easily used to evaluate and compare the ergodic capacities of communication systems operating over log-normal fading channels. We also utilize this expression to show that the capacity of a multi-antennas UWB system operating over the IEEE 802.15.3a channel can be improved mainly through receive diversity.

The log-normal probability distribution is commonly used in wireless communications to model the shadowing and, more recently, the small-scale fading for indoor ultra-wideband communications. In this paper, an accurate closed-form approximation of the ergodic capacity over log-normal fading channels is derived. This expression can be easily used to evaluate and compare the ergodic capacity of communication systems operating over log-normal fading channels.

The log-normal probability distribution is commonly used in wireless communications to model the shadowing and more recently the small scale fading for indoor ultra wideband communications. In this paper, an accurate closed-form approximation of the average probability of error over a log-normal fading channel is derived for various constellation types and sizes. This expression can be used to evaluate and compare easily the symbol-error performance of communication systems over a log-normal fading channel.

Ultra wideband (UWB) systems have attracted a lot of research interest lately, owing to their appealing features in short-range mobile communications. These features include low power peer-to-peer transmissions, multiple access communications, high data rates, and precise positioning capabilities. Space-time coding (STC) techniques, such as the block coding scheme, or the trellis coding scheme, are known to be simple and practical ways to increase the spectral efficiency in wireless communications. We aim to combine a pulse position modulation (PPM) impulse radio multiple access (IRMA) system with two different space-time coding techniques. Thus, we developed a space-time block code scheme and adapted a space-time trellis code scheme to UWB signalling, relying on the channel state information (CSI) at the receiver side. Then the added diversity produced by these techniques is exploited to enhance the performance of UWB systems. Analysis is conducted in a typical UWB environment, with fractionally-spaced (FS) coherent RAKE detection.