Accurate radio environment map (REM) construction proves critical for efficient wireless spectrum management. Although conventional 2D REMs have demonstrated effectiveness in wireless network optimization, they inherently overlook vertical signal strength variations, which are vital for UAV operations, particularly in urban landscapes with skyscrapers or diverse terrain features. Current estimation approaches, including ground-based crowdsourcing, random sampling, and predetermined trajectory measurements, show limited capability in generating high-fidelity 3D REMs. This study proposes a joint optimization framework for UAV-enabled adaptive 3D radio mapping, integrating 3D REM construction with adaptive aerial sampling. At the heart of the construction module, a dual-branch encoder-decoder architecture fuses multi-scale features from sparse aerial measurements with building structural data, explicitly modeling obstruction effects through offline pre-training and online refinement to enhance generalization. For adaptive sampling, a diffusion-based trajectory planner dynamically optimizes UAV measurement paths by integrating environmental priors (e.g., building layouts), effectively overcoming the sparse-reward limitations inherent in reinforcement learning methods. Experimental validation demonstrates significant performance improvements across all evaluation metrics. Compared to 2D per-layer estimation methods, our 3D estimator achieves 49% superior structural similarity (SSIM) in construction accuracy, while the feature fusion module yields a 37% reduction in mean squared error (MSE). The diffusion-based planner outperforms reinforcement learning approaches by achieving 45% lower MSE and 18% higher SSIM in resultant map quality after 5,000 step iterations.

The deployment of high-frequency carriers in 5G networks and beyond introduces significant challenges, particularly due to increased path loss and physical limitations of user equipment (UE). In particular, these challenges lead to uplink/downlink coverage imbalances, critically affecting applications that rely on robust uplink capacity such as autonomous driving, telemedicine, and live streaming. While downlink-uplink decoupling (DUDe) and supplementary uplink (SUL) have emerged as promising solutions for uplink enhancement, their flexible cell association mechanisms disrupt conventional handover strategies by introducing multidimensional, decoupled decision-making. To address this, we propose a heterogeneous network architecture that integrates DUDe into SUL, supporting non-co-located deployment of supplementary uplink carriers and enabling dual decoupling at both the base station and carrier levels. Building on this architecture, we introduce Counterfactual Multi-agent fuzzy neural network (COMA-FNN), a multi-agent reinforcement learning (MARL) algorithm based on centralized training with decentralized execution (CTDE). COMA-FNN incorporates fuzzy neural networks to model the complex, nonlinear relationships among multiple communication attributes, improving the precision and adaptability of handover decisions. The algorithm also employs a centralized critic with counterfactual baselines to effectively resolve credit assignment issues among competing agents. To accommodate varying service requirements, COMA-FNN incorporates service-specific reward functions aligned with four 3GPP-standardized service types. These rewards are weighted using the Analytic Hierarchy Process (AHP), enabling the algorithm to support different QoS policies. Simulation results demonstrate that COMA-FNN significantly improves handover efficiency, reduces latency, and enhances throughput, making it a robust solution for intelligent mobility management in decoupled uplink/downlink architectures.

This work introduces a novel blind channel estimation (CE) scheme for intelligent reflecting surface (IRS)-assisted networks with heterogeneous communications and sensing devices. The proposed approach operates in two stages: the first stage is dedicated to transmitting the sensing data, and the second to transmitting communications data. By leveraging the fact that sensing information typically has less stringent quality of service (QoS) requirements compared to communication data, the sensing data transmission stage is leveraged for blind CE. The CE is performed using a specific frame structure, where the modulated sensing symbols collaborate to estimate the channel coefficients for all IRS elements blindly and jointly. The performance of sensing data transmission is evaluated in terms of average bit error rate (BER), with exact closed-form expressions derived for the considered modulation schemes. For the communications data, the BER is analyzed, and a tight lower bound is derived. Additionally, an accurate closed-form expression is derived for the mean-squared-error (MSE) of the proposed CE. The MSE results demonstrate that the proposed blind CE outperforms state-of-the-art schemes.

Non-orthogonal multiple access (NOMA) is widely recognized for enhancing the energy and spectral efficiency through effective radio resource sharing. However, uplink NOMA systems face greater challenges than their downlink counterparts, as their bit error rate (BER) performance is hindered by an inherent error floor due to error propagation caused by imperfect successive interference cancellation (SIC). This paper investigates the BER performance improvements enabled by reconfigurable intelligent surfaces (RISs) in multi-user uplink NOMA transmission. Specifically, we propose a novel RIS-assisted uplink NOMA design, where the RIS phase shifts are optimized to enhance the received signal amplitudes while mitigating the phase rotations induced by the channel. To achieve this, we first develop an accurate channel model for the effective user channels, which facilitates our BER analysis. We then introduce a channel alignment scheme for a two-user scenario, enabling efficient SIC-based detection and deriving closed-form BER expressions. We further extend the analysis to a generalized setup with an arbitrary number of users and modulation orders for quadrature amplitude modulation signaling. The analysis is also extended to consider imperfect channel state information (CSI) knowledge and the multi-antenna base station (BS) cases. Using the derived BER expressions, we develop an optimized uplink NOMA power allocation (PA) scheme to minimize the average BER while satisfying the user transmit power constraints. It will be shown that the proposed NOMA detection scheme, in conjunction with the optimized PA strategy, eliminate SIC error floors at the base station. The theoretical BER expressions are validated using simulations, which confirms the effectiveness of the proposed design in eliminating BER floors.

This paper investigates the symbol error rate (SER) performance of the pilot-aided simultaneous communication and localisation (PASCAL) system with a ground-to-air model. A scenario where multiple drones transmit communication signals to a base station (BS), which needs to simultaneously decode the signals and continuously locate the drones’ positions during the communication session, is considered. The BS operates in two stages: first, it estimates the drones’ location parameters using pilot signals; second, it performs data detection by reconstructing the channel response based on the estimated location parameters. The theoretical analysis presented in this paper demonstrates that the distributions of the estimated location parameters follow Gaussian distributions of which the mean values are equal to the actual values of the locations, and their variances are determined by the achievable mean square error of the estimator. Using these distributions, the average SER is derived to quantify the impact of localisation errors on decoding performance. This analysis highlights the synergy between communication and localisation, providing valuable insights into the influence of localisation inaccuracies on the performance of location-aware communication systems. Simulations are conducted to validate the theoretical derivations.

This paper introduces a novel framework aimed at designing integrated waveforms for robust integrated sensing and communication (ISAC) systems. The system model consists of a multiple-input multiple-output (MIMO) base station that simultaneously serves communication user equipments (UEs) and detects multiple targets using a shared-antenna deployment scenario. By leveraging Kullback-Leibler divergence (KLD) to holistically characterise both communication and sensing subsystems, three optimisation problems are formulated: (i) radar waveform KLD maximisation under communication constraints, (ii) communication waveform KLD maximisation subject to radar KLD requirements, and (iii) an integrated waveform KLD-based optimisation for ISAC that jointly balances both subsystems. The first two problems are solved using a projected gradient method with adaptive penalties for the radar waveforms and a gradient-assisted interior point method (IPM) for the communication waveforms. The third, integrated waveform optimisation approach adopts an alternating direction method of multipliers (ADMM) framework to unify radar and communication waveform designs into a single integrated optimisation, thereby synergising sensing and communication objectives and achieving higher overall performance than either radar- or communication-only techniques. Unlike most existing ISAC waveform designs that regard communication signals solely as interference for sensing, the proposed framework utilises the holistic ISAC waveform—that is, the superimposed communication and sensing signals—to boost detection performance in the radar subsystem. Simulation results show significant improvements in both radar detection and communication reliability compared with conventional zero-forcing beamforming, identity-covariance radar baselines, and traditional optimisation approaches, demonstrating the promise of KLD-based waveform designs for next-generation ISAC networks.

This work proposes an efficient two-stage jamming detection and channel estimation algorithm for orthogonal frequency division multiplexing (OFDM)-based unmanned aerial vehicles (UAVs) communications. The proposed scheme is designed based on the unique time and frequency domain statistical characteristics of OFDM signals. In the time domain (TD), a likelihood ratio test (LRT)-based decision rule is derived as a function of the inherent correlation between the cyclic prefix (CP) samples and their counterparts in the OFDM symbol. In addition, in the frequency domain (FD), a closed-form joint jamming detection and channel estimation scheme is derived using the maximum a posteriori probability (MAP) principle as a function of the statistics of the received pilots and virtual subcarriers (VSCs) signals, which is then re-expressed using the generalized MAP ratio test (GMAPRT). The system’s complexity is reduced by applying the two stages sequentially, where the possible implementation of the second stage is conditioned on the outcome of the first stage. The performance of the proposed algorithm is evaluated using Monte Carlo simulations, where the results demonstrate its effectiveness compared to the TD-only and FD-only approaches. The results confirm the superior performance of the proposed scheme compared to the cyclostationary feature (CF)-based technique under various operating scenarios.

n this paper, we analyze the performance tradeoff between integrated radar and communications (RadCom) systems using the Kullback-Leibler divergence (KLD) measure, also called the relative entropy (RE). Specifically, we derive the KLD measure for both subsystems for a base-station serving a number of communication users while detecting multiple targets simultaneously. We evaluate the trade-off between the radar and the communication systems using a weighted KLD that can enhance the flexibility of the allocations. The results demonstrate that the KLD is an effective mean for achieving the optimal tradeoff between both systems and that it provides a higher degree of controllablity and adaptability for RadCom systems.

This paper considers joint power allocation and sub-carrier assignment (J-PA-SA) in uplink clustered multi-carrier non-orthogonal multiple-access (NOMA) networks. Specifically, the goal is to maximize the network sum-rate subject to users' minimum rate requirements. A novel network-coded (NC) many-to-one subcarrier assignment scheme is proposed to improve bandwidth utilization over the conventional one-to-one subcarrier assignment. In general, the J-PA-SA problem is non-convex and NP-hard. To efficiently solve it, it is split into two sub-problems: (1) power allocation per (user cluster, subcarrier) combination, and (2) subcarrier assignment. A solution procedure is devised to efficiently solve the J-PA-SA problem for the network-coded SA scheme. Simulation results revealed that the proposed solution procedure efficiently yields the optimal network sum-rate solution, while satisfying the minimum rate requirement per user. More importantly, the proposed network-coded SA scheme is shown to be superior to the conventional SA scheme.

This paper investigates various receiver architectures for uplink non-orthogonal multiple access (NOMA)-based integrated sensing and communication (ISaC) systems. Specifi-cally, a novel signaling approach is considered whereby mutual interference between the radar and communication signals is canceled by alternately reversing the radar symbols and phase-rotating the transmitted data symbols in consecutive periods. While such a signaling approach eliminates both detection ambiguity and radar interference at the receiver, this requires the receiver to detect the targets and data over two symbol periods at a time. To this end, in this paper, we adapt various well-known receivers, such as the maximum ratio combining (MRC), zero forcing (ZF), successive interference cancellation (SIC) and max-imum likelihood (ML) receivers, and compare their performance under a variety of conditions. When evaluating the bit error rate (BER), the achievable sum rate (ASR), and the radar channel estimation (RCE) accuracy, it is found that the proposed ISaC system exhibits remarkable performance regardless of the radar signal's power compared to other ISaC signaling approaches. It is also found that the MRC receiver suffers from error floors when the system loading is relatively high, while ZF and ML provide comparable and superior performances regardless of the system load.

This paper proposes a multiple target localization scheme using a clustered wireless sensor network (WSN) for terrestrial and underwater environments. In the considered system, sensors measure the total energy emitted by the targets and transmit quantized versions of their measurements to a data central device (DCD) with the help of intermediate cluster-heads (CHDs), which employ decode-and-forward relaying (DFR). Upon data collection from sensors, the DCD performs the localization process, which involves estimating the number and positions of the targets. Data transmission from the sensors to CHDs takes place through an imperfect medium, which is characterized by a Rician fading model. The penalized maximum likelihood estimator (PMLE), also known as regularized maximum likelihood estimation (MLE), is applied at the DCD to provide optimal estimates of the number and locations of targets. Furthermore, a suboptimal estimator is derived from PMLE that offers comparable performance under certain operating conditions, but with significantly reduced computational complexity. Cramer-Rao lower bound (CRLB) is derived to serve as an asymptotic benchmark for the root mean square error (RMSE) of the estimators in addition to the centroid-based localization benchmark. Monte Carlo simulation is used to evaluate the performance of the proposed estimation techniques under various system conditions. The results show that PMLE can effectively estimate the number and locations of the targets. Furthermore, it is shown that the RMSE of the proposed estimators approaches the CRLB for a large number of sensors and a high signal-to-noise ratio.

This work investigates the performance of intelligent reflective surfaces (IRSs) assisted uplink nonorthogonal multiple access (NOMA) in energy-constrained networks. Specifically, we formulate and solve two optimization problems; the first aims at minimizing the sum of users’ transmit power, while the second targets maximizing the system-level energy efficiency (EE). The two problems are solved by jointly optimizing the users’ transmit powers and the beamforming coefficients at the IRS, subject to the users’ individual uplink rate and transmit power constraints. A novel and low-complexity algorithm is developed to optimize the IRS beamforming coefficients by optimizing the objective function over the complex circle manifold (CCM). To efficiently optimize the IRS phase shifts over the manifold, the optimization problem is reformulated into a feasibility expansion problem which is reduced to a max-min signal-to-interference-plus-noise ratio (SINR). Then, with the aid of a smoothing technique, the exact penalty method is applied to transform the problem from constrained to unconstrained. The proposed solution is compared against three semi-definite programming (SDP)-based benchmarks which are semi-definite relaxation (SDR), SDP-difference of convex (SDP-DC) and sequential rank-one constraint relaxation (SROCR). The results show that the manifold algorithm provides better performance than the SDP-based benchmarks, and at a much lower computational complexity for both the transmit power minimization and EE maximization problems. The results also reveal that IRS-NOMA is only superior to orthogonal multiple access (OMA) when the users’ target achievable rate requirements are relatively high.

In this work, we evaluate the bit error rate (BER) and block error rate (BLER) performances of a downlink two-user non-orthogonal multiple access system considering the received energy per bit per noise spectral density (Eb/N0). A one-to-one mapping between the Eb/N0and transmit signal to noise ratio (SNR) is derived for the uncoded and coded systems. Furthermore, the channel coding gain is quantified for turbo product codes with various code rates and block lengths. In addition, the performance is evaluated for Mn-ary quadrature amplitude modulation of selected orders. It is shown that the BER and BLER performances reach the waterfall region with smaller Eb/N0values compared to transmit SNR, which reduces the simulation run time to capture the desired performance.

In this paper, we present an intelligent reflective surface (IRS)-assisted physical layer network coding (PNC) system in a two-way relaying channel (TWRC). Specifically, IRS is used to align the effective channels of the two received superimposed signals at the relay, which allows canceling the carrier phase offset (CPO) between the two received signals. The IRS phase shifts are optimized to maximize the received PNC signal amplitude while having a zero CPO constraint. An efficient manifold optimization-based approach is proposed to solve this problem, where the optimization is performed on the complex circle manifold. Moreover, we improve the performance of channel-coded IRS-assisted PNC by introducing the weighted non-binary PNC (WN-PNC) scheme, where the binary data are mapped to, and encoded over, Galois Fields (GFs). We present two WN-PNC cases where the data is encoded over GF(4) and GF(8), then modulated using quadrature phase shift keying (QPSK) and 8-quadrature amplitude modulation (8-QAM), respectively. We also design proper PNC mapping functions for both cases, ensuring that no PNC ambiguity can occur at the relay. Our simulation results show the efficacy of the proposed manifold optimization-based approach and the error performance improvement of the WN-PNC over the binary PNC case.

In this paper, we provide performance analysis for an integrated radar-communication (RadCom) system based on the relative information (RE), also called the Kullback-Leibler divergence (KLD) theorem. The considered system model consists of a multiple-input-multiple-output (MIMO) base-station (BS) which aims at providing RadCom services to multiple communication user equipments (UEs) and detecting a target. The separated deployment, in which the base-station antennas are distributed among radar and communication subsystems, is considered with Zero forcing (ZF) and maximum ratio transmission (MRT) precoders are applied to precode the communication signal. Results show that the derived formulas in this paper are accurate and imply that MRT suffers from bad performance compared to ZF.

In this paper, the problem of joint direction of arrival (DOA) and Doppler frequency estimation with array model defects is investigated. To this end, a two-dimensional (2D) robust multiple signal classification (MUSIC) algorithm is proposed, which is a generalization of the conventional MUSIC algorithm. The introduced algorithm is based on a colocated multiple-input-multiple-output (MIMO) radar composed of uniform linear arrays, in which a mix of calibrated and uncalibrated antennas exist in its transmitter, while all the receiver antennas are assumed to be uncalibrated. To be specific, the 2D R-MUSIC algorithm adopts a separation scheme to automatically obtain the signals associated with the calibrated subset of transmitter antennas and then eliminates the effect of the signals belonging to the uncalibrated transmitting and receiving antennas. Afterward, the localization is performed by modifying the conventional algorithms in accordance with the separation scheme. In addition, a 2D Genie maximum likelihood (ML) algorithm under the assumption of precisely known errors at the receiver is derived to provide a lower bound benchmark for the introduced method. The simulation results demonstrate the superiority of the proposed algorithms relative to the conventional ones.

Conventional localization algorithms, including maximum likelihood (ML) and multiple signal classification (MUSIC), are significantly influenced by array model imperfections. To address this problem, two generalized algorithms are proposed in this paper by extending the two conventional algorithms. The presented techniques are evaluated within the context of a passive uniform rectangular array (URA) where a rectangular subarray is assumed to be calibrated perfectly, while the remaining antennas incur array model errors. In this case, the performance of the conventional algorithms degrades seriously or even the operations fail. Nevertheless, the proposed algorithms can eliminate this issue by employing a separation technique. In specific, a separation strategy is applied to the introduced algorithms to automatically selects signals belonging to the calibrated subarray from the received signal matrix and eliminate the signals belonging to the uncalibrated antennas prior to conducting the azimuth-elevation-Doppler estimation. In order to reduce the computation complexity, the azimuth-elevation-Doppler estimation is divided into two sub-problems: the estimation process of the Doppler frequency and the estimation process of the azimuth-elevation angles. The simulation results are shown to demonstrate the efficiency and superiority of the proposed algorithms compared to the conventional algorithms.

This paper considers resource allocation for network-coded clustered uplink non-orthogonal multiple-access (NOMA) networks with simultaneous wireless information and power transfer (SWIPT)-enabled relays. In particular, the goal is to perform joint power allocation, power-splitting, and relay selection (J-PA-PS-RS) to maximize the network sum-rate, subject to quality-of-service requirements. The formulated problem happens to be a non-convex and excessively complex. Thus, it is split into two sub-problems: (1) joint power allocation and power-splitting per relay, and (2) relay selection. Particularly, a solution procedure is proposed, where the joint user and relay power allocation, and power-splitting per relay is solved via a low-complexity iterative three-layer algorithm, and then followed by optimal relay selection. Simulation results have revealed that the proposed solution procedure achieves near-optimal solutions as well as being superior to the OMA-based network.

