This paper proposes a quantum-enabled gradient-based coverage optimization (QEGCO) framework for dynamic antenna configuration in future wireless networks. The optimization task of adjusting antenna azimuth and tilt to maximize soft coverage is formulated using a differentiable surrogate objective, enabling the application of gradient-based methods. A parameterized quantum circuit (PQC) encodes the control variables, and the parameter-shift rule is employed to compute exact gradients efficiently, independent of spatial sampling resolution. Entanglement is introduced via CNOT gates to enhance circuit expressivity and model interactions between antennas. Simulation results demonstrate that QEGCO achieves faster convergence, higher final coverage ratios, and superior computational scalability compared to classical stochastic gradient descent (SGD) and finite gradient descent (FGD) baselines. Complexity analysis highlights that QEGCO reduces computational complexity from ${\mathcal{O}}(2\cdot a\cdot T)$ in classical methods to ${\mathcal{O}}(2\cdot a\cdot\log (T))$, where a is the number of antennas, and T is the total time required for computation of gradients and coverage metrics. These findings illustrate the potential of quantum-assisted optimization techniques for scalable and efficient wireless network self-organization. Future directions include extending QEGCO to cooperative multi-cell networks and implementing hardware-efficient quantum circuits for near-term quantum devices.

Traditional machine learning techniques have achieved great success in improving data-rate performance and reducing latency in millimeter wave (mmWave) communications. However, these methods still face two key challenges: (i) their reliance on large-scale paired data for model training and tuning, which limits performance gains and makes beam predictions outdated, especially in multi-user mmWave systems with large antenna arrays, and (ii) meta-learning (ML)-based beamforming solutions are prone to overfitting when trained on a limited number of tasks. To address these issues, we propose a memristorbased meta-learning (M-ML) framework for predicting mmWave beam in real time. The M-ML framework generates optimal initialization parameters during the training phase, providing a strong starting point for adapting to unknown environments during the testing phase. By leveraging memory to store key data, M-ML ensures the predicted beamforming vectors are wellsuited to episodically dynamic channel distributions, even when testing and training environments do not align. Simulation results show that our approach delivers high prediction accuracy in new environments, without relying on large datasets. Moreover, MML enhances the model's generalization ability and adaptability.

The exponential growth in the number of handheld devices and other user equipment belonging to power class 3 as per 3GPP specifications is projected to reach 64 billion by the end of 2025. This has led to a drastic increase in the power consumption of radio units. This increase in power consumption is further enabled by the increasing demand for higher data rates and reduced latency for emerging 6G communications. Furthermore, with the expected latency of 1ms in 6G communications, the user equipment demands also change accordingly. This leads to a rapid change in requirements and therefore fluctuations in power consumption. Addressing this problem, this paper presents a novel Quantum Optimised Priority Resource Allocation (QO-PRA) algorithm designed to reduce dynamic power consumption in wireless communications. QO-PRA integrates heuristic-based multi-dimensional knapsack problem framework with quantum algorithms such as the Variational Quantum Eigensolver to optimise its parameters. This allow the QO-PRA algorithm to reduce the power fluctuations in radio units over time. Furthermore, reduced power fluctuations in radio units allow the wireless system to be more efficient, reliable and predictable. Benchmarking the QO-PRA against another widely used scheduling algorithm such as round-robin demonstrates a significant improvement in smoothening power fluctuations over time while maintaining a lower average power and average power per user per second. Furthermore, it achieves a 81.65% lower standard deviation of the first derivatives of power consumption compared to the round-robin algorithms which indicates a smoother power consumption curve.

The trend of integrated satellite-HAP-ground networks (IS-HAP-GNs) as an critical directions for the future development of next generation network technology is widely recognized by academia and industry. Besides, utilizing reconfigurable intelligent surfaces (RIS) as a green paradigm, unmanned aerial vehicles (UAVs) can be equipped to reflect uplink signals from vehicle transmitters (VTs) to high altitude platforms (HAPs). Acting as relays, HAPs then forward these signals to satellites via hybrid free-space optical (FSO) links to enable rapid link deployment. In this paper, we firstly investigate a novel uplink signal transmission mode to maximize the system ergodic sum rate. Then, to tackle the high-dimensional non-convex optimization problems, we propose an asymmetric long short-term memory (LSTM)-deep deterministic policy gradient (DDPG) (AL-DDPG) algorithm builds on the deep reinforcement learning (DRL) framework. The numerical results demonstrate the superiority of the AL-DDPG algorithm over traditional optimization algorithms and reveal the effect of different system parameter settings on the performance.

This paper derives probability distribution functions (PDFs) of the co-channel interference (CCI) and the effective noise (EN) of maximal-ratio combining (MRC) detection in orthogonal frequency-division multiplexing (OFDM) based massive multiple-input, multiple-output (MMIMO) systems. The effects of CCI and EN are expressed as a function of random variables and their PDFs for the OFDM-MMIMO system utilizing Gray-coded, binary and quadrature phase shift keying (BPSK, QPSK), and M-ary quadrature amplitude modulation (QAM) are derived. In addition, we firstly propose asymptotic closed-form expressions for the PDFs of the CCI and the EN in terms of Gaussian mixture model (GMM), i.e., a sum of multiple Gaussian distributions. Furthermore, the proposed PDFs are utilized to determine the probability of bit error (PBE) of the OFDM-MMIMO system. The derived equations are evaluated through Monte-Carlo simulations, and the results confirm that the derived equations produced accurate PDFs and PBE performances of OFDM-MMIMO systems. The PBE from the proposed equations for the 10 × 256 system with 16-QAM, operating at Eb/N0= 5 dB, was 2.41 × 10−5, which was only 1.55 × 10−6different from the simulation result. Therefore, the derived PDFs can be efficiently utilized to evaluate the performance of OFDM-MMIMO systems.

This paper proposes a technique to improve bit error rate (BER) performance of soft-output maximal-ratio combining (MRC) detection for Low-density parity-checked (LDPC)-coded, orthogonal frequency-division multiplexing (OFDM) based massive multiple-input, multiple-output (MMIMO) systems. The detector uses a derived probability distribution function (PDF) instead of the conventional Gaussian distribution to produce soft information in form of the log-likelihood