Abstract This paper proposes combined precoding and artificial noise‐insertion scheme to enhance the secrecy of generalized precoded spatial modulation when the wiretap channel is partially correlated with the legitimate channel. It is shown that randomizing the modulated and spatial symbols prior to artificial noise insertion can significantly enhance secrecy even with a highly correlated eavesdropper channel. The proposed scheme exploits the channel state information (CSI) of the legitimate channel without requiring knowledge of the eavesdropper channel. The security of the proposed system depends on the amount of power allocation and the number of active receive antennas. Simulation results validate the proposed security scheme and show that the hybrid approach proposed outperforms the one that relies on artificial noise transmission.

This work presents a novel nonorthogonal multiple access (NOMA) cognitive radio (CR) system where the base station (BS) opportunistically multiplexes the secondary user (SU) with the primary user (PU) using power-domain NOMA. As the PU has the priority to transmit and SU is satisfied on best-effort basis, four different transmission-modes (TMs) are produced at the BS, which are PU orthogonal multiple access (PU-OMA), SU-OMA, PU/SU-NOMA, and silent mode. Consequently, the considered protocol can be classified as a hybrid underlay-interweave CR-NOMA. The TM adaptation should be seamless for the PU where its detector configuration remains unchanged regardless of the active TM. In contrast, the SU has to identify the active TM blindly, i.e. without side information, to select the appropriate detector. The identification process is performed using a classifier that is designed based on the maximum likelihood criterion. The performance of the proposed system is analyzed in terms of throughput, packet error rate (PER), and classification error. The Binomial and Multinomial theorems are utilized to simplify and allow a tractable analysis. The derived closed-form expressions, corroborated by Monte-Carlo simulation results, show that the hybrid CR-NOMA can provide substantial throughput improvement over conventional NOMA, which is about a 100%.

The need for integrated sensing and communication (ISAC) services has significantly increased in the last few years. This integration imposes serious challenges such as joint system design, resource allocation, optimization, and analysis. Since sensing and telecommunication systems have different approaches for performance evaluation, introducing a unified performance measure which provides a perception about the quality of sensing and telecommunication is very beneficial. To this end, this paper provides performance analysis for ISAC systems based on the information theoretical framework of the Kullback-Leibler divergence (KLD). The considered system model consists of a multiple-input-multiple-output (MIMO) base-station (BS) providing ISAC services to multiple communication user equipments (CUEs) and targets (or sensing-served users). The KLD framework allows for a unified evaluation of the error rate performance of CUEs, and the detection performance of the targets. The relation between the detection capability for the targets and error rate of CUEs on one hand, and the proposed KLD on the other hand is illustrated analytically. Theoretical results corroborated by simulations show that the derived KLD is very accurate and can perfectly characterize both subsystems, namely the communication and radar subsystems.

This paper presents a novel approach for power-constrained internet of things (IoT) networks that employ non-orthogonal multiple access (NOMA) and are assisted by an intelligent reflecting surface (IRS) for uplink transmissions. The main objective of this work is to maximize the sum rate of power-constrained IoT networks by jointly designing the IRS phase shifts and the users’ transmit power allocation. The proposed solution optimizes the power allocation and phase shifts alternatively. We devise a novel approach to optimize the IRS phase shifts that is based on manifold optimization techniques. Specifically, the IRS phase shifts optimization problem is formulated and solved over the complex circle manifold. Our results show that the proposed method outperforms the widely used semi-definite relaxation (SDR) technique as higher sum rates with less power consumption can be achieved.

In recent years, orthogonal frequency division multiplexing has been considered a potential technology for serving as a source of randomness for the physical layer security designs due to the high dimensionality per single transmission represented by the modulated subcarriers. In this paper, we first proposed an algorithm with a pre-shared key to rotate the constellation mapping of the modulated M-ary phase shift keying M-PSK symbols. Following this, we exploited the independent channel fading of the subcarriers by inducing a phase error per symbol based on the channel state information to make the cryptographic attacks more challenging. The bit mismatch was then minimised through error-correcting codes. The security’s efficacy can be evaluated by the symbol error rate as a false cipher detection rate. The simulation results indicated that the attacker’s receiver suffers higher detection errors of the cipher even when the received signal-to-noise ratio is the same as that of the legitimate users.

Nowadays, improving the reliability and security of the transmitted data has gained more attention with the increase in emerging power-limited and lightweight communication devices. Also, the transmission needs to meet specific latency requirements. Combining data encryption and encoding in one physical layer block has been exploited to study the effect on security and latency over traditional sequential data transmission. Some of the current works target secure error-correcting codes that may be candidates for post-quantum computing. However, modifying the popularly used channel coding techniques to guarantee secrecy and maintain the same error performance and complexity at the decoder is challenging since the structure of the channel coding blocks is altered which results in less optimal decoding performance. Also, the redundancy nature of the error-correcting codes complicates the encryption method. In this paper, we briefly review the proposed security schemes on Turbo codes. Then, we propose a secure turbo code design and compare it with the relevant security schemes in the literature. We show that the proposed method is more secure without adding complexity.

In this paper, a downlink cooperative non-orthogonal multiple accesses (C-NOMA) system assisted with a decode and forward (DF) UAV-relay is developed, where the channel gains follow the $\kappa-\mu$ generalized fading model to evaluate its system performance. The study involves two scenarios in which the NOMA signal is propagated through the outdoor-to-indoor channel and the outdoor-to-outdoor channels, where the practical successive interference cancellation (SIC) is addressed. In particular, exact closed-form expressions are derived for the outage probability (OP) of indoor-outdoor NOMA users on $\kappa-\mu$ fading channels. To obtain more insight into how channel fading parameters affect OP performance, asymptotic expression is also evaluated. The results provide insight into the impact of key parameters, such as power allocation and channel fading parameters, on system performance. Ultimately, Monte Carlo simulations were used to validate the analytical expressions.

In this work, we derive new closed-form expressions for the throughput of non-orthogonal multiple access (NOMA) system with adaptive modulation orders. The system design considers a packet-based transmission where the base station adapts the modulation orders to satisfy the block error rate (BLER) requirement for each user and maximize the throughput by minimizing the maximum signal to noise ratio (SNR) requirements of the users. The optimization problem is formulated as a minmax problem to jointly optimize the modulation orders and SNR thresholds, where the original mixed-integer programming is simplified to integer programming by introducing an auxiliary variable. Compared to the grid search approach, the analytical and simulation results show that the min-max approach can improve the throughput with a significant reduction in the number of transmission modes, the throughput can be improved by up to 2.5 dB at moderate SNRs and by 1 bit/symbol at extremely high SNRs.

Nonorthogonal multiplexing (NOM) is a novel superposition coding scheme that has been recently proposed to improve the throughput of wireless systems. However, restricting the number of multiplexed packets to two limits the throughput improvement of nonorthogonal multiplexing (NOM) to 100% in best-case scenarios. Therefore, this work presents a generalized NOM (GNOM) design with an unlimited number of multiplexed packets. In the multiplexing process, new and retransmitted packets due to arq are combined while considering the impact of channel conditions on the power assigned per packet. The proposed GNOM employs an efficient heuristic algorithm to perform the power assignment and multiplexing decisions. Moreover, the complexity can be controlled by enforcing a limit on the maximum number of multiplexed packets per transmission, making it suitable for iot nodes with diverse computational capabilities and quality of service requirements. The obtained results demonstrate the effectiveness of the proposed scheme, which offers up to 200% throughput improvement at moderate signal to noise ratios (SNRs), and up to 700% at high SNRs. Furthermore, the new scheme can reduce the transmission power consumption by up to 6 dB in the high SNR region.

This paper presents the design and bit error rate (BER) analysis of a phase-independent non-orthogonal multiple access (NOMA) system. The proposed NOMA system can utilize amplitude-coherent detection (ACD) which requires only the channel amplitude for equalization purposes. In what follows, three different designs for realizing the detection of the proposed NOMA are investigated. One is based on the maximum likelihood (ML) principle, while the other two are based on successive interference cancellation (SIC). Closed-form expressions for the BER of all detectors are derived and compared with the BER of the coherent ML detector. The obtained results, which are corroborated by simulations, demonstrate that, in most scenarios, the BER is dominated by multiuser interference rather than the absence of the channel phase information. Consequently, the BER using ML and ACD are comparable for various cases of interest. The paper also shows that the SIC detector is just an alternative approach to realize the ML detector, and hence, both detectors provide the same BER performance.

This paper considers the problem of joint power allocation and antenna selection (J-PA-AS) for downlink clustered non-orthogonal multiple-access (NOMA) networks. In particular, the goal is to perform antenna selection for each user cluster and allocate transmit power to its users so as to maximize the network sum-rate, while satisfying quality-of-service (QoS) requirements. The formulated problem happens to be non-convex and NP-hard, and thus, there is no computationally-efficient approach to solve it directly. In turn, a low-complexity two-stage algorithm is proposed, where the first stage optimally solves the sum-rate maximizing power allocation problem for each (antenna, user cluster) pair. In the second stage, antenna selection is optimally solved in polynomial-time complexity via the Kuhn-Munkres with backtracking (KMB) algorithm. Simulation results are provided to validate the proposed algorithm, which is shown to efficiently yield the optimal network sum-rate, and in comparison to the optimal J-PA-AS scheme (solved via a global optimization package), and superior to other benchmark schemes. The impact of spatial-diversity on the network sum-rate is also highlighted, where it is shown that the greater the number of antennas at the base-station is, the higher the network sum-rate, and the lower the outage events.

Non-orthogonal multiple access (NOMA) is a promising candidate for future wireless networks due to its ability to improve the spectral-efficiency and network connectivity. Nevertheless, the error rate performance of NOMA depends significantly on the power assignment, which requires accurate knowledge of the channel state information at the transmitter (CSIT). However, providing accurate CSIT can be challenging. Therefore, this paper proposes a data-aware adaptive power assignment NOMA scheme called PANOMA which adaptively changes the signal power based on the transmitted data to maximize the constructive interference. To quantify its potential, closed-form bit error rate (BER) expressions are derived for two users over the broadcast Rayleigh fading channel. Based on these expressions, the power assignment that minimizes the system’s average BER is found. The results demonstrate that PANOMA provides a tangible BER performance gain over conventional power-domain NOMA when both schemes use optimal power and sub-optimal power assignments. Also, PANOMA provides robustness to imperfect power assignment which results from imperfect CSIT. The integrity of the analytical results is verified by Monte Carlo simulation.

In this paper, we consider the problem of channel feedback in massive multiple-input-multiple-output (MIMO) systems. For the downlink scenario, we present a detailed comparison between the performance of the quantized and the analog channel feedback schemes for the case of having multiple antenna users. Both schemes’ performance is evaluated by deriving an upper bound on the rate gap between the rate of the system with perfect channel state information (CSI) and with imperfect CSI for both feedback schemes. We compare the two schemes, namely, quantized channel feedback and analog channel feedback, under the same resources allocated for channel feedback for a fair comparison. Moreover, we consider two different downlink transmission schemes; the first one does not consider power allocation across the streams and the second one does power allocation (water-filling) across the streams. Our results show that the analog feedback scheme performs better in the low signal to noise (SNR) region when performing power allocation across the multiple data streams. However, the quantized channel feedback scheme performs better at the high SNR region, where the quantized CSI can provide a better approximation of the actual CSI. Finally, simulation results are presented to verify our theoretical analysis and demonstrate our conclusions.

This article proposes a downlink/uplink decoupled (DUDe) access scheme for cellular-enabled unmanned aerial vehicle (UAV) communication systems. To minimize interference, the proposed scheme separates the control and data links of UAVs, as well as the uplinks (ULs) and downlinks (DLs) of ground users (GUEs), onto different serving base stations and operating frequencies. Since power availability is a major constraint in UAV communications, two power allocation schemes based on$Q$-learning (QL) and deep$Q$-learning (DQL) are proposed to optimize the communication energy efficiency (EE) of this DUDe network. To quantify the improvements achieved, the proposed schemes are compared with the fractional power control (FPC) scheme used in 4G and 5G networks, as well as a convex optimization-based optimal power allocation scheme. The results demonstrate that the proposed DUDe scheme can achieve up to several times higher sum rates and EE in the UL direction than its coupled counterparts. Moreover, it is shown that the EE performance of the QL and DQL power allocation schemes approach the optimal performance and surpass the conventional FPC scheme by 80%–100% in the UHF band, and by 160%–170% in the mmWave band.

Nonorthogonal multiple access (NOMA) is a promising candidate for future wireless networks due to its ability to improve the spectral efficiency and network connectivity. Nevertheless, the error rate performance of NOMA depends significantly on the power assignment for each user, which requires accurate knowledge of the channel state information (CSI) at the transmitter, which can be challenging for several applications, such as wireless sensor networks (WSNs) and Internet of Things (IoT). Therefore, this article proposes a power-tolerant NOMA by adaptively changing the signal power of each user to reduce the system sensitivity to inaccurate power assignment. The power adaptation in the power-adaptive NOMA (PANOMA) is performed based on the transmitted data, and it does not require accurate CSI. To quantify its potential, the bit error rate (BER) and the lower bound capacity performance, over Rayleigh fading channels, are derived in exact closed forms for two and three users scenarios. The results demonstrate that PANOMA provides a tangible BER performance improvement over conventional power-domain NOMA when both schemes use suboptimal power assignment, which is typically experienced in practical scenarios involving channel time variation and CSI estimation errors. Specifically, it will be shown that both schemes provide similar BERs using optimal assignment, but the PANOMA offers BER reduction by a factor of 10 for certain scenarios when suboptimal power values are assigned. The integrity of the analytical results is verified via matching extensive Monte Carlo simulation experiments.

This work presents the symbol error rate (SER) and outage probability analysis of multi-layer unmanned aerial vehicles (UAVs) wireless communications assisted by intelligent reflecting surfaces (IRS). In such systems, the UAVs may experience high jitter, making the estimation and compensation of the end-to-end phase for each propagation path prone to errors. Consequently, the imperfect phase knowledge at the IRS should be considered. The phase error is modeled using the von Mises distribution and the analysis is performed using the Sinusoidal Addition Theorem (SAT) to provide accurate results when the number of reflectors$L\leq 3$, and the Central Limit Theorem (CLT) when$L\geq 4$. The achieved results show that accurate phase estimation is critical for IRS based systems, particularly for a small number of reflecting elements. For example, the SER at 10−3degrades by about 5 dB when the von Mises concentration parameter$\kappa =2$and$L=30$, but the degradation for the same$\kappa $surges to 25 dB when$L=2$. The air-to-air (A2A) channel for each propagation path is modeled as a single dominant line-of-sight (LoS) component, and the results are compared to the Rician channel. The obtained results reveal that the considered A2A model can be used to accurately represent the A2A channel with Rician fading.

This paper considers the optimization of a dual-functional radar and communication (RadCom) system with the objective is to maximize its sum-rate (SR) and energy-efficiency (EE) while satisfying certain radar target detection and data rate per user requirements. To this end, novel RadCom precoder schemes that can exploit downlink radar interference are devised for massive multiple-input-multiple-output (MIMO) orthogonal frequency-division multiplexing (OFDM) systems. First, the communication capacity and radar detection performance metrics of these schemes are analytically evaluated. Then, using the derived results, optimum beam power allocation schemes are deduced to maximize SR and EE with modest computational complexity. The validity of the analytical results is confirmed via matching computer simulations. It is also shown that, compared to benchmark techniques, the devised precoders can achieve substantial improvements in terms of both SR and EE.

Non-orthogonal multiple access (NOMA) is a promising candidate for future mobile networks as it enables improved spectral-efficiency, massive connectivity and low latency. This paper derives exact and asymptotic bit error rate (BER) expressions under Rayleigh fading channels for NOMA systems with arbitrary number of users and arbitrary number of receiving antennas and modulation orders, including binary phase-shift keying and rectangular/square quadrature amplitude modulation. Furthermore, the power coefficients' bounds, which ensure users' fairness, and solve the constellation ambiguity problem, are derived for N=2 and 3 users cases with any modulation orders. In addition, this paper determines the optimal power assignment that minimizes the system's average BER. These results provide valuable insight into the system's BER performance and power assignment granularity. For instance, it is shown that the feasible power coefficients range becomes significantly small as the modulation order, or N, increases, where the BER performance degrades due to the increased inter-user interference. Hence, the derived expressions can be crucial for the system scheduler in allowing it to make accurate decisions of selecting appropriate N, modulation orders, and power coefficients to satisfy the users' requirements. The presented expressions are corroborated via Monte Carlo simulations.

This paper considers the deployment of intelligent reflecting surfaces (IRSs) technology for wireless multi-hop backhauling of multiple basestations (BSs) connected in a mesh topology. The performance of the proposed architecture is evaluated in terms of outage and symbol error probability in Rician fading channels, where closed-form expressions are derived and demonstrated to be accurate for several cases of interest. The analytical results corroborated by simulation, show that the IRS-mesh backhauling architecture has several desired features that can be exploited to overcome some of the backhauling challenges, particularly the severe attenuation at high frequencies. For example, using IRS with four elements, N=4, provides a symbol error rate of about 10-5at a signal-to-noise ratio of about 0 dB, even for a large number of hops. Moreover, the obtained analytical results corroborated by Monte Carlo simulation show that the gain obtained by increasing N decreases significantly for N > 5. For example, increasing N from 1 to 2 provides about 8dB of gain, while the increase from 3 to 4 provides about 4dB. Moreover, the degradation caused by the relaying process becomes negligible when the number of IRS elements N= 3.

This paper considers hybridization of non-orthogonal multiple access (NOMA) and Orthogonal multiple access (OMA) schemes for next-generation cellular networks. The proposed hybrid multiple access (HMA) scheme considers a multi-cell environment that combines NOMA/OMA mode selection as well as channel and power allocation to improve the resource utilization and bandwidth efficiency. The NOMA/OMA modes are categorized into intra-cell and inter-cell OMA and NOMA modes based on an interference map. The HMA focuses on determining the best mode of operation between user pairs to improve the overall sum rate and quality of service (QoS). Results show that the proposed NOMA/OMA mode selection provides superior performance to the conventional OMA schemes without compromising the QoS demands.

The global market for unmanned aerial vehicles (UAVs) has grown substantially over the past decade and has become a high point for economic growth in many countries. Hence integrating UAVs with cellular networks is considered pivotal to tapping into new business opportunities for cellular operators, especially as the smartphone market is almost saturated. In this paper, we propose a new scheme for efficiently integrating UAVs within 5G cellular systems. To this end, we separate the UAV control and non-payload communication links (CNPC) from high-capacity data communication links-by decoupling the uplink (UL) and downlink (DL) access-to allow user equipments (UEs) to connect to different base-stations (BSs) and transmit over different frequency bands in the UL and DL, such that the interference between ground UEs (GUEs) and UAVs is significantly reduced. The ground UE-BS links are also decoupled in a similar fashion to further minimize interference and maximize energy-efficiency. The numerical results validate the effectiveness of the proposed scheme and quantify the improvement in terms of the data rate of UAVs and GUEs in comparison to coupled benchmarks.

In this paper, we evaluate the performance of NOMA system in downlink scenario over a well-known generalized fading channel called α-η-μ in terms of the Average Bit Error Rate (ABER). The exact closed-forms of Average Bit Error Rate (ABER) for two NOMA users case are obtained in this work in order to study the significant of different fading parameters such as the non-linearity (α), the different power between the in-phase and quadrature components of the signal (η), and the amount of multipath clusters (μ). Therefore, the Bit Error Rate (BER) of BPSK modulation technique is averaged by the probability of density function (PDF) of frequency flat fading channel modelled by α-η-μ fading distribution. This work is being validated via a Monte Carlo Simulation to show the correction of the analytical derivations. However, this particular generalized fading channel can introduce other non-homogeneous attributes of the transmission medium such as Rayleigh, Weibull, Nakagami-m, α-η, α-μ fading channel models as special cases, which makes it more essential and worthy to be investigated.

In this paper, we propose a novel technique to integrate millimeter wave (mmWave) communication into the popular direct short-range communication (DSRC) standard to achieve ultra-reliable, low-latency, and high data rate communication (URLLHDC). Specifically, a vehicle is equipped with a front and a rear directional mmWave antenna as well as a DSRC omni-directional antenna. Then, we design a clustering protocol that groups vehicles driving in the same lane by multi-hop mmWave links. To minimize collisions and latency, only the first and last vehicles in the cluster will enable the DSRC channel acting as gateways for the remaining DSRC-inactive cluster members. The proposed scheme is evaluated using realistic VANET simulators, namely, VEINS and SUMO. The results show that the scheme can achieve URLLDHC in different road densities and with negligible overheads.

This study analyses the performance of downlink non‐orthogonal multiple‐access (NOMA) networks over independent but not necessarily identically distributed Rayleigh fading channels by deriving closed‐form expressions for the average signal‐to‐interference‐plus‐noise ratio (SINR), average achievable rate, and outage probability of all network users. Moreover, SINR‐based power allocation strategies are studied. Specifically, the optimisation problems of max–min SINR, multi‐objective SINR, sum‐SINR and proportional‐fairness‐SINR maximisation under minimum SINR constraints are formulated and shown to be non‐convex. Additionally, the problems of total power and sum‐SINR minimisation are also formulated. Particularly, the formulated problems take the form of linear‐fractional programming problems. By applying intelligent reformulation techniques, these problems have been reformulated into convex optimisation problems, and thus efficiently solved. Numerical evaluations are presented to validate the derived closed‐form expressions for the different performance metrics, which are found to be in agreement with the network simulation results. More importantly, it has been demonstrated that the user with the best channel conditions achieves full diversity order, whereas all the other users achieve diversity orders equivalent to their ordered channel conditions. Finally, the reformulated power allocation strategies are evaluated, and shown to coincide with the original problem formulations.

In this study, the problem of joint relay selection and power allocation (J‐RS‐PA) for NOMA‐based multicast cognitive radio networks is considered. In particular, the aim is to simultaneously maximise the end‐to‐end SINR/SNR of the primary and secondary transmitter–receiver (TR) pairs, subject to quality‐of‐service (QoS) constraints. Communication between the primary and secondary TR pairs is performed over two‐phases, namely, the broadcasting phase, and the cooperation phase. In the broadcasting phase, the primary and secondary transmitters broadcast their data symbols; while in the cooperation phase, the selected relay forwards the decoded symbols to their intended receivers. However, the formulated J‐RS‐PA problem happens to be non‐convex, resulting in computationally‐prohibitive complexity. Consequently, an optimal low‐complexity two‐stage relay selection and power allocation (TS‐RS‐PA) algorithm is devised, which is based on the solution of linear programming problem reformulations. Simulation results are presented to validate the proposed TS‐RS‐PA algorithm, which is shown to yield the optimal SINR/SNR values in comparison to the J‐RS‐PA scheme, but with lower computational complexity, while satisfying QoS constraints.

This article presents a novel decision fusion algorithm for Internet-of-Things-based wireless sensor networks, where multiple sensors transmit their decisions about a certain phenomenon to a remote fusion center (FC) over a wide area network. The proposed algorithm denoted as the individual likelihood approximation (ILA) can significantly reduce the decision fusion error probability performance while maintaining the low computational complexity of other state-of-the-art fusion algorithms. The performance of the ILA rule is evaluated in terms of the global fusion probability of error, and an efficient analytical expression is derived in terms of a single integral. The analytical results corroborated by Monte Carlo simulation show that the ILA significantly outperforms all other considered rules, such as the Chair-Varshney (CV) and MaxLog rules. Moreover, the impact of the link from the cluster head to the FC, which is modeled as a binary symmetric channel with unknown transition probabilities, has been investigated. It is shown that the probability of error over such links should not exceed 10-3to avoid severe performance degradation. Furthermore, we derive a closed-form expression for the system fusion error probability of the CV rule for the most general system parameters.

In this paper, the problem of joint subcarrier assignment and weighted-sum energy-efficient power allocation (J-SA-WSEE-PA) in multi-carrier uplink NOMA relay networks is considered. Specifically, the aim is to assign subcarriers to network users, while maximizing the weighted-sum energy-efficiency, subject to quality-of-service (QoS) constraints. The J-SA-WSEE-PA problem is shown to be non-convex, and thus is computationally-intensive. In turn, it is split into two subproblems: (1) WSEE maximizing power allocation per subcarrier, and (2) matching-theoretic subcarrier assignment. For the first sub-problem, a low-complexity iterative solution procedure is devised to optimally solve the WSEE-maximizing power allocation problem per subcarrier. As for the second sub-problem, a linear time-complexity stable matching algorithm based on the hospitals-residents matching problem is proposed to assign subcarriers to network users. Simulation results are presented to validate the devised solution procedure and the proposed stable matching algorithm, where it has been shown they yield comparable network sum energy-efficiency to the J-SA-WSEE-PA scheme, while satisfying QoS constraints.

In this paper, the problem of joint relay selection and power allocation (J-RS-PA) for NOMA-based multicast cognitive radio networks is considered. In particular, the aim is to simultaneously maximize the SINR/SNR of the primary and secondary transmitter-receiver (TR) pairs, subject to quality-of-service (QoS) constraints. Communication between the primary and secondary TR pairs is performed over two-phases, namely, the broadcasting phase, and the cooperation phase. In the broadcasting phase, the primary and secondary transmitters broadcast their data symbols to the intermediate relays; while in the cooperation phase, the selected relay forwards the decoded symbols to their intended receivers. However, the J-RS-PA problem happens to be non-convex (i.e. computationally-prohibitive). Alternatively, an optimal low-complexity two-stage relay selection and power allocation (TS-RS-PA) algorithm is devised, which is based on the solution of intelligent linear programming problem formulations. Simulation results are presented to validate the proposed TS-RS-PA algorithm, which has been shown to yield the optimal SINRlSNR values for the primary and secondary TR pairs in comparison to the J-RS-PA scheme, but with lower computational complexity, while satisfying QoS constraints.

In this paper, the problem of joint relay selection and global energy-efficient power allocation in energy-harvesting cooperative non-orthogonal multiple-access (NOMA) networks is studied. In particular, a base-station communicates with multiple users via a selected energy-harvesting relay, such that network global energy-efficiency (GEE) is maximized, subject to quality-of-service (QoS) constraints. To that end, the problem of joint-relay selection and global energy-efficient power allocation (J-RS-GEE-PA) is formulated, which happens to be non-convex (i.e. computationally-expensive). In turn, the J-RS-GEE-PA problem is decoupled into two sub-problems: (1) relay selection, and (2) GEE power allocation. Different relay selection schemes are explored, and then a computationally-efficient algorithm is devised to optimally solve the GEE power allocation problem for the selected relay. In addition, a low-complexity solution procedure is proposed to solve the J-RS-GEE-PA problem, so as to achieve the global optimal solution. Simulation results are presented to evaluate the resulting network GEE for the different relay selection schemes, and the proposed solution procedure. More importantly, the proposed solution procedure is shown to yield the optimal network GEE when compared to the J-RS-GEE-PA, and superiority to the other relay selection schemes, while maintaining QoS.

This paper studies device-to-device (D2D) group association and channel assignment in uplink multi-cell non-orthogonal multiple-access (NOMA) networks. In particular, the goal is to assign D2D groups to cellular user channels at each base-station, while accounting for the interference caused by pairing users with D2D groups. To that end, a multi-objective signal-to-interference-plus-noise ratio (SINR)-maximizing power allocation solution procedure is proposed to determine the optimal power allocation for each (D2D group, user) pair, while meeting quality-of-service (QoS) requirements. After that, the joint D2D group association and channel assignment problem is modeled as a student-project allocation with preferences over (student, project) pairs matching problem. Then, a polynomial-time complexity stable matching algorithm is proposed to pair D2D groups with users, and associate them with base-stations. Simulation results are presented to evaluate the proposed matching algorithm, and compare it to a joint D2D group association, channel assignment and power allocation (J-GA-CA-PA) scheme. The proposed algorithm is shown to efficiently yield comparable SINR-per user and D2D receiver-to the J-GA-CA-PA scheme, while maintaining QoS requirements.

This paper considers joint relay selection and maxmin energy-efficient power allocation (J-RS-MMEE-PA) in downlink multi-cell non-orthogonal multiple-access (NOMA) networks. Particularly, the aim is to perform relay selection for each user within each cell, so as to achieve max-min energy-efficiency, while satisfying quality-of-service (QoS) constraints. However, the J-RS-MMEE-PA problem happens to be non-convex (i.e. computationally-intensive). In turn, a solution procedure for maxmin energy-efficient power allocation is devised to determine the energy-efficiency per potential relay, while meeting the target minimum rate per user. After that, the relay selection problem is modeled as a student-project allocation with preferences over projects matching problem, where a polynomial-time complexity stable matching algorithm is proposed to pair users with relays within each cell. Simulation results are presented to validate the proposed stable matching algorithm, where it is demonstrated that it efficiently yields comparable energy-efficiency per user to the J-RS-MMEE-PA scheme, while satisfying QoS constraints.

This paper proposes a multi-level interference mapping (MIM) technique for enabling spectral-reuse maximization in cellular networks. The basic idea is to generate a user-centric interference map that can lead towards maximum resource reutilization. We focus on studying the impact of this map on the aggregate throughput, quality of service (QoS) and latency performance. In the proposed method, an interference intensity map, which indicates the level of interference between conflicting Base Stations (BSs) and users, is constructed based on each user's perspective. The purpose of this map is to classify users according to the level of interference they receive from the surrounding interfering BSs, which is used to impose orthogonalization between certain BSs and users. Such classification is then utilized jointly with power-control to achieve the maximum possible reuse efficiency without compromising QoS. For validation purposes, the performance of the proposed scheme is evaluated and compared with a predefined threshold approach, which represents the minimum required signal-to-interference-plus-noise-ratio (SINR). The results showed the impact of the number of interference levels on the network performance. It was shown that the MIM outperforms the predefined threshold approach and that increasing the interference levels improves the overall performance.

This study examines the uplink performance of large‐constellation multi‐user massive multiple‐input multiple‐output systems with low‐resolution analogue‐to‐digital converters (ADCs) in the presence of channel correlation and imperfect channel state information (CSI). The base station (BS) employs a large number of antennas for multiplexing and demultiplexing co‐channel users with each antenna element having a dedicated radio frequency chain and two low‐resolution ADCs. While such ADCs cause data loss due to coarse quantisation, the large number of antennas can be exploited not only to alleviate such a problem but also to make it possible to utilise large‐constellation modulation schemes. The results provide an insight into the trade‐off between various performance metrics and the number of quantisation bits under a wide range of realistic conditions. It will be shown that 1‐bit quantisation provides sufficient resolution with 100 BS antennas to communicate with ten user equipments using quadrature phase shift keying, but the number of quantisation bits must be increased for larger constellations particularly to overcome CSI mismatch and channel correlation. The results also consider the trade‐off between average mutual information and power consumption of the low‐resolution ADCs. It will be shown that 16‐quantum amplitude modulation with 2‐bit quantisation may provide a good compromise between energy efficiency and average mutual information.

This paper studies joint device-to-device (D2D) group association and channel assignment in uplink multi-cell non-orthogonal multiple-access (NOMA) networks. Particularly, the goal is to assign D2D groups to cellular user channels at each base-station, while accounting for negative network externality due to the interference caused by pairing a user with a D2D group. To that end, a multi-objective signal-to-interference-plus-noise ratio (SINR)-maximizing power allocation solution procedure is proposed to determine the optimal power allocation for each (D2D group, user) pair, while meeting quality-of-service (QoS) requirements. After that, the joint D2D group association and channel assignment problem is modeled as a student-project allocation with preferences over (student, project) pairs matching problem. More specifically, two polynomial-time complexity stable matching algorithms are proposed to pair D2D groups with users, and associate them with base-stations. Simulation results are presented to evaluate the proposed matching algorithms when combined with the devised solution procedure, and compare them to a joint D2D group association, channel assignment and power allocation (J-GA-CA-PA) scheme. More importantly, the proposed algorithms are shown to efficiently yield comparable SINR-per user and D2D receiver-to the J-GA-CA-PA scheme, while maintaining QoS requirements.

In sports stadia and similar crowded venues, maintaining an acceptable network quality of experience (QoE) becomes a difficult task. Currently, the problem is approached via small cells, distributed antenna systems and high-density WiFi, which are complex and expensive. Hence, we propose a distributed low-cost solution based on user coordination to improve the average QoE without increasing the network capacity. Specifically, fans take turns in disabling their cellular connectivity, such that the connected users utilize the relaxed network to share common match data with the disconnected users via Peer-to-Peer (P2P) connectivity. To eliminate a free-riding behavior, a limited punishment strategy is proposed and shown to yield an approximate subgame-perfect Nash equilibrium. MATLAB simulations demonstrate tangible gains in average QoE when the number of users of the proposed scheme is significant.

In this paper, the problem of distributed multirelay selection in energy-harvesting cooperative wireless networks is studied and modeled as an Indian Buffet Game (IBG). Particularly, the IBG is utilized to model the multi-relay selection decisions of network source nodes, while taking into account the negative network externality. Since the relays are energy-harvesting (and thus intermittently harvest random amounts of energy), the accumulated energy at each relay is unknown to the source nodes, leading to uncertain relays' energy states. In turn, a non-Bayesian learning algorithm is devised for source nodes to learn the relays' energy states. After that, a distributed best-response multi-relay selection (BR-MRS) recursive algorithm is proposed to allow source nodes to make multi-relay selections, while guaranteeing subgame perfect Nash equilibrium. Simulations results are presented to verify the efficacy of the proposed algorithm when compared to other multi-relay selection schemes, and illustrate that it yields comparable rate improvement (and utility) to the centralized multi-relay selection.

Millimeter-wave communication is limited by high penetration and pathloss but can be used in base stations closer to the user terminals through heterogeneous networks to maximize spectrum usage and enrich coverage. This paper compares the performance of single and dual connectivity from both perspectives of pathloss and capacity. We also expand our capacity based association approach proposed in [12] to work in UHF-mmWave hybrid networks where mobile users can connect to different ultra high frequency small cells, millimeter-wave small cells and ultra high frequency macro cells with the option of decoupling. The results provide an insight into the performance of such techniques and network typologies for various performance metrics of interest. It will be shown that dual connectivity is not always superior and that single and dual hybrid connectivity can be a better choice. It will also be shown that wireless networks with both ultra high frequency and millimeter-wave small cells achieve higher capacity than those with only one kind of small cells.

In this paper, we investigate joint power allocation and time switching (TS) control for energy efficiency (EE) optimization in a TS-based simultaneous wireless information and power transfer (SWIPT) non-orthogonal multiple access (NOMA) system. Our aim is to optimize the EE of the system whilst satisfying the constraints on maximum transmit power, minimum data rate and minimum harvested energy per-terminal. The considered EE optimization problem is formulated and then transformed according to the duality of broadcast channels (BC) and multiple access channels (MAC). The corresponding non-linear and non-convex optimization problem, involving joint optimization of power allocation and time switching factor, is difficult to solve directly. In order to tackle this problem, we develop a dual-layer algorithm where a convex programming-based Dinkelbach's method is proposed to optimize the power allocation in the inner-layer and an efficient search method is then applied to optimize the TS factor in the outer-layer. Numerical results validate the theoretical findings and demonstrate that significant performance gain over orthogonal multiple access (OMA) scheme in terms of EE can be achieved by the proposed algorithm in a SWIPT-enabled NOMA system.

This paper analyzes the performance of downlink non-orthogonal multiple-access (NOMA) networks over independent but not necessarily identically distributed Rayleigh fading channels for arbitrary number of network users. Specifically, closed-form expressions for the average SNR, average achievable rate, and outage probability are derived, where it has been shown that network users achieve diversity orders equivalent to their ordered channel gains. Numerical evaluations are presented to validate the derived closed-form expressions for the different performance metrics, which are found to be in agreement with the network simulation results.

Unequal error protection (UEP) divides the data into different levels of importance in order to ensure that the most important parts of the source information have more protection than the less important parts. In this study, the authors investigate the application of UEP using polar codes and propose a technique that utilises the channel polarisation property of these codes to achieve UEP without any significant modification. They demonstrate the error bounds of the proposed technique particularly within the context of JPEG2000. In addition, they propose a joint source‐channel decoding method that is based on iterative decoding. This method takes the advantage of the error resilience tools that already exist in the JPEG2000 decoder. It will be shown that the proposed technique offers better performance than the conventional transmission with equal error protection.

This paper proposes a cooperative clustering protocol based on the low energy adaptive clustering hierarchy approach to enhance the longevity of energy harvesting-based wireless sensor networks (EH-WSN). In the proposed protocol, to ensure that any energy consumption associated with the role of the cluster head (CH) is shared between the nodes, the CH role is alternated between the nodes using duty cycling as a function of their individual energy harvesting capabilities. Furthermore, to maintain an energy neutral operation when not acting as a CH, the nodes adopt a data transmission duty cycle and any excess energy is invested in relaying other nodes' packets. To optimize the relaying performance, a novel cross-layer cooperative TDMA scheme is also presented. The optimal number of clusters in an EH-WSN is analyzed in terms of energy consumption, latency, and bandwidth utilization. Simulations, performed using GreenCastalia, demonstrate tangible performance enhancements in adopting the proposed protocol over benchmark schemes in terms of throughput and lifetime, particularly under highly constrained energy conditions.

This paper proposes a variant of the low energy adaptive clustering hierarchy (LEACH) routing protocol that is suitable for energy harvesting wireless sensor networks (EH-WSNs). In the proposed design, the cluster head (CH) role is shared by the network nodes so that the associated energy consumption is balanced between the nodes with duty cycling as a function of the nodes' energy harvesting capabilities. Also, during the non-CH rounds, a node adopts data transmission duty cycling to maintain energy neutrality operation extending the network lifetime. The optimal number of clusters in energy harvesting networks is analyzed and shown not to minimize the network energy consumption. Simulations performed using GreenCastalia demonstrate tangible performance enhancements in adopting the proposed protocol over benchmark schemes in terms of throughput and lifetime, particularly under highly constrained energy conditions.

IEEE 802.11ah is a WiFi standard developed to support M2M communications, among other things. It caters for sub 1 GHz long range transmissions. However, this long range exacerbates the hidden node problem. Sectorization and grouping have been proposed to mitigate the hidden node problem. Sectorization can also be used to eliminate the overlapping basic service set problem. In this paper, we create hidden node-free groups using the Welsh Powell algorithm. We propose the setting of backoff timers using AIDs of STAs in the group and analyse the maximum throughput that can be attained by the network in the presence of packet errors. Our simulation results show a 45% improvement in throughput compared to existing techniques.

Physical layer security (PHY-SEC) research had shown promising results to be a potential candidate for providing security functionalities. In this paper, we propose a random constellation mapping technique for secret key exchange in Spatial Modulation (SM) systems in which we exploit the inherent symbol-antenna mapping feature of this transmission technique. In addition, the proposed technique imposes a random phase shift to each of the modulated symbols using a channel driven method in order to uniquely authenticate the transmitted key bits or further the encrypted confidential data. The results show that the proposed technique is superior to benchmark techniques in terms of both computational complexity and key bit error rate. Also, the proposed technique offers further flexibility in terms of preference of the authentication process over other proposed techniques.

The pilot contamination problem is one of the major obstacles that limit the performance of time-division duplex (TDD) multi-cell massive multiple-input multiple-output (MIMO) systems. Pilot contamination results from the re-use of the same set of pilot sequences in the different cells of the system. In this paper, we compare between two different scenarios of pilot signals allocation with respect to the impact of pilot contamination. We derive lower bounds on the achievable rates and study the performance of both scenarios under different system settings. Our results show that although increasing the number of base station (BS) antennas improves the system performance, it does not eliminate the effect of pilot contamination. Thus, when the pilot contamination is high, it should be countered by allocating more system resources for the training phase. This can be achieved by increasing the number of pilot sequences to guarantee an orthogonal pilot sequence for each user in the system. Further, we show that the pilot sequences allocation strategy also depends on the characteristics of the communication environment: a low mobility environment has better performance when orthogonal sequences are allocated to all users while the opposite is true for a high mobility environment.

In this paper, we provide joint subcarrier assignment and power allocation schemes for quality- of-service (QoS)-constrained energy-efficiency (EE) optimization in the downlink of an orthogonal frequency division multiple access (OFDMA)-based two-tier heterogeneous cellular network (HCN). Considering underlay transmission, where spectrum- efficiency (SE) is fully exploited, the EE solution involves tackling a complex mixed-combinatorial and non-convex optimization problem. With appropriate decomposition of the original problem and leveraging on the quasi-concavity of the EE function, the problem can be efficiently solved. On the other hand, the inherent inter-tier interference from spectrum underlay access may degrade EE particularly under dense small-cell deployment and large bandwidth utilization. We therefore develop a novel resource allocation approach based on the concepts of spectrum overlay access and resource efficiency (RE) (normalized EE-SE trade-off). Specifically, the optimization procedure is separated where the macro- cell optimal RE and the corresponding bandwidth is first determined, then the EE of small-cells utilizing the remaining spectrum is maximized. Simulation results confirm the theoretical findings and demonstrate that the proposed resource allocation schemes can approach the optimal EE with each strategy being superior under certain system settings.

The pilot contamination problem is one of the major obstacles that limit the performance of time-division duplex (TDD) multicell massive multiple-input multiple-output (MIMO) systems. Pilot contamination results from the re-use of the same set of pilot sequences in the different cells of the system. In this paper, we propose an Adaptive Pilot Allocation (APA) algorithm for pilot contamination mitigation. The proposed algorithm divides the users in the system into two groups according to the inter-cell interference they cause to the other users in the system. To improve the system performance, the algorithm allocates orthogonal pilot sequences to the users that can cause high inter-cell interference. Simulation results show that the proposed algorithm outperforms the conventional (random) allocation method. Also it show that the proposed algorithm improves both the minimum and the mean achievable rates.

Massive multiple-input multiple-output (MIMO) systems are expected to achieve significant gains in both energy and spectral efficiency compared to conventional MIMO systems. However, these promising gains are limited by the impact of pilot contamination in TDD multicell massive MIMO which results from reusing the same set of pilot sequences in all the system's cells. In this paper, we propose an algorithm for pilot sequences allocation that aims to maximize the minimum achievable rate in a target cell by utilizing the availability of the large-scale fading information at the BSs. Our results show that the proposed algorithm can significantly improve both the spectral efficiency and the minimum achievable rate compared to the conventional pilot allocation scheme which assigns the pilot sequences randomly.

Time‐division duplex (TDD) is the most efficient technique for acquiring channel state information in massive multiple‐input multiple‐output (MIMO) systems where the reciprocity between the uplink and downlink channels is utilised by the pilot signals to extract the channel parameters. In this study, the authors consider the pilot contamination problem in TDD multicell multiuser massive MIMO systems and examine two different pilot signal allocation schemes for which they derive the lower bounds on the achievable rate on the uplink for the cases of maximum‐ratio combining (MRC) and zero‐forcing (ZF) detectors. To achieve further performance enhancements, they propose a new algorithm for pilot sequences allocation in which the multiplicity of the pilot sequences over the number of users in each cell is exploited. The authors' results show that when pilot contamination is severe, allocating more system resources for channel estimation results in a better system performance especially in limited mobility environments. Moreover, they show that when the signal‐to‐interference plus noise ratio is low, MRC is superior to ZF, and vice versa. Finally, they demonstrate that their proposed allocation algorithm can significantly improve the spectral efficiency of the network compared to the conventional pilot allocation method.

In wireless communication systems, the conventional secret key exchange is based on the public key cryptography, which requires complex computations to retain the secrecy level of these key bits. The proposed physical layer‐based algorithms have shown promising performance to extract secret keys from the privately shared randomness relying on the reciprocal channel state between both communicated nodes. In this study, the authors propose a physical layer key exchange method which transmits the key bits by encoding them within some phase randomisation (PR) sequences that are privately indexed to a specific channel criterion. The PR sequences only randomise the data phases and thus no efficiency reduction will be incurred. In fact, by choosing a pool of randomisation sequences with certain statistical properties, they could also be used to condition the signal to meet physical layer transmission requirements such as bandwidth, envelope and so on. They quantify the potential of the proposed method by demonstrating it within the context of a multiple‐input multiple‐output orthogonal frequency division multiplexing system. The results reveal that, relative to existing techniques, the proposed method offers superior key error rate performance at lower computational complexity with better secrecy level.

This paper investigates the capacity and energy consumption metrics of small-cell networks that are enabled with sleep mode (SL) functionality. A novel method is introduced to systematically and accurately identify the potential SL cells that can maximize the spectrum reuse efficiency without the need for an exhaustive search. The performance of the proposed technique is assessed and compared with the always-on approach and an optimal benchmark. The results show that the proposed method significantly outperforms the always-on system and approaches the performance of the optimal benchmark with notably reduced computational burden.

Energy-harvesting (EH) and wireless power transfer are increasingly becoming a promising source of power in future wireless networks and have recently attracted a considerable amount of research, particularly on cooperative two-hop relay networks in Rayleigh fading channels. In contrast, this paper investigates the performance of wireless power transfer based two-hop cooperative relaying systems in indoor channels characterized by log-normal fading. Specifically, two EH protocols are considered here, namely, time switching relaying (TSR) and power splitting relaying (PSR). Our findings include accurate analytical expressions for the ergodic capacity and ergodic outage probability for the two aforementioned protocols. Monte Carlo simulations are used throughout to confirm the accuracy of our analysis. The results show that increasing the channel variance will always provide better ergodic capacity performance. It is also shown that a good selection of the EH time in the TSR protocol, and the power splitting factor in the PTS protocol, is the key to achieve the best system performance.

We devise a framework using tools from stochastic geometry and queuing theory for the study of irregular cellular networks when user traffic varies randomly in time and space. We consider a typical wireless cell with a guard zone surrounded by an interference environment comprised of a dominant node at the guard-edge plus an outer-bound Poisson field of sources. A systematic approach is presented to characterize the flow rate in the presence of elastic data traffic with closed-form expressions of the intended signal power and bounded aggregate interference statistics over Nakagami-m fading channels accordingly derived. We then formulate and solve an optimization problem for the computation of the traffic capacity defined as the maximum elastic data flow intensity for which the system remains unsaturated.

The demands for higher data rates and network decentralized nodes in wireless communication systems urge the need for efficient methods to preserve the security levels. Many of the existing methods to share a private secret key between the connected nodes, tend to have high computational complexity. Furthermore, most physical layer approaches assume TDD systems to use the intrinsic feature of the reciprocal channels. In this paper, we propose a new method for exchanging secret key bits using a private random precoding based in MIMO FDD systems. The principle of this method is to exploit the PMI in a manner that produces low correlation at the intruder. By uniquely relating the secret key bits to the channel precoding matrix in a private version of the universal codebook, a robust key exchange between the transmitter and the receiver is then performed.

This paper studies power allocation and relay selection strategies in energy harvesting cooperative wireless networks for end-to-end signal-to-noise ratio (SNR) maximization. Energy cooperation via wireless energy transfer is also considered to efficiently utilize harvested energy. Particularly, different optimal strategies are formulated as optimization problems, which are non-convex. Intelligent transformations are applied to transform non-convex problems into convex ones, and polynomial-time solution procedures are proposed. Simulation results illustrate that power allocation strategies achieve higher end-to-end SNR than relay selection ones. Finally, energy cooperation is shown to be effective in improving the end-to-end SNR.

In this paper, power allocation over time-varying multi-user multi-relay amplify-and-forward networks is studied. Specifically, stochastic network sum-rate and max-min rate power allocation problems are formulated. However, solving such stochastic problems relies on perfect global instantaneous channel state information (CSI), and thus entails complex computations and excessive communication overheads. To circumvent these issues, second-order statistics of the CSI (i.e. partial CSI) are utilized to transform the stochastic formulations into deterministic optimization problems in terms of ergodic capacity while satisfying quality-of-service constraints via target outage probability. The obtained optimal deterministic problems are non-convex and thus are computationally prohibitive. However, at high enough signal-to-noise ratio, such problems can be transformed into asymptotically convex ones, and thus solved efficiently. Simulation results illustrate that the proposed approximate deterministic power allocation reformulations coincide with their optimal exact deterministic and dynamic counterparts.

This paper proposes a resource allocation technique for distributed and uncoordinated femtocell networks. We focus on enhancing the Quality of Service (QoS) and throughput by relying only on feedback from the base-station's (BS) users in addition to locally estimated information from the surrounding environment. A novel algorithm is developed to analyze the uplink (UL) interference in order to estimate the number of neighboring users in the vicinity of a femtocell without requiring any information exchange with a central unit or neighboring femtocells. The downlink inter-cell interference is reduced by utilizing the variability in the interference conditions of femtocells and restricting the resource usage of individual cells based on the detected nearby users. The performance of the algorithm is evaluated and compared with state-of-art techniques and benchmarks. The simulation results show that the proposed scheme outperforms other techniques and can provide an improvement in the QoS and overall performance. and overall performance.

In this paper, we present a power allocation technique that improves the sum rate and energy efficiency without reducing the minimum data rate of an established resource block allocation technique. To achieve this, the technique is implemented in two stages where the first is for ensuring that the minimum data rate remains unchanged. The second stage is for increasing the sum rate by ensuring that more resource blocks are reused by the femtocells that reduce their power. The algorithm is iterative with changes in transmit power resulting in changes in resource block allocation. It will be shown that at the expense of some delay, the proposed technique can result in significant energy savings while maintaining the minimum data rate when compared to equal power allocation. Further, relative to optimal allocation techniques, the proposed technique results in better fairness.

We present an analytical model for the design and analysis of dense cellular networks (DenseNets) where load-awareness is explicitly incorporated in the system performance. New bounded expressions of aggregate interference and average rate are developed considering spatially-correlated heterogeneous sources. Subsequently, an optimization problem for pinpointing the optimal network density which minimizes the total energy expenditure is formulated and tackled. The validity of our framework and its advantages over the existing fully-loaded and interference- thinning methods are depicted via Monte-Carlo simulations. Based on state-of-the-art system parameters, a homogeneous pico deployment is revealed to be the most energy-efficient solution in future dense urban environments.

We propose an analytical stochastic geometry-based model for multiple-input multiple-output (MIMO) heterogeneous cellular networks (HetNets) with zero-forcing (ZF) precoding at transmitting base stations (BSs) and partial zero-forcing (PZF) beamforming at receiving user equipments (UEs). The user and area spectral efficiencies are characterized using a non-direct moment- generating-function (MGF) methodology with closed- form expressions of the intended signal power and aggregate network interference statistics accordingly developed. The impact of different cellular network deployments, antenna configurations, and transmission schemes on achievable performance are examined through theoretical and simulation studies. The results confirm the promising potential of multi-antenna communications and small-cell solution in emerging wireless environments.

The application of stochastic geometry theory for the study of cellular networks has gained huge popularity recently. Most existing works however rely on unrealistic assumptions concerning the underlying user traffic model. This paper aims to make a step in this direction by devising a new model for the performance analysis and optimization of heterogeneous cellular networks (HetNets) with irregular BS deployment and flow- level traffic dynamics. We provide a unified methodology for the evaluation of the flow rate with closed-form expressions of the useful signal power and aggregate network interference over Nakagami-m fading channels. The problem of computing the optimal loading factors which result in the greatest sustainable traffic whilst the system remains stable is formulated and tackled.

Channel correlation between different users can significantly deteriorate the energy and spectral efficiency of massive MIMO systems. As such, it is tempting to separate the highly correlated users in order to reduce intra-cell interference to improve the overall system performance. In this respect, and unlike existing work, we propose an adaptive user grouping algorithm for the downlink of multiuser massive MIMO systems where users are grouped based on the values of their correlation coefficients. The proposed algorithm is adaptive in the sense that the number of neither the groups nor the users of each group is fixed. Furthermore, the grouping process relies on finding the correlation coefficients that are larger than a certain threshold value and isolating their corresponding users in separate groups which are served in different scheduled time. The threshold value is variable and can be adjusted to achieve the best performance compared to the non grouping scenario. The results reveal that the proposed system can considerably enhance the sum rate performance relative to the non-grouping case for the same bandwidth requirements.

This paper presents a game theoretic multi-relay selection scheme for energy harvesting cooperative networks with non-orthogonal relay channels. Specifically, relays are selected through repeated Stackelberg interactions in which the source updates its payment offer to sequentially induce the next utility maximizing relay to participate by meeting its cost of transmission. The relay cost is assumed to reflect the relay energy profile and channel conditions such that the average utility over several energy harvesting periods is maximized. With only statistical knowledge of channel gains and energy profiles, the source applies Bayesian inference to select its strategy and update its beliefs. The equilibrium of the proposed game, that is, the Perfect Bayesian Equilibrium is shown to exist and its convergence is shown to be controlled by the stage cost. The performance of the proposed technique is then evaluated and compared against other benchmark schemes.

In this paper the joint cost-sharing and multi-relay selection problem in two-way relay networks is modeled as a repeated Bayesian Stackelberg game. In each Stackelberg stage, the two source nodes submit payment offers to the relays targeting the next best relay that maximizes the network power efficiency. Each relay, as a follower, will participate only if its cost will be covered by the payments promised. Assuming asymmetric source utility functions, a source may not always afford its fair share payment and the other source may benefit from covering the shortage in payment. However, because utility functions are private information to each source, Bayesian strategies that maximize the expected utility of players are derived along with a belief update system, which together are shown to constitute a perfect Bayesian equilibrium. Additionally, a means to trade off performance for complexity is realized through a stage game cost factor.

In this paper, the problem of distributed multi-relay selection in cooperative wireless networks is studied via a political coalition formation game approach. Specifically, a sum-rate maximizing distributed coalition formation algorithm is proposed, in which a winning coalition eventually emerges, which is also self-enforcing (and hence stable). In addition, the proposed algorithm offers a sum-rate performance/stability tradeoff through formation of political parties, which also reduces complexity and overheads. The proposed algorithm is compared with centralized multi-relay selection as well as other multi-relay selection algorithms from literature, and is shown to provide comparable network sum-rate with the added advantage of network stability.

In this paper, power allocation over time-varying multiple-access interference channels is studied. Particularly, a stochastic network sum-rate maximizing power allocation problem is formulated, capturing the random nature of communication channels. Typically, a centralized controller must have perfect knowledge of global instantaneous channel state information (CSI) for dynamic optimal power allocation; however, this may not be possible, due to the computational complexity and communication overheads/delays involved. Based on the second-order statistics of the CSI, the stochastic problem formulation is transformed into an optimal deterministic representation in terms of ergodic capacity, while ensuring satisfactory quality of service via target outage probability. However, such deterministic reformulation happens to be non-convex and thus is computationally expensive. In turn, a sub-optimal reformulation is derived and solved via an iterative low-complexity algorithm. Simulation results demonstrate that the proposed deterministic sub-optimal power allocation reformulation coincides with its optimal deterministic counterpart, with the proposed algorithm converging in a finite number of iterations.

Power control and carrier allocation are the main focus of work on interference management in 3G heterogeneous networks. This work introduces interference management in 3G small base stations by coordinating the allocation of orthogonal variable spreading factor codes (OVSF) in order to improve both the guaranteed data rate and the system sum rate. The coordination is done by a centralised controller using an existing algorithm that was previously used to allocate subcarriers in a 4G network. Results show that even without power control, there is significant improvement in guaranteed data rate and sum rate performance of a 3G small cell network.

Interference alignment is an effective capacity achieving technique in wireless networks. We propose a method of achieving maximum degrees of freedom for a considered three-cell compounded MIMO network. We first define the compounded MIMO network as a combination of IC and X-channel, and then design transmit beamforming matrices to mitigate interference under the considered MIMO network scenario. Finally, we analyse the degrees of freedom region of the proposed interference alignment scheme and present results derived for the three-cell MIMO network scenario.

In this study, power allocation over time‐varying multi‐user multi‐relay amplify‐and‐forward networks is studied. Specifically, stochastic network sum‐rate, max–min rate power allocation and total power minimisation problems are formulated. However, solving such stochastic problems relies on perfect global instantaneous channel state information (CSI), and thus entails complex computations and excessive communication overheads. To circumvent these issues, second‐order statistics of the CSI (i.e. partial CSI) are utilised to transform the stochastic formulations into deterministic optimisation problems in terms of ergodic capacity while satisfying quality‐of‐service constraints via target outage probability. The obtained optimal deterministic problems are non‐convex and thus are computationally prohibitive. However, at high enough signal‐to‐noise ratio, such problems can be transformed into asymptotically convex ones, and thus solved efficiently. Simulation results illustrate that the proposed approximate deterministic power allocation reformulations closely agree with their optimal exact deterministic and dynamic counterparts.

This paper presents a stochastic geometry-based framework for the design and analysis of downlink multi-user multiple-input multiple-output (MIMO) heterogeneous cellular networks with linear zero-forcing transmit precoding and receive combining, assuming Rayleigh fading channels and perfect channel state information. The generalized tiers of base stations may differ in terms of their Poisson point process spatial density, number of transmit antennas, transmit power, artificial-biasing weight, and number of user equipments served per resource block. The spectral efficiency of a typical user equipped with multiple receive antennas is characterized using a non-direct moment-generating-function-based methodology with closed-form expressions of the useful received signal and aggregate network interference statistics systematically derived. In addition, the area spectral efficiency is formulated under different space-division multiple-access and single-user beamforming transmission schemes. We examine the impact of different cellular network deployments, propagation conditions, antenna configurations, and MIMO setups on the achievable performance through theoretical and simulation studies. Based on the state-of-the-art system parameters, the results highlight the inherent limitations of baseline single-input single-output transmission and conventional sparse macro-cell deployment, as well as the promising potential of multi-antenna communications and small-cell solution in interference-limited cellular environments.

Interference alignment is an effective technique for reducing interference in wireless networks. This paper proposes a generalized interference alignment and cancellation scheme for a cellular network with multiple-input multiple-output users under a Gaussian interfering broadcast channel scenario. We first focus on a three-cell network scenario to demonstrate the basic principle of how to design the transmit beamforming matrix using a non-iterative closed-form approach. We further analytically define the degree of freedom region and numerically confirm the validity of the proposed scheme. Finally, we generalize the proposed method to the L -cell case and consider the impact of different antenna configurations to maintain the proposed scheme.

Massive multiple-input-multiple-output (MIMO) is a promising technique for providing unprecedented spectral efficiency. However, it has been well recognized that the excessive training overhead required for obtaining the channel side information is a major handicap in frequency-division duplexing (FDD) massive MIMO. Several attempts have been made to reduce this training overhead by exploiting the sparsity structures of massive MIMO channels. So far, however, there has been little discussion about how to exploit the partial support information of these channels to achieve further overhead reductions. Such information, which is a set of indices of the significant elements of a channel vector, can be acquired in advance and hence is an important option to explore. In this paper, we examine the impact on the required training overhead when this information is applied within a weighted ℓ1minimization framework, and analytically show that a sharp estimate of the reduced overhead size can be successfully obtained. Furthermore, we examine how the accuracy of the partial support information impacts the achievable overhead reduction. Numerical results for a wide range of sparsity and partial support information reliability levels are presented to quantify our findings and main conclusions.

Abstract In this paper, optimal power allocation and relay selection strategies in energy harvesting cooperative wireless networks are studied. In particular, signal‐to‐noise ratio (SNR)‐maximizing based power allocation and relay selection without and with energy cooperation—via wireless energy transfer—are considered. Moreover, total relay power minimization subject to target end‐to‐end SNR is investigated. The different optimal strategies are formulated as optimization problems, which are non‐convex. Thus, intelligent transformations are applied to transform non‐convex problems into convex ones, and polynomial‐time solution procedures are proposed. Simulation results illustrate that power allocation strategies achieve higher end‐to‐end SNR than relay selection ones. Finally, energy cooperation is shown to be effective in improving end‐to‐end SNR, while total relay power minimization balances end‐to‐end SNR, transmit power consumption, and harvested energy. Copyright © 2016 John Wiley & Sons, Ltd.

This paper proposes a solution to enhance the performance of femtocell networks. We focus on studying the capacity and QoS behavior of femtocell deployment by utilizing a joint cellular association and resource partitioning strategy. A novel method is proposed to maximize the reuse efficiency by careful partitioning of the frequency resources, such that the interfering parties do not overlap. A cellular association scheme is also developed to improve the resource utilization further, by accurate identification of the association pairs with the potential to increase the reuse efficiency, while taking into consideration several factors such as cell load, the received signal power and the availability of resources. To ensure efficient utilization of the additional resources, the association scheme is combined with the interference aware resource partitioning. For validation purposes, the performance of the proposed scheme is evaluated and compared with the standard Max-RSS Cellular association.The simulation results show good overall performance when compared with the standard association scheme.

Traffic demand is increasing exponentially and operators will need to densify their networks with small cells to meet this demand. This has created economic and ecological concerns due to the high cost of energy and the associated greenhouse gas emissions. In this paper, we apply tools from stochastic geometry to design a deployment strategy for multi-tier heterogeneous networks (HetNets). Using appropriate approximations, we derive simple expressions that allow insights into the energy efficiency (EE) performance of biased and unbiased HetNets. We perform a comprehensive analysis on the effect of biasing on the EE performance of HetNets. We also formulate an optimization framework that minimizes the area power consumption (APC) of the HetNet subject to appropriate performance constraints. Our results show that significant energy savings can be made by appropriately biasing the HetNet and optimizing the BS densities and their transmit powers subject to the performance constraints.

This paper proposes an adaptive scheduling strategy to improve the energy efficiency of massive MIMO. The proposed technique combines a novel adaptive discontinuous transmission (ADTx) and antenna optimization that can optimize the number of active antennas and transmission period such that data can be delivered to users with the minimum power. The proposed ADTx utilizes a DTx principle and adaptive precoding technique selection. On the other hand, antennas optimization is used to relax the number of active antennas once the required period has been calculated. Although massive MIMO is initially designed to utilize the multiplexing users found in dense users scenario, this paper discusses the impact of the proposed technique to low density scenarios, in particular suburban scenario, because major parts of cellular coverage are low density. It will be shown that the proposed scheme provides significant energy efficiency (EE) and QoS improvement that can support green cellular network.

This paper addresses energy efficiency (EE) of large scale antenna systems (LSAS) or massive MIMO based cellular networks. We propose a joint technique that combines a novel successive discontinuous transmission (SDTx) scheme with antenna array optimization (AAO). The SDTx utilizes information regarding the users' requirements and properties to deliver data efficiently and without compromising the users' service. On the other hand, AAO further reduces power consumption through minimizing the number of active antenna elements. Users requirements include bit rate and latency requirement while the users properties include pathloss between users and macro base station (MBS) and users' movement. It will be shown that, relative to conventional LSAS, the proposed scheduling significantly improves the EE of LSAS network for various network load under practical users' requirement in dense urban environment making it a potential candidate for green cellular networks.

Wireless power transfer conveniently enables prolonging the lifetime of energy-constrained wireless nodes by means of scavenging the energy of radio-frequency signals. Most existing work on this topic assumes negligible background noise power and focuses only on harvesting the power signal transmitted by the access point (AP). In contract, in this paper we show that in Gaussian-Bernoulli (GB) impulsive noise channels such an assumption is invalid, especially in highly impulsive noise scenarios. In this respect, we study the performance of a multiple-antenna AP system with an energy- constrained single-antenna destination in various GB impulsive noise environments. The proposed system here adopts the harvest-then-transmit protocol where communication is accomplished over two distinct phases, namely, power transfer phase (down-link) and information transmission phase (up-link). To characterize system performance, we consider the ergodic capacity. An analytical expression for parameter is derived and then validated with Monte Carlo simulations. Results reveal that incorporating GB impulsive noise can considerably improve the performance of energy-harvesting based systems. It is also demonstrated that increasing the number of AP antennas will further enhance the ergodic capacity and that careful selection of the energy- harvesting time is crucial for achieving best performance.

In wireless communication systems, secret key is used to protect confidential transmission. The process of securely exchanging these key bits is critical. Most existing methods require cumbersome calculations which may not be appropriate for limited power devices. In this paper, we propose a physical layer key exchange method which transmits the key bits by encoding them within some phase randomization sequences that are selected according to a certain channel criterion. The phase randomization sequences only randomize the data phases and thus no efficiency reduction will be incurred. The proposed is demonstrated within the context of multiple-input multiple-output orthogonal frequency division multiplexing (MIMO- OFDM) system. The results reveal that, relative to existing techniques, this method offers superior performance and lower computational complexity.

This paper proposes a solution for interference management in femtocell networks. We focus on studying the capacity and energy consumption behavior of femtocell deployment by utilizing a sleep mode strategy. A novel method is proposed to provide a systematic way to accurately select the candidate femtocells that yield a substantial impact in terms of resource utilization when deactivated. Those femtocells are selected by running customized tests that do not require an exhaustive search. For validation purposes, the performance of the proposed scheme is evaluated and compared with the approach without sleep mode activation. Additionally, a maximum likelihood benchmark is also provided for comparison. The simulation results show that the proposed scheme can provide an excellent overall performance and outperforms the always-on system, while approaching the performance of the optimal benchmark scheme with significantly less computational complexity.

This paper investigates the application of orthogonal poly-phase based multi-carrier code division multiple access (OPP-MC-CDMA) over multipath power-line channels perturbed by Middleton class-A noise. The proposed OPP-MC-CDMA system is aided with a minimum-mean square error equalizer combined with nonlinear preprocessing to overcome the effect of bursty noise and multipath fading. We study the performance of this system in terms of the output signal-to-noise ratio (SNR) and symbol error rate with various constellation sizes of OPP codes, different noise scenarios and non-linear processor's thresholds. For comparison-sake, the performance of a conventional orthogonal frequency-division multiple access (OFDM) scheme is included. The results reveal that the proposed approach always provides superior performance over the conventional OFDM system with a maximum output SNR gain of up to 5.25 dB. It is also shown that the performance of the OPP-MC-CDMA technique improves significantly with increasing the constellation size of the OPP codes.

Impulsive noise (IN) over power-lines can significantly corrupt communication signals. To diminish its effect, a nonlinear preprocessor is usually applied at the receiver's frond-end to blank or clip the incoming signal when it exceeds a certain threshold. Applying a combination of blanking and clipping in a hybrid fashion is characterized by two thresholds T1and T2(T2= αT1), where α is a scaling factor. Previous studies assumed a fixed value for the scaling factor and found that optimizing the threshold T1is the key to improve performance. In contrast to the existing work, in this paper we show that the performance of the hybrid technique is sensitive not only to the threshold but also to the scaling factor, and in light of this we propose to enhance the capability of this technique by optimizing the two parameters. System Performance is evaluated mathematically in terms of the probability of missed blanking/clipping (Pm), probability of IN identification (Pi) and the symbol error rate (SER) performance. In all our investigations, simulation results are provided to validate the analysis. Results reveal that the proposed scheme is superior in terms of minimizing Pmand maximizing Piwhich consequently results in improving SER performance.

Massive MIMO is a promising technique to provide unprecedented spectral efficiency. However, it has been well recognized that huge training overhead for obtaining channel side information (CSI) is a major handicap in frequency-division duplexing (FDD) massive MIMO. Several attempts have been made to reduce this training overhead by exploiting sparse structures of massive MIMO channels. So far, however, there has been little discussion about how to utilize partial support information of sparse channels to achieve further overhead reduction. This support information, which is a set of indexes of significant elements of a channel vector, actually can be acquired in advance. In this paper, we examine the required training overhead when partial support information is applied within a weighted ℓ1minimization framework and analytically show that a sharp estimate of this overhead size can be successfully obtained. Furthermore, we demonstrate that the accuracy of partial support information plays an important role in determining how much reduction can be achieved. Numerical results shall verify the main conclusions.

We provide new results on the signal-to-interference-plus-noise ratio (SINR) statistics considering a Poisson point process (PPP)-based heterogeneous interference field. In particular, closed-form expressions for the density functions of the reciprocal of the aggregate interference and signal-to-interference ratio (SIR) are developed. We prove that the effect of PPP-based interference on useful transmission is mathematically equivalent to the severe impact from a one-sided Gaussian fading channel. As an application example, the proposed approach is used to design and analyze the average SINR performance of a typical user in heterogeneous cellular networks (HetNets).

Heterogeneous network (HetNet) deployment is considered a de facto solution for meeting the ever increasing mobile traffic demand. However, excessive power usage in such networks is a critical issue, particularly for the mobile operators. Characterizing the fundamental energy efficiency (EE) performance of HetNets is therefore important for the design of green wireless systems. In this paper, we address the EE optimization problem for downlink two-tier HetNets comprised of a single macro-cell and multiple pico-cells. Considering a heterogeneous real-time and non-real-time traffic, transmit beamforming design and power allocation policies are jointly considered in order to optimize the system energy efficiency. The EE resource allocation problem under consideration is a mixed combinatorial and non-convex optimization problem, which is extremely difficult to solve. In order to reduce the computational complexity, we decompose the original problem with multiple inequality constraints into multiple optimization problems with single inequality constraint. For the latter problem, a two-layer resource allocation algorithm is proposed based on the quasiconcavity property of EE. Simulation results confirm the theoretical findings and demonstrate that the proposed resource allocation algorithm can efficiently approach the optimal EE.

This paper proposes a solution for interference management in cellular networks. We focus on studying the guaranteed and average data rate performance of cellular networks by using a multi- level interference mapping technique. A novel method is proposed in which an interference intensity map, which indicates the level of interference between conflicting Base Stations (BSs) and users is constructed, based on the interference bounds of users. In addition, a power control algorithm is developed to maximize the reuse efficiency of the entire system based on the interference intensity map. For validation purposes, the performance of the proposed scheme is evaluated and compared with state-of-art techniques. The simulation results show that the proposed scheme can provide an excellent overall performance in comparison with the other techniques.

Switching off base stations is a popular approach to improving the energy efficiency a network. The challenge is how to determine which and how many base stations to switch off given a network configuration while ensuring that the network coverage is not compromised. Different algorithms have been formulated to solve this challenge ranging from load-aware algorithms to random selection. Results show that load-aware algorithms have better performance. Most algorithms assume universal frequency reuse by all base stations even in the case of heterogeneous networks. In this paper we assume an indoor, femtocell network where subcarrier allocation is based on an existing subcarrier allocation technique which ensures maximum reuse. A load-aware base station switch-off algorithm is developed that uses the allocation matrix when all base stations are active and an estimate of required subcarriers by each base station to determine which base stations to switch off. It will be shown that even without any power control, the proposed technique can result in significant energy savings for lower femtocell densities.

Interference Alignment is an effective technique to reduce interference in a wireless system. This paper proposes an alignment based interference cancellation scheme for a multi-cell network with multiple-input multiple-output users under Gaussian Interference Broadcast Channel scenario. We focus the description on a three cell network scenario and design transmit beamforming matrix using a non-iterative closed-form approach. This approach utilizes the possibility to split up the role of the transmit beamforming matrix according to the type of interference caused by a base station. Simulation results confirm the theoretical findings and demonstrate that the proposed scheme can achieve the (L-1) degrees of freedom for each user.

Femtocell technology is widely known for its ability to improve cellular services while reducing the capital and operation expenditure of cellular providers. However, this can lead to more interference and accessibility issues. There are three types of femtocell access schemes currently, which are open, closed and hybrid access. While open access improves the overall network performance, closed access is a much more preferred by the end-user since it guarantees access to the femtocell owner. For this reason, hybrid access is a compromise which releases the femtocell access to the visitor when there is surplus resource left by the owner. This paper proposes a comprehensive method to solve the femtocell access issue by designing a joint multilevel priority scheduling and femtocell access policy based on a Matrix of Conflict RRM. It will be shown through computer simulation that the proposed scheduling and access policy provide network flexibility, for the femtocell owner and cellular provider, which can be utilized to achieve more benefits for both.

In this paper we investigate the application of multi-carrier code division multiple access (MC- CDMA) in impulsive noise power-line channels. In order to improve system performance, impulsive noise blanking is utilized at the receiver's front-end. For comparison-sake, three families of spreading codes are considered here, namely, pseudonoise (PN), Walsh-Hadamard (WH) and poly- phase (PP) sequences. Probability of blanking error P_b and output signal-to-noise ratio (SNR) performances are adopted to characterize the achievable gains. The results reveal that the proposed scheme is able to achieve considerable improvements in terms of P_b and output SNR performance. It is also shown that PP-based MC- CDMA yields the best overall performance with a 1.2 dB SNR gain relative to blanking-based orthogonal frequency division multiple access systems.

Secret key establishment is considered to be one of the main challenging issues in cryptography. Many security algorithms are implemented in practice using complicated mathematical methods to exchange secret keys, but those methods are not desirable in power limited terminals such as cellular and sensor networks. In this paper, we propose a physical layer method for exchanging secret key bits in precoding based multi-input multi-output (MIMO) orthogonal frequency division multiplexing (OFDM) systems. The proposed method uniquely relates the key bits to the indices of the precoding matrix used for MIMO channel precoding. The basic idea of the technique is to utilize a MIMO-OFDM precoding codebook. Comparative analysis with respect to the average number of mismatch bits, named key error rate (KER), shows an interesting lead for the new method relative to existing work. In addition, it will be shown that the proposed technique requires lower computation per byte per secret key.

Spectral efficiency (SE) and energy efficiency (EE) are the main performance metrics for designing green radio (GR) networks; however they are conflicting criteria. Consequently, instead of separately focusing on either SE or EE, characterizing the fundamental trade-off between EE and SE of MIMO broadcast channels (BC) is significant for the development of green wireless communications. This paper investigates the fundamental EE-SE relationship in a multiple-input multiple-output (MIMO) broadcast channel, which is important for facilitating a desirable balance between energy savings and spectrum utilization. Through our investigation, we prove that EE-SE relationship for MIMO-BC is a quasiconcave function. Furthermore, EE is proved to be either strictly decreasing with SE or first strictly increasing and then strictly decreasing with SE. Based on these findings, we propose a two-layer resource allocation algorithm in order to tackle the comprehensive EE-SE trade-offs problem. The key of the proposed method lies in the inner-layer algorithm which is solved by applying the principle of multiple access channel - broadcast channel (MAC-BC) duality. The algorithm in its dual form is solved using sub-gradient method and bisection searching scheme. Simulation results confirm the theoretical findings and demonstrate that the proposed resource allocation algorithm can efficiently approach the optimal EE-SE trade-off for MIMO-BC.

We present a new unified model for the design and analysis of load-aware downlink heterogeneous networks (HetNets) where interferers are inherently spatially-correlated. A closed-form expression for the aggregate network interference statistics generated by correlated load-proportional tiers of base stations (BSs) over Nakagami-m fading interfering channels is developed. This approach allows for relaxation of several major limitations in the existing state-of-the-art models, in particular the always-on-BSs, uncorrelated interferers, and Rayleigh fading with no shadowing assumptions. The validity and advantages of the proposed load-aware framework over the heavily-adopted fully-loaded model and the more recent interference-thinning-based approximation are confirmed via extensive Monte-Carlo (MC) simulations. The results reveal several important trends and design guidelines for the practical deployment of HetNets.

Heterogeneous network (HetNet) deployment is considered a de facto solution for meeting the ever increasing mobile traffic demand. However, excessive power usage in such networks is a critical issue, particularly for mobile operators. Characterizing the fundamental energy efficiency (EE) performance of HetNets is therefore important for the design of green wireless systems. In this paper, we address the EE optimization problem for downlink two-tier HetNets comprised of a single macro-cell and multiple pico-cells. Considering a heterogeneous real-time and non-real-time traffic, transmit beamforming design and power allocation policies are jointly considered in order to optimize the system energy efficiency. The EE resource allocation problem under consideration is a mixed combinatorial and non-convex optimization problem, which is extremely difficult to solve. In order to reduce the computational complexity, we decompose the original problem with multiple inequality constraints into multiple optimization problems with single inequality constraint. For the latter problem, a two-layer resource allocation algorithm is proposed based on the quasiconcavity property of EE. Simulation results confirm the theoretical findings and demonstrate that the proposed resource allocation algorithm can efficiently approach the optimal EE.

This paper proposes an alignment based interference cancellation scheme for a multi-cell network with multiple-input multiple-output users under a Gaussian Interference compounded broadcast channel scenario. The basic idea is to split up the role of the transmit beamforming matrix according to the type of interference caused by each base station. It will be shown that, for a network of L base stations, the proposed method would result in achieving (L - 1) degrees of freedom per user and convert the multi-cell multi-user MIMO channel into a set of single-cell single-user MIMO channels. Finally, we derive the relationship between all the relevant network elements as Nt= (L - ds+ 1)K'Nr+ 1, where Ntand Nrare the numbers of transmit and receive antennas, respectively, L and dsdenote the number of cells and the number of data streams transmitted from each base station, and K' is the number of users per cell defined under the proposed system model. Hence, we show that the proposed scheme makes it possible to implement interference alignment using less antenna resources.

Characterizing the fundamental energy efficiency (EE) performance of multiple-input–multiple-output interfering broadcast channels (MIMO-IFBC) is important for the design of green wireless system. In this paper, we propose a new network architecture proposition based on EE maximization for Multi-Cell MIMO-IFBC within the context of interference alignment (IA). Particularly, EE is maximized subject to maximum power and minimum throughput constraints. We propose two schemes to optimize EE for different signal-to-noise ratio (SNR) regions. For high-SNR operating regions, we employ a grouping-based IA scheme to jointly cancel intra- and inter-cell interferences and thus transform the MIMO-IFBC to a single-cell MIMO scenario. A gradient-based power adaptation scheme is proposed based on water-filling power adaptation and singular value decomposition to maximize EE for each cell. For moderate SNR cases, we propose an approach using dirty paper coding (DPC) with the principle of multiple access channel and broadcast channel duality to perform IA while maximizing EE in each cell. The algorithm in its dual form is solved using a subgradient method and a bisection searching scheme. Simulation results demonstrate the superior performance of the proposed schemes over several existing approaches. It also shows that interference-nulling-based IA approaches outperform hybrid DPC-IA approach in high-SNR region, and the opposite occurs in low-SNR region.

We derive new results for the higher order moments of signal-to-interference-plus-noise ratio (SINR) in the presence of an arbitrary Poisson point process (PPP)-based heterogeneous interference field. The analysis leverages on a moment-generating-function (MGF) methodology, which only requires the statistics of intended signal and aggregate interference, thus eliminating the need for the exact distribution of SINR. We extend the existing results on interference statistics by deriving a generalized closed-form expression of the interference MGF considering Nakagami-m fading channels with exclusion region. In certain special cases, explicit expressions for the averages of different functions of SINR are found, which also lead to closed-form solutions for the probability distributions of aggregate interference reciprocal and signal-to-interference ratio. We prove that in such cases the effect of total PPP-based interference power on useful transmission is mathematically equivalent to the severe fluctuations from a one-sided Gaussian fading channel. As an application example, the proposed methodology is used together with stochastic geometry theory to characterize the average SINR and rate in heterogeneous cellular networks. The validity of our analytical derivations is confirmed via Monte Carlo simulations for various system settings. We show that with cellular network densification there exists a tradeoff between the average SINR and rate performance.

In this paper, the problem of multi-relay selection in one-to-many cooperative wireless networks is studied via a political coalition formation game approach. Specifically, each relay node is endowed with some coalitional strength, and the selected coalition consists of a subset of the available relays in the network that is powerful enough to win against any other potential coalition. In addition, the formed “ruling” coalition must be self-enforcing (and hence stable) such that none of its members would split and become the new ruling coalition. A distributed ruling coalition formation algorithm is proposed that selects such stable set of relays with a marginal compromise on network sum-rate performance. Moreover, our proposed algorithm offers a network sum-rate performance/stability tradeoff through formation of political parties of relays, which also reduces complexity and communication overheads. The proposed algorithm is compared with centralized multi-relay selection, as well as other multi-relay selection algorithms from the literature, and is shown to provide comparable network sum rate with the added advantage of network stability.

Power-line communication (PLC) is considered as the backbone of smart grid. Impulsive noise (IN) over such channels, however, remains the main factor responsible for degrading communication signals. A simple method to mitigate IN over PLC channels is to precede the receiver with a nonlinear preprocessor to blank and/or clip the incoming signal when it exceeds a certain threshold. Applying a combination of blanking and clipping in a hybrid fashion was shown to provide the best performance. The hybrid scheme is characterized by two thresholds T1and T2(T1= α.T2), where a is a scaling factor. Previous studies assume a fixed value for the scaling factor and found that optimizing the threshold T2is the key to enhance performance. In this paper, we show that the performance of this scheme is sensitive not only to the threshold, but also to the scaling factor. With this in mind, a mathematical expression for the output signal-to-noise ratio as a function of the threshold and scaling factor is formulated and used to optimize the hybrid scheme performance. Simulation results are also provided to validate our analysis. The results reveal that using an adaptive hybrid scheme with an optimally selected threshold and scaling factor always outperforms other nonlinear schemes.

Characterizing the fundamental metric of energy efficiency (EE) of multiple-input multiple-output interfering broadcast channels (MIMO-IFBC) is important for the development of green wireless communications. In this paper, we address the EE optimization problem for multi-cell MIMO-IFBC within the context of interference alignment (IA). We employ grouping-based IA scheme to cancel both inter-cell interference (ICI) and inter-user inference (IUI), and thus transform the MIMO-IFBC to a single cell single user MIMO scenario. A gradient-based optimal power adaptation scheme is proposed which utilizes water-filling approach and singular value decomposition (SVD) to maximize EE for each cell. Simulation results confirm the theoretical findings and demonstrate that the proposed resource allocation algorithm can efficiently approach the optimal EE.

The problem of spectrum sensing for cognitive radio networks has attracted much interest in the research community. The Multitaper detector has its unique importance and was highly recommended for spectrum sensing in cognitive radio systems. In this paper, we investigate the Multitaper detector for the generalized nonzero-mean case. We analyze the Hermitian form of the Multitaper estimate to obtain the detector performance for nonzero-mean primary signals. The difficulty in this case arises from finding an expression for the noncentrality parameters associated with the diagonalized form of the quadratic representation of the Multitaper estimate. We provide closed form expressions for the noncentrality parameters, which also turned to be a function of the eigenvalues of the quadratic form. The validity of the derived mathematical model is verified through Monte-Carlo simulations.

This paper proposes and analyses a new cooperative diversity technique that combines users pairing and interference exploitation for enhancing the performance of asynchronous uplink transmission in OFDMA based systems. As well as achieving a diversity order of two, the proposed technique attains further performance enhancements by exploiting co-channel interference. The impact of the proposed technique on various asynchronous conditions is considered in this paper and the performance is assessed through simulation and mathematical analysis. Combined with an effective interference cancellation technique, it will be shown that the results from both models closely match and demonstrate that a significant performance enhancement is obtained relative to other schemes for OFDMA uplink transmission.

This paper proposes a new pairing cooperative technique to achieve spatial diversity and constructive interference exploitation in uplink orthogonal frequency-division multiple access (OFDMA) systems. The underlying principle is to pair users such that their symbols are combined into a single constellation, according to a predefined rule, so that the same symbol is transmitted by each pair of users so their signals can be coherently summed at the receiver, hence maximizing the received signal power. To achieve such constructive combination of both signal copies, single-dimensional OFDMA is utilized in the inphase and quadrature dimensions. It will be shown that such transmission method not only maximizes the received power but also greatly reduces sensitivity to timing misalignment between the cooperating users. Both time synchronous and asynchronous transmission scenarios will be considered. In the asynchronous case, interference reduction will be applied at the base station to reinstate the pairs' orthogonality and hence minimize co-channel interference. The performance of this technique is evaluated through simulations and mathematical analysis. It will be shown that the results from both models closely match and that the proposed technique provides significant bit-error-rate reductions, particularly at low signal-to-noise ratio, and throughput improvements relative to existing cooperative transmission techniques.

We develop a unified framework for the performance analysis of arbitrary-loaded downlink heterogeneous networks (HetNets) in which interfering sources are inherently spatially-correlated. Considering a randomly-deployed multi-tier cellular network comprised of a diverse set of large-and small-cells, we incorporate the notion of load-awareness and spatial-correlations in characterizing the activities of base stations (BSs) using binary decision variables. A stochastic geometry-based approach is accordingly employed to systematically develop a bounded expression of ergodic rate with different cellular association and load-balancing strategies. Employing the proposed unified framework hence allows for relaxation of several major limitations in the existing state-of-the-art models, in particular the always-transmitting-BSs, uncorrelated interferers, and Rayleigh fading assumptions. We elaborate on the usefulness of adopting this methodology by providing detailed analysis of the aggregate network interference generated by interdependent load-proportional sources over Nakagami-m fading interfering channels. The analytical formulations are validated through Monte-Carlo (MC) simulations for various scenarios and system settings of interest. We observe that the heavily-adopted fully-loaded model as well as the more recent interference-thinning-based approximations are significantly limited in capturing the actual performance curve. The proposed bounded load-aware model and MC trials reveal several important trends and design guidelines for the practical deployment of HetNets.

A new radio resource management (RRM) technique for improving the downlink performance in soft-frequency-reuse based long term evolution (LTE) networks is presented. In this RRM the resource is dynamically allocated in distributed and centralized manners such that spectral efficiency is maximized across the whole network. To achieve this a unique interference mapping strategy is implemented to assist in deciding whether a distributed or centralized mode is applicable per basestation. When a distributed approach is granted to a basestation it can use the entire spectrum while when a centralized approach is imposed on a basestation it will only be allocated a subset of the spectrum. The proposed then utilizes the confederation concept in the sense that once the allocation approach is determined the individual basestations can take control of their allocated resource. When combined with proportional fairness scheduling, this RRM can also benefit from multiuser diversity. It will be shown through mathematical analysis and computer simulations that this technique offers significant improvements in terms of sum rate and quality of service by increasing the guaranteed data rate per user.

Cognitive radio opportunistically accesses the spectrum while the licensed user is idle. A spectrum sensing procedure to monitor primary users' existence is therefore vital to cognitive radios. In this paper, we investigate the energy detection based sequential cooperative spectrum sensing technique in time varying channels. By utilizing past local observations from previous sensing slots, cognitive radio nodes can aggregate the current and previously received energy values to improve the detection performance. We propose the weighted sequential energy detector (SED) in which a fixed number of past observations are taken for decision making. In addition, we propose two adaptive schemes, namely the Two-Stage SED and the Differential SED, where a cognitive radio user uses previously received energy values until it detects a change in primary user's activity. The probability of false alarm and detection for the Weighted SED and Two-Stage SED schemes are derived. The results show that the proposed schemes achieve better detection performance over the conventional cooperative energy detection technique. In particular, the Two-Stage SED and Differential SED schemes can satisfy the IEEE 802.22 standard's requirement of 10% false alarm and 90% detection in scenarios that conventional techniques cannot accommodate.

Spectral efficiency (SE) and energy efficiency (EE) are the main metrics for designing wireless networks. Rather than focusing on either SE or EE separately, recent works have focused on the relationship between EE and SE and provided good insight into the joint EE-SE tradeoff. However, such works have assumed that the bandwidth was fully occupied regardless of the transmission requirements and therefore are only valid for this type of scenario. In this paper, we propose a new paradigm for EE-SE tradeoff, namely the resource efficiency (RE) for orthogonal frequency division multiple access (OFDMA) cellular network in which we take into consideration different transmission-bandwidth requirements. We analyse the properties of the proposed RE and prove that it is capable of exploiting the tradeoff between EE and SE by balancing consumption power and occupied bandwidth; hence simultaneously optimizing both EE and SE. We then formulate the generalized RE optimization problem with guaranteed quality of service (QoS) and provide a gradient based optimal power adaptation scheme to solve it. We also provide an upper bound near optimal method to jointly solve the optimization problem. Furthermore, a low-complexity suboptimal algorithm based on a uniform power allocation scheme is proposed to reduce the complexity. Numerical results confirm the analytical findings and demonstrate the effectiveness of the proposed resource allocation schemes for efficient resource usage.

Cognitive Radio (CR) aims to access the spectrum opportunistically mainly by two access strategies, overlay and underlay. Overlay can utilize the spectrum whenever the primary system is off. On the other hand, underlay can utilize the spectrum at any time with considering the interference limit of the primary system. However, by using hybrid methods and performing proper equalization technique, spectrum can be utilized more efficiently. In this paper, we propose a hybrid MC-CDMA system which utilizes the whole spectrum for underlay transmission rather than solely the occupied parts. Due to the interference rejection capability, MC-CDMA can minimize the interference from the Primary User (PU) and exploit more diversity. Furthermore, overlay utilizes the spectrum holes while maintaining orthogonality to the underlay by Orthogonal Variable Spreading Factor (OVSF) codes. Chip and symbol- level MMSE-based modified equalizers are proposed for the system and the underlay performance of the system is evaluated. Simulation results show that BER performance improves significantly with the modified MMSE equalizers and for all PU occupancy levels.

This paper proposes a new resource management algorithm that utilizes the self-organizing network functionality for optimising spectrum usage and minimising cross-tier interference between macrocell and femtocells and co-tier interference between femtocells. To achieve this, the proposed algorithm dynamically maximizes usage of all the available subcarriers by exploiting knowledge of the interference power at each user. Taking into account the associated overhead and power consumption it will be shown that the proposed algorithm improves the average data rate per user as well as the energy efficiency of femtocells networks in all femtocell density scenarios, and, is also superior to existing techniques. The fact that the proposed RRM minimizes the energy efficiency and maximizes the average data rate makes it an ideal contender for adoption in future green heterogeneous wireless networks.

A very efficient method to mitigate impulsive noise (IN) over powerline channels is to precede the OFDM demodulator with a blanker to zero the incoming signal when it exceeds a certain threshold. Blanking the signal samples unaffected by IN exceeding this threshold, i.e. blanking errors, can cause severe performance degradation. For best performance, the optimal blanking threshold must be determined and this requires some prior and accurate knowledge about the characteristics of IN; this method is referred to as the unmodified method. In this paper, we propose an algorithm to enhance the capability of such methods by processing the OFDM signal at the transmitter to make the IN more easily identifiable at the receiver. This is done by simply deploying a peak to average power ratio (PAPR) reduction technique such as the selective mapping (SLM) scheme. A closed-form analytical expression for the probability of blanking error is derived and the problem of blanking threshold optimization is addressed under various IN environments. The results reveal that the proposed technique is able to minimize the probability of blanking error dramatically and can provide significant SNR improvement relative to the unmodified scheme. It will also be shown that when SLM is implemented with a large number of phase sequences, not only a considerable SNR enhancement is achieved but also, unlike the unmodified method, it becomes feasible to completely alleviate the need for any previous knowledge about the IN characteristics for optimal blanking.

Cognitive radio can improve the spectrum utilization by allowing cognitive users (CUs) to access the licensed bands. To coexist without causing harmful interference, cognitive users have to detect the presence of primary users in the vicinity. Cyclostationary feature detection (CFD) is proposed for performing this task due to its reliability and robustness. Given multiple branches of observations either from multiple receiving antennas or from cooperative CUs, pre-combining or post-combining techniques can be applied to fusing these data. In this paper, the analytical performance of post-combining based CFD subject to independent and identically distributed Rayleigh fading is investigated. We derive approximated detection probabilities in a series form for post addition combining and post selection combining. Numerical results demonstrate that the theoretical detection performance can be well approximated by our proposed in the low average signal-to-noise ratio region which is critical for cognitive radio applications.

This paper addresses the problem of spectrum sensing from a frequency domain approach using periodogram-based energy detection which naturally yields a lower probability of false alarm when compared with the time-domain detector. In this paper, the periodogram-based detector is optimized based on the likelihood ratio test and accurate expressions are derived for the probability of false alarm and the probability of detection. In addition, the case of sensing with multiple antennas is considered assuming that equal gain combining (EGC) is used, which yields a hypoexponential decision statistic. The high accuracy of the obtained models is verified by the obtained simulation results. The performance is enhanced by employing the optimized models. The receiver operator characteristics clearly show that better operation points are obtained as the SNR is increased.

This paper proposes an adaptive radio resource management (RRM) algorithm based on self-organizing network (SON) and distance vector routing protocol (DVRP) strategy for power consumption reduction and quality of service (QoS) improvement in long term evolution (LTE) network. Using SON principle, the base stations downlink transmissions can be effectively organized to maximise interference avoidance. Combining with DVRP routing strategy for enhance resource allocation, it will be shown that the proposed strategy is capable to adaptively adjust the power consumption of the BS and support the increasing demand on QoS per user in LTE cellular network.

This paper proposes and analyzes a new cooperative diversity technique that combines users pairing and interference exploitation for enhancing the uplink transmission performance in uplink OFDMA systems suitable for 4G technology. The underlying principle is to pair users on the basis of best interuser channel by utilizing low transmit power communication in the unlicensed band to exchange data symbols. Then, each pair remap their combined symbols according to a predefined rule such that they transmit the same constellation using single dimensional OFDMA to ensure that the signals of each pair combine constructively at the destination. As well as achieving a diversity order of two, the proposed technique attains further performance enhancements by exploiting co-channel interference. The impact of the proposed technique on various modulation orders is considered in this paper. The performance is assessed through Monte Carlo simulation and accurate mathematical analysis. It will be shown that the results from both models closely match and demonstrate that significant BER reduction as well as throughput enhancement are obtained relative to other uplink OFDMA transmission techniques.

Many IN mitigation techniques have been proposed to mitigate impulsive noise (IN) over powerlines, the most common of which is the blanking technique. The conventional way to implement this technique however requires prior knowledge about the IN characteristics to identify the optimal blanking threshold (OBT). When such knowledge cannot be obtained the performance deteriorates rapidly. To alleviate this, a look-up table (LUT) based algorithm with uniform quantization is deployed to utilize estimates of the peak to average power ratio at the receiver to determine the OBT. In this paper, we investigate the impact of quantization bits on the system performance as well as the performance loss due to the impact of IN on the side information. Two aspects of the achievable performance are considered namely, output signal-to-noise ratio (SNR) and symbol error rate under various IN scenarios. The results reveal that a 5 bit LUT is sufficient to achieve a gain of up to 3dB SNR improvement relative to the conventional blanking method. Furthermore, it will be shown that the loss due to the practical impact of IN on the side information is insignificant.

Powerline communication technology is a promising communication platform for smart grid and has nowadays become an attractive alternative for data transmission in the home. Impulsive noise (IN) over such channels, however, remains the main factor responsible for degrading communication signals. Many techniques for mitigating IN have been reported in the literature the most common of which is preceding the OFDM receiver with blanking, clipping or hybrid (combined blanking-clipping) nonlinear preprocessors. In this paper, we propose to enhance the capability of these techniques by preprocessing the signal at the transmitter. A closed-form analytical expression for the probability of IN detection error is derived and the problem of blanking/clipping threshold selection is also considered. The results reveal that the proposed is able to minimize the probability of IN detection error significantly and can provide up to 3dB SNR improvement relative to the conventional techniques.

Impulsive noise (IN) is the most dominant factor degrading the performance of communication systems over powerlines. Many IN mitigation techniques have been introduced in the literature such as the application of a blanker at the front-end of the receiver which sets the incoming signal to zero when it exceeds a certain threshold. Determining this threshold is the key for achieving best performance in this technique. Most studies dealing with threshold optimization require prior knowledge about the IN characteristics. However, if the peak to average power ratio (PAPR) of the OFDM symbols can be determined at the receiver, this will allow optimal blanking of IN without requiring any knowledge about the noise parameters. In this paper we propose a look-up table (LUT) based algorithm with uniform quantization to estimate the peak of OFDM symbols. We also investigate the impact of quantization bits on the system performance in terms of the signal-to-noise-ratio (SNR) at the output of the blanking device, in two different scenarios, weakly and heavily disturbed IN environments. Simulation results reveal that a 5 bit LUT is sufficient for reliable performance.

This paper proposes a new resource management (RRM) algorithm that utilizes the self-organizing network functionality for optimizing spectrum usage and minimizing co-layer interference between femtocells. To achieve this, the proposed algorithm dynamically maximizes usage of all the available subcarriers by exploiting knowledge of the users' location. Taking into account the associated overhead and power consumption it will be shown that the proposed algorithm improves the average data rate per user as well as reduced the overall system power consumption in all femtocell density scenarios, and, is also superior to existing techniques. The fact that the proposed minimizes power consumption without compromising the data rate makes it an ideal candidate for adoption in future green heterogeneous wireless networks.

Cyclostationary feature detection enables a cognitive radio system to reliably sensing the existence of licensed users. A statistical test based on the second-order cyclostationary features has been widely used. This paper evaluates the detection performance of this 2nd-order feature based technique subject to Nakagami fading. The analytical upper and lower bounds on the detection probability are derived by exploiting some available series expansion and exponential-type bound of the generalized Marcum Q-function. As a result, the preliminary detection performance can be acquired without relying on Monte Carlo simulations.

The principle of cognitive radio (CR) systems is to utilize the licensed spectrum when their interference to primary users (PUs) can be maintained below a certain threshold. Thus, to successfully coexist, cognitive users must have awareness of PUs presence in the vicinity. As most communication signals exhibit statistical periodicities, cyclostationary feature detection (CFD) can be used to perform the task of sensing the spectrum for PUs presence. A second-order statistical approach is most widely used to perform CFD in which a set of lags should be chosen for statistical testing. The optimal method for choosing multiple lags requires knowledge of the 4th-order cyclic cumulant of PUs' signals, which can be a burden in practice. In this letter, we present a new idea for lag set selection with which avoids the mentioned 4th-order cumulant burden. The results, verified via analysis and simulation, show that the performance of the proposed method is comparable to the optimal one in the low signal to-noise ratio region where it is most critical for CR applications.

Knowledge of the channel path-loss between a primary user and a secondary user in underlay cognitive radio systems could be vital for deciding how a secondary user accesses a specific frequency band. The conventional way to acquire this knowledge relies on some collaboration with primary user systems. This letter proposes a novel cooperative technique for estimating the path-loss parameter in cognitive radio interference channels without the need for channel measurements from any primary user. The results reveal that, relative to existing techniques, the proposed offers improved performance.

This paper presents a new technique for jointly optimizing energy consumption and quality of service (QoS) in heterogeneous cellular networks employing fractional frequency reuse (FFR) in the macrocell tier. The proposed technique combines radio resource management (RRM) and network routing principles to produce an effective way of utilizing the spectrum. Based on a novel method of interference mapping, the RRM is invoked, in distributed or centralized manner, to allocate the resource. In the case of centralized RRM, network routing is applied to maximize spectrum utilization. It will be shown through matching mathematical analysis and computer simulations that, relative to existing well known techniques, the proposed technique offers significant QoS improvements, in terms of guaranteed data rate per user, as well as, enhancements in the overall energy efficiency of the network.

Spectrum sensing is a major function within a cognitive radio system, and it is recently shown that the frequency-domain implementation of the energy detector yields a lower probability of false alarm when compared with the timedomain model. In this paper, an accurate mathematical model is presented for spectrum sensing using the periodogram-based energy detector over for independent and identically distributed (i.i.d.) Nakagami fading channels. By exploiting the quadratic form representation of the periodogram, the eigenvalue of the product of the sample covariance matrix of the observed vector and the matrix of the quadratic form is investigated for the case of transmission over Nakagami fading. Hence accurate closed forms are derived for the average probability of missed detection as a function of the sensing threshold and the signal-to-noise ratio (SNR). The results show that the derived equations are accurate and the performance is enhanced with any increase of the eigenvalue or the SNR. However, it is also found that for a given signal and fading parameters, the detector is not affected with any change of the length of observations.

In this paper an accurate analysis is provided for the Multitaper-based detector. We study the quadratic form representation of the Multitaper estimate (MTE), and we derive accurate expressions of the eigenvalues of the diagonalized representation of the quadratic form. It is found that in AWGN all the nonzero eigenvalues are identical, and the number of eigenvalues is identical to the number of the employed Slepian tapers. Using this information, closed forms are obtained for the probability of false alarm and the probability of detection. Furthermore, the case of propagation over fading channels is investigated and the corresponding eigenvalues are derived. The results demonstrate the accuracy of the obtained model. It is found that the performance of the Multitaper estimate is enhanced when the number of employed Slepian tapers is increased. In addition, at a given sensing threshold the conventional time-domain (TD) energy detector outperforms the MTE in terms of the probability of detection. However, the MTE outperforms the TD energy detector in terms of the probability of false alarm.

In this paper a new and accurate performance analysis of the Bartlett method-based spectrum sensor is presented for the application of cognitive radios. To do this, first the attributes of the quadratic form representation of Bartlett power spectrum estimator are studied, and then a closed form for the cumulative distribution function (CDF) is derived and exploited to obtain the probabilities of false alarm and detection. We also investigate the case of joint detection of multiple frequencies where we apply the Neyman-Pearson approach to obtain an optimized detector for both cases of single and multiple frequency sensing. The accuracy of the presented mathematical analysis is verified by Monte-Carlo simulations.

This paper proposes a dynamic symbol adaptation scheme for downlink and point-to-point multiple input multiple output (MIMO) systems aiming at the minimization of the overall system bit error rate. The proposed scheme adaptively changes the order or the values of the symbols to be transmitted within a sub-frame of symbols with the objective to enhance the received symbols' power. The adaptation is based on the instantaneous interference between the symbols taking into account the channel's characteristics as well as the actual symbol values. This procedure is targeted to optimizing, rather than strictly minimizing the interference between the symbols. In this way, constructive instantaneous interference is utilized in enhancing the decision variables at the receiver on a symbol-by-symbol basis, so that detection is made more reliable. The proposed scheme can be used in conjunction with various conventional MIMO precoding and detection techniques. The presented simulations show that it provides significant benefits to the corresponding conventional system's error rate performance.

Spectrum sensing is an essential function for the operation of cognitive radios. This paper, considers the application of periodogram-based energy detection for spectrum sensing and presents a generalized mathematical model which includes the case of a complex non-zero mean primary signal. The model is then used to obtain accurate performance analysis of this technique. By defining and exploiting the noncentral quadratic form of the periodogram, the cumulative distribution function (CDF) is obtained directly through numerical inversion. The presented model is simplified through manipulating the characteristics of the Hermitian matrix of the quadratic form along with the covariance matrix of the received signal. Using this, the non-zero eigenvalue of the corresponding product is obtained and the probabilities of false alarm and missed detection are derived. Furthermore, the performance of detecting multiple frequencies simultaneously is considered by investigating the independence requirements of the corresponding quadratic forms. The presented results are validated with the aid of Monte-Carlo simulations.

In this paper, the problem of spectrum sensing for cognitive radios is investigated when the decision statistic is computed using Welch Overlapped Segmented Averaging (WOSA). A novel analysis is presented using the performance measures which are the probability of false alarm and the probability of detection. First, we present a novel investigation of the hermitian form of Welch's estimate. Using the theory of quadratic forms, we investigate the hermitian matrix of the hermitian form and exploit its characteristics to obtain the eigenvalues of the diagonalized representation of the hermitian form. Second, the obtained results are used to derive mathematical expressions for the probabilities of false alarm and detection over Rayleigh fading. The numerical results have revealed the high accuracy of the obtained mathematical models.

Spectrum sensing is a major function within the cognitive radio system. In this paper, spectrum sensing using energy detection is considered and an accurate performance analysis is provided for both cases of single and cooperative sensing. The performance of the periodogram-based energy detector is studied for random signals employing a complex envelope. The contribution of this paper is twofold. New and accurate closed forms are developed for the performance measures which are the probability of false alarm and the probability of miss. The obtained mathematical models are supported by Monte-Carlo simulations. In addition, the obtained derivations are extended to include the performance of centralized cooperative sensing using decision fusion. The considered decision rules are Logical OR (LO), Logical AND (LA) and Majority Rule (MR). The obtained numerical results reveal that the probability of detection tends to increase when using LO and MR. On the other hand, LA yields the same receiver operator characteristic (ROC) curve irrespective of the number of cooperative users.

This paper introduces a technique for joint channel control signal estimation for OFDM systems. The basic idea proposed is to embed the control signal information in the pilot sequence such that when it is estimated at the receiver it can reveal both the channel response and the intended control signal information. We also provide a novel technique, which utilizes the channel''s correlation, for recovering the pilot sequence, and show that we can achieve accurate channel and side information estimation even at relatively low SNR values. Additionally, the impact of various sequence types on the pilot sequence detectability are investigated under different scenarios. It will be demonstrated here that the proposed method can successfully work and used in a number of applications.

A performance-enhanced two-transmit antenna spatial modulation (SM) technique is introduced and analysed. Specifically, this paper modifies the conventional spatial modulation technique by utilising simultaneous transmission from two antennas, couple with the utilisation of short orthogonal codes for antenna identification. A unique symbol to antenna assignment to enable the receiver to distinguish between the different possible constellation points is also presented. To highlight the achieved gains, the paper compares the performances of the proposed technique to those of the conventional SM technique in OFDM systems. The results show that the proposed technique outperforms the conventional one in terms of BER performance. Furthermore we develop analytical analysis for the symbol error ratio (SER) of the proposed technique and show that the analytical and simulation results closely match.

A simultaneous transmission spatial modulation (SM) technique is introduced in this paper. Unlike in conventional SM where only one antenna transmits at a time, the simultaneous spatial modulation (SSM) transmits from two antennas at the same time. The proposed technique utilizes a unique symbol to antenna assignment algorithm at the transmitter and the SM optimum detector at the receiver. The paper compares the performances of the proposed technique to those of the conventional and optimum SM techniques and V-BLAST. The results show that the proposed technique outperforms the conventional one in terms of BER performance under different channel conditions.

A dynamic symbol mapping technique is proposed for downlink and point-to-point multiple input multiple output (MIMO) systems. The proposed mapping introduces a perturbation to the transmitted symbols by adaptively changing the order or the values of the symbols to be transmitted within a sub-frame of symbols with the objective to enhance the received symbols' power. The symbol mapping aims at taking advantage of constructive instantaneous interference, considering the channel's characteristics as well as the actual symbol values. In other words, rather than minimising interference between the symbols, the goal is to optimize the resulting interference so that it is more constructive. In this way the received symbol energy is enhanced and detection is made more reliable. It is shown by the presented results and analysis that it provides significant benefits to the corresponding conventional system's error rate performance.

Multi-user MIMO systems have the potential to combine the high capacity achievable with MIMO processing with the benefits of space-division multiple access. Although recent theoretical results show that the sum capacity grows linearly with the minimum of the number of antennas and users, the sum rate of channel inversion does not due to the large spread in the singular values of the channel matrix. In this paper, we introduce a suitably modified channel inversion technique which randomises the phases of the channel to mitigate the impact of the ill-conditioned channel and obtains near-sum-capacity of the multi-user MIMO systems. The proposed technique not only achieves significant improvement over conventional linear precoding techniques at all signal-to-noise ratios (SNRs) but also outperforms the convolutional precoder at low SNRs.

A novel linear precoding scheme is proposed for the downlink of multiuser multiple input multiple output (MIMO) systems, that offers enhanced data throughput compared to conventional precoding. The proposed technique is based on the fact that part of the instantaneous multiple access interference (MAI) inherent in a multiuser MIMO system adds constructively to the useful signal. It utilises this concept by applying partial linear precoding such that the destructive part is eliminated while the constructive part of MAI is preserved and exploited. By doing so, the effective signal to interference-plus-noise ratio (SINR) delivered to the mobile unit (MU) receivers is enhanced, without the need to invest in additional transmitted signal power at the MIMO base station (BS). The presented analysis and simulations verify that the proposed precoding scheme significantly enhances the data throughput compared to conventional precoding.

An extension to decomposition based transmit beamforming is proposed for multiple input multiple output (MIMO) multiuser systems. In contrast to conventional beamforming which is constrained towards orthogonalizing the subchannels of the different users to yield groups of correlated antennas that belong to only one user, a more flexible orthogonalization approach is proposed which is targeted directly towards the optimization of the decision variables at the multi-antenna receivers of all users. The resulting groups of correlated antennas may consist of elements belonging to multiple users. Thus, the proposed beamforming has more degrees of freedom and therefore attains a more efficient performance optimization. The trade-off to the performance improvement is an increase in the precoding complexity imposed by the adaptive nature of the proposed beamforming. A suboptimal adaptive-decomposition beamforming scheme is therefore also proposed with a reduced complexity overhead. Comparative simulations of the proposed scheme to conventional beamforming show considerable error rate reductions that justify the increased complexity and verify the superiority of the proposed scheme.

Precoding is introduced as an excellent choice for complementing the MIMO systems. In addition, the non-linear techniques can achieve near optimal capacity at the expense of reasonable levels of complexity. Such techniques show that any known interference at the transmitter can be subtracted at the receiver without the penalty of degrading the radio resources. However, precoding is subject to the knowledge of the channel. On the other hand, recent works in MIMO systems have shown that channel-knowledge at the transmitter, in either full or partial forms can increase the channel capacity and performance considerably. Thus, we present a precoding algorithm able to deal efficiently in fully/partially-known channels with the advantage of keeping low levels of complexity.

This paper proposes a hybrid transmission technique based on code optimization and partial linear precoding for interference exploitation on the downlink of phase shift keying (PSK) based mulitcarrier code division multiple access (MC-CDMA) systems. The first stage of the technique is to dynamically allocate codes to the users so that the combination of instantaneous data and user cross correlations yield a favourable constructive to destructive multiple access interference (MAI) ratio. To further optimize the received signal to interference plus noise ratio (SINR), the second stage is to employ a dynamic, partial transmitter based pre-decorrelation scheme specifically designed for the exploitation of constructive MAI. The decorrelation processing is targeted to the destructive interferers, while users that interfere constructively are let correlated. This results in a significant SINR enhancement without the need for additional power-per-user investment. Mathematical analysis and simulations show that significant bit error rate (BER) performance benefits can be achieved with this technique.

In this paper a novel channel inversion (CI) precoding scheme is introduced for the downlink of multiple input multiple output (MIMO) systems. The proposed technique outperforms conventional CI by exploiting some of the consequential inter- channel interference (ICI). It achieves this by applying partial channel inversion such that the constructive part of ICI is preserved and exploited while the destructive part is eliminated by means of CI precoding. By doing so, the effective signal to interference-plus-noise ratio (SINR) delivered to the mobile unit (MU) receivers is enhanced, without the need to invest in additional transmitted signal power at the MIMO base station (BS). The trade-off to this achievement is a minor increase in the complexity of the BS processing. The presented theoretical analysis and simulations show that due to the SINR enhancement, significant performance gains are offered by the proposed MIMO precoding technique compared to its conventional counterpart.

This paper introduces and analyses a novel uplink CDMA pairing diversity technique. In particular, this paper considers the use of orthogonal polyphase (OPP) sequences on the synchronous and asynchronous uplink to benefit from the codes' good cross-correlation properties. A code allocation algorithm is also presented in this paper that aims to exploit the cross-correlation properties to achieve the best possible system performance. For the sake of comprehensiveness, the paper compares the performance of this new diversity technique with a conventional pairing diversity technique and with the well known maximum gain combined (MGC) time diversity. The results show that the proposed algorithm outperforms the conventional pairing technique, in terms of BER, and with proper code allocation, is also able to outperform time diversity systems. The new algorithm is able to accommodate up to 200% system loading even under severe asynchronous and multipath conditions.

A novel antenna selection scheme is introduced in conjunction with a partial linear preceding technique for downlink and point-to-point multiple input multiple output (MIMO) systems. The proposed technique outperforms conventional channel inversion (CI) linear preceding by utilizing part of the existing inter-channel interference (ICI) between the MIMO sub-channels. It applies partial sub-channel orthogonalization in contrast to the full decorrelation of the channels attained by conventional CI. This yields an increased signal to interference-plus-noise ratio (SINR) to the multi-antenna receiver, without investing additional transmitted signal power at the multi-antenna transmitter. This benefits performance and throughput in a variety of transmission scenarios. However, the focus of this paper is on transmit antenna selection where a customized selection criterion is introduced that enhances the residue-interference optimization. Comparative simulations to conventional schemes are presented to illustrate the superiority of the proposed technique.

The power constraint factor in precoding methods plays an important role in the reduction of SER at the receiver. The value of this scaling factor lies in the individual power assigned to the transmit symbols prior the transmission. Such assignment will depend entirely on the matrix condition of the channel, in this case the eigenvalue's power of the channel inverse. Thus, the minimisation of this power constraint will rely on closing the power gap among the transmit symbols, and one solution is to use an auxiliary vector for fixing the matrix condition. This is equivalent to solving the integer least-squares problem. For achieving this specific goal there are two effective choices: the lattice-reduction, whose objective is to reduce the basis of any given matrix, and the sphere techniques which enumerate all the lattice points inside a sphere centered at the query point. Both choices aim for finding or fitting an approximated least-squares solution occasioning astonishing results in performance when minimising the scaling factor prior to transmit.

This paper introduces a novel channel inversion (CI) precoding scheme for the downlink of phase shift keying (PSK)-based multiple input multiple output (MIMO) systems. In contrast to common practice where knowledge of the interference is used to eliminate it, the main idea proposed here is to use this knowledge to glean benefit from the interference. It will be shown that the system performance can be enhanced by exploiting some of the existent inter-channel interference (ICI). This is achieved by applying partial channel inversion such that the constructive part of ICI is preserved and exploited while the destructive part is eliminated by means of CI precoding. By doing so, the effective signal to interference-plus-noise ratio (SINR) delivered to the mobile unit (MU) receivers is enhanced without the need to invest additional transmitted signal power at the MIMO base station (BS). It is shown that the trade-off to this benefit is a minor increase in the complexity of the BS processing. The presented theoretical analysis and simulations demonstrate that due to the SINR enhancement, significant performance and throughput gains are offered by the proposed MIMO precoding technique compared to its conventional counterparts.

This paper proposes a hybrid transmission technique based on adaptive code-to-user allocation and linear precoding for the downlink of phase shift keying (PSK) based multi-carrier code division multiple access (MC-CDMA) systems. The proposed scheme is based on the separation of the instantaneous multiple access interference (MAI) into constructive and destructive components taking into account the dependency on both the channel variation and the instantaneous symbol values of the active users. The first stage of the proposed technique is to adaptively distribute the available spreading sequences to the users on a symbol-by-symbol basis in the form of codehopping with the objective to steer the users' instantaneous crosscorrelations to yield a favourable constructive to destructive MAI ratio. The second stage is to employ a partial transmitter based zero forcing (ZF) scheme specifically designed for the exploitation of constructive MAI. The partial ZF processing decorrelates destructive interferers, while users that interfere constructively remain correlated. This results in a signal to interference-plus-noise ratio (SINR) enhancement without the need for additional power-per-user investment. It will be shown in the results section that significant bit error rate (BER) performance benefits can be achieved with this technique.

A novel code optimization scheme is presented for the downlink of multicarrier code division multiple access (MC-CDMA) systems employing phase shift keying (PSK) modulation. The optimization is based on dynamically re-allocating the available signature waveforms amongst the users on a symbol-by-symbol basis in order to manipulate and utilize interference amongst them. By applying the appropriate allocation criteria destructive interference between users is minimized while constructive is maximized. As a result, employing this on top of conventional schemes enhances the received signal to interference-plus-noise ratio (SINR) without additional transmitted power-per-user investment. The trade-off to the resulting performance improvement is the need for transmission of some extra side information, which by using the proposed processing is kept to a minimum. While performance benefits can be expected for various scenarios, the focus of this paper is on MC-CDMA precoding schemes. Analysis and simulations show a considerable bit error rate (BER) reduction for the case of decorrelating precoding methods.

Finding the least-squares solution to a system of linear equations where the unknown vector is comprised of integers, but the matrix coefficient and given vector are comprised of real or complex numbers is a problem equivalent to finding the closest lattice-point to a given point and is well known that the search is hard. However, in communications applications the given vector is not arbitrary but rather is an unknown lattice-point that has been perturbed by an additive offset vector whose statistical properties are known, making it relatively easier to decode. In this paper we will discuss the vector- perturbation technique proposed for solving this problem and analyse a possible solution for overcome the complexity issues.

High peak to average power ratio (PAPR) is a serious drawback for orthogonal frequency division multiplexing (OFDM) system as it reduces the efficiency of high-power amplifiers commonly used in the transmitter and causes spectral spillage. OFDM transmissions are also sensitive to frequency selective fading channels which can severely attenuate certain parts of the signal making it much more vulnerable to additive noise. This paper proposes an effective precoding technique with the dual ability to both reduce PAPR and condition the OFDM signal against frequency selective fading channels. It will be demonstrated that by advisedly creating diversity among the subcarriers of one OFDM symbol, and exploiting it with a dirty- paper-coding (DPC) approach, excellent bit-error-rate (BER) performance is achieved without reducing transmission rate. Low PAPR factor can also be obtained through a proper selection of diversity matrix that distributes the power of each modulated symbol over the OFDM block. Simulation results show that the proposed technique has not only better BER performance than the ordinary channel inversion but also similar PAPR reduction ability to the selective mapping (SLM) technique.

In this paper a new dynamic code distribution technique is presented. This method chooses the optimal code-to-user allocation for transmission between different combinations of the available signature waveforms according to the data to be transmitted at every symbol period by the base station (BS) at the downlink of a cellular code division multiple access (CDMA) system. The selection is done with the aim to minimise the destructive and maximize constructive interference between users. This effectively spreads the signal constellation and enhances the signal to interference-plus-noise ratio (SINR) at the receiver with no additional power-per-user investment. However, the trade-off to this is some extra side information. Theoretical analysis and simulations presented suggest that this method can provide a bit error rate reduction of an order of a magnitude when combined with multiuser detection.

Amongst the advantages of Multicarrier on-off keying (MOOK) is the simplicity of its transmitter-receiver pair and inherent good performance in noisy channels which make it a popular choice for some communication systems. However the MOOK technique is widely considered as bandwidth inefficient relative to other existing transmission schemes. The aim of this paper is to investigate methods for improving the spectral efficiency of this technique. Two strategies are proposed and analysed here. The methods investigated show that significant bandwidth efficiency enhancement can be achieved especially when the number of subcarriers is large.

Although non-coherent multicarrier on-off keying (MOOK) is a relatively bandwidth inefficient technique, the simplicity of its transmitter-receiver pair and inherent coding ability make it a popular choice for a number of communication systems. This technique however is particularly susceptible to frequency selective fading channels which are often encountered in the wireless environment. The purpose of this paper is to investigate and analyze bandwidth efficient diversity exploitation techniques with the objective to enhance the performance and data throughput of MOOK transmissions. We first analyze the impact of using spatial diversity and then a novel spatial-amplitude diversity (SAD) scheme is introduced for MOOK systems. The simulation results provided show that the proposed technique can provide significant performance improvement in frequency selective fading channels and at no extra bandwidth degradation.

Selective mapping (SLM) is one of the most effective peak-to-average power ratio (PAPR) reduction techniques proposed for orthogonal frequency-division multiplexing systems. However, the fact that this technique requires the transmission of side information (SI), to enable the receiver to reverse the randomisation process before performing signal demodulation, can make it undesirable for certain applications as it degrades the system's bandwidth efficiency and, more significantly, the bit error rate (BER) performance. A modified SLM technique (MSLM) that can operate without the need for any dedicated SI for both channel-coded and uncoded scenarios while providing similar PAPR reduction performance as the ordinary SLM technique is proposed. It will be demonstrated that the proposed MSLM technique not only improves the system's bandwidth efficiency, but also achieves significantly better BER performance than the ordinary SLM technique.

The inherent high peak-to-average power ratio (PAPR) of multicarrier transmission, such as orthogonal frequency-division multiplexing (OFDM) or discrete multi-tone (DMT), can lead to a significant degradation in the transmission power efficiency which is unacceptable especially in battery-powered terminals. Among the most popular PAPR reduction techniques proposed in the literature is the selective mapping (SLM) technique which has been shown to offer PAPR reductions of several decibels. However, the SLM technique requires invoking the inverse fast fourier transform (IFFT) process several times per transmitted OFDM block which increases the system's complexity and hence may result in long latencies and high power consumption. The authors propose a new low complexity post-IFFT PAPR reduction technique that can outperform the SLM technique in terms of PAPR reduction while its operational complexity is orders of magnitude less than that of SLM technique.

A novel transmitter code optimisation technique based on adaptive code-to-user allocation is presented for interference exploitation on the time division duplex downlink of binary phase shift keying-based multiple carrier code division multiple access systems. The principle of the proposed technique is to exploit the dependency of multiple access interference on the instantaneous symbol values of the active users. The objective is to adaptively allocate the available spreading sequences to users on a symbol-by-symbol basis to enhance the ratio between constructive and destructive interference and thus optimise the decision variables at the downlink receivers. The resulting signal-to-interference plus noise improvement happens by making use of the energy inherent in the system so the performance benefit is attained with no additional power-per-user investment. It will be shown that when this optimisation technique is incorporated with common pre- and post-equalisation schemes, a significant bit error rate performance improvement is achieved while the associated adaptation overhead is kept less than 6% of the available bandwidth.

A new technique based on adaptive code-to-user allocation for interference management on the downlink of BPSK based TDD DS-CDMA systems is presented. The principle of the proposed technique is to exploit the dependency of multiple access interference on the instantaneous symbol values of the active users. The objective is to adaptively allocate the available spreading sequences to users on a symbol-by-symbol basis to optimize the decision variables at the downlink receivers. The presented simulations show an overall system BER performance improvement of more than an order of a magnitude with the proposed technique while the adaptation overhead is kept less than 10% of the available bandwidth.

A novel scheme is presented that enhances the near-far resistance of conventional transmitter precoding for CDMA with unequal power distribution. The proposed technique applies a partial pre-decorrelation to the users in contrast to the full orthogonalisation performed in conventional precoding. When the appropriate criteria are employed for the selection of the users to be decorrelated, an improved signal to interference-plus-noise ratio (SINR) is obtained without the need for additional power-per-user investment. Performance enhancement is attained for a variety of communication scenarios, but the focus of this paper is on unequal power users systems and the resistance to the near-far effect. Comparative simulations to conventional precoding methods demonstrate the superiority of the proposed technique.

In this paper a new transmitter preceding technique is presented that outperforms conventional preceding by making use of a portion of the interference between the users in a CDMA system downlink. The proposed technique selectively pre-decorrelates users that are experiencing destructive interference while allowing interference to other users when it is expected to contribute to their signal. The existence and exploitation of constructive interference effectively spreads the signal constellation and enhances the SNR at the receiver. The SNR improvement happens by making use of energy that is already in the system so the performance improvement is attained with no additional power-per-user investment. This however comes with the trade-off of some extra processing at the transmitter for the measurement of the expected interference. The proposed technique applies to the downlink of cellular CDMA systems employing PSK modulation. Theoretical analysis supported by comparative simulations of this and other preceding methods are presented and discussed.

Energy-efficient transmission technique is a very essential performance decision factor for maximizing the lifetime of energy-constrained wireless devices such as Wireless Personal Area Network (WPAN) devices. Moreover, if the WPAN is operated in conjunction with a TDMA based scheme, the assurance of QoS requirements in the actual physical transmission at each allocated time slot is another important factor to be satisfied. We therefore propose an energy-efficient and QoS aware transmission scheme for WPANs operating in conjunction with a TDMA-based contention-free medium access protocol. The proposed algorithm determines the optimum combination of transmit power, physical data rate (i.e. modulation level) and fragment size required to simultaneously minimize the energy consumption and satisfy the required QoS in each assigned time duration. The proposed algorithm demonstrated the improved performance results in terms of throughput and energy consumption via computer simulations.

Although multicarrier on-off keying (MOOK) is a relatively bandwidth inefficient technique, the simplicity of its transmitter-receiver pair and inherent coding ability make it a popular choice for a number of communication systems. This technique however is particularly susceptible to frequency selective fading channels which are often encountered in the wireless environment. The aim of this paper is to investigate and analyse bandwidth efficient diversity exploitation techniques with the objective to enhance the performance of this technique. A hybrid frequency-amplitude diversity scheme is proposed. It will be shown that significant performance enhancement can be achieved in frequency selective fading channels, and at no extra bandwidth degradation.

The simplicity of the required transmitter-receiver pair and inherent coding ability of non-coherent multicarrier on-off keying (MOOK) are the reasons for its popular choice for a number of communication systems. Among the disadvantages for this technique however are its relative bandwidth inefficiency and its susceptibility to frequency selective fading channels which are often encountered in the wireless environment. The aim of this paper is to investigate and analyse antenna diversity exploitation techniques with the objective to enhance the performance of MOOK transmissions. Two antenna combining techniques are considered at the receiver and their performances are compared in both static and time varying frequency selective fading channels.

Multiple-input multiple-output (MIMO) systems are still attracting the attention of many researchers and designers for their promising improvements in performance and bandwidth efficiency. This paper presents a low-complexity precoding technique which aims to maximise the MIMO diversity at the receiver. The proposed technique achieves maximum diversity by matching the transmitted data symbols with a suitable precoding matrix from a list of predetermined precoding matrices at the transmitter. This paper shows that significant performance improvements can be obtained with this technique and without any bandwidth degradation.

Multicarrier code division multiple access (MC-CDMA/OFDM-CDMA) is a promising candidate for future high-data rate fourth generation (4G) wireless systems. However multicarrier modulation tends to have a high peak-to-average power ratio (PAPR) factor which leads to a significant degradation in the transmission power efficiency. In this paper we propose a PAPR reduction technique for the downlink MC-CDMA based on redistributing the spreading codes and optimizing the sequences with the objective to minimize the PAPR at the transmitter. Our technique utilizes the characteristic of the CDMA spreading codes as an extra degree of freedom that can be exploited to reduce the signal's PAPR without any loss in the system performance. Both lightly loaded and fully loaded systems are considered with the orthogonal sets of Walsh-Hadamard and complementary Golay sequences. It will be shown that our proposed technique requires very low complexity and only a few side information, while at the same time achieves significant PAPR reduction.

High peak-to-average power ratio (PAPR) is a big obstacle for multicarrier transmission techniques, such as OFDM or DMT. Many PAPR reduction techniques have been proposed in the literature each offering a different combination of system performance, complexity and bandwidth efficiency. Selective mapping (SLM) is one of the most promising techniques which has been shown to offer PAPR reductions of several dBs. However, the fact that the SLM technique requires invoking the IFFT process several times per transmitted OFDM-block increases the system complexity and hence results in long latencies and high power consumption. In this paper, we propose a novel post-IFFT PAPR reduction technique combined with a intelligent strategy for generating a unique time-domain sequence per OFDM block that can minimize the PAPR. It will be shown that our proposed technique has much better overall PAPR reduction ability than the ordinary SLM while at the same time requires several order of magnitude less complexity than that of the SLM technique.

A new transmitter precoding technique is presented that selectively pre-decorrelates users to destructive multiple access interference while allowing interference when it is expected to contribute to the useful signal. This enhances the effective signal to interference-plus-noise ratio at the receiver. The resulting benefit comes by making use of energy that is already in the system so performance improvement is attained with no additional power-per-user investment. The proposed technique applies to the downlink of cellular CDMA systems employing phase-shift-keying modulation.

The inhernet high peak-to-average power ratio (PAPR) of multicarrier transmission, such as OFDM or DMT, is a major drawback that can significantly worsen the power efficiency and performance of these systems. One of the most effective techniques proposed for reducing the PAPR in multi-carrier systems is based on selective mapping (SLM) in which a family of sequencies with random phase distribution is used iteratively to modify the phases of the modulated subcarriers with the aim to minimise the PAPR. However, the fact that this technique requires the transmission of side information, to enable correct demapping at the receiver, reduces the system's spectral and transmission-power efficiency. In this paper, we propose a modified SLM technique that does not require the transmission of any side information while at the same time it can achieve the same PAPR reduction and even lower symbol error rate (SER) performance as the unmodified SLM technique.

Multicarrier code-division multiple access (MC-CDMA) has been tipped as the technique of choice for future high-data rate fourth generation (4G) wireless systems. It is well known however that multicarrier modulation tends to have high Peak-to-Average Power Ratio (PAPR) which results in nonlinear distortions at the high power amplifier (HPA) and consequently degradation of the Bit Error Rate (BER) performance at the receiver. In this paper we introduce a MC-CDMA specific PAPR reduction technique that uses spreading-code shuffling with the objective to minimise the PAPR at the transmitter. Unlike conventional PAPR reduction techniques proposed so far for orthogonal frequency division multiplexing (OFDM) systems, our technique utilises the characteristic of the CDMA spreading codes to reduce the signal's PAPR without any loss in system performance. It can be shown that our proposed technique is much less complex and requires far less side information than many of the existing techniques while at the same time achieves significant PAPR reduction.

The near Gaussian-distribution of the time-domain signal samples of multicarrier transmission, such as OFDM or DMT, gives rise to unacceptable peak-to-average power ratio (PAPR) which leads to a significant degradation in the transmission power efficiency. As a consequence, several PAPR reduction techniques have been proposed in the literature each offering a different combination of system performance, complexity and bandwidth efficiency. One of the most promising of these is the selective mapping (SLM) technique which has been shown to offer PAPR reductions of several dBs. However, the fact that the SLM technique requires invoking the IFFT process several times per transmitted OFDM-block increases the system complexity and hence results in long latencies and high power consumption. Inspired by the SLM approach, we propose a novel post-IFFT PAPR reduction technique combined with a suitable selection strategy for determining a unique set of time-domain sequences per OFDM block that can minimise the PAPR. It will be shown that PAPR reductions within 0.7 dB of the ordinary SLM performance can be achieved with our proposed technique which requires several order of magnitude less complexity than that of the SLM technique

This paper presents new accurate packet error rate analysis of ALOHA type networks that employ BPSK or QPSK modulation in a Rayleigh fading environment. Relying on a precise interference model, we derive new accurate expressions for the packet success probabilities that account for bit to bit error dependence, and are valid for unequal power levels. The accuracy of the new expressions is validated by simulation. These results are used to investigate the throughput performance of Aloha type networks in different local area environments

The use of pilot signals for the purpose of channel estimation in multicarrier systems does not only consume bandwidth but also signal power that could otherwise be invested in the information symbols to be transmitted. The aim of this paper is to investigate the issue of optimal transmitter power distribution between the pilot and information signals and evaluate its impact on the performance of multicarrier systems. It will be shown that the optimal power distribution is primarily influenced by the ratio of number of pilots to the total number of subcarriers used. An optimal pilot power allocation as a function of this ratio will be proposed for both MPSK and MQAM systems taking into account channel estimation errors

Based on the combination of space-time coding and iterative multiuser detection, this paper proposes a new architecture for DS-CDMA systems over frequency-selective channels. A cyclic prefix is also incorporated in the data transmission to cancel the ISI. The novelty of the paper is mainly related to an unexplored combination of known ingredients. To illustrate the practical implementation of this architecture an analysis of complexity is also presented.

This paper reports a number of individual research activities being performed as part of the UK mobile virtual centre of excellence, mobile VCE, an industry-university research partnership conducting precompetitive research for 4G systems.

In this paper we address the problem of how to measure the link quality in terms of signal-to-interference ratio (SIR) over rapidly time varying channels which are due to either fast variation of the interference or the bursty nature of the traffic. We propose a new SIR estimation approach for the UTRA-TDD system, that is based on a pre-selection tentative decision device which discards and selects the estimated symbol on the basis of MAP ratio. Simulation results show that the proposed SIR estimator works well in the context of rapidly time varying channels.

The aim of this paper is to present a comparison between four tree-search based multiuser detectors, namely, the pre-selection based maximum likelihood detector (PS-ML) (Al-Susa and Cruickshank, 2001), the M-algorithm detector (MA) (Wei et al., 1997), the greedy algorithm detector (GA) (AlRustamani and Vojcic, 2000), and the optimum maximum likelihood (ML) detector (Verdu, 1986). The comparison is on the basis of BER performance and computational complexity in both AWGN and multipath channels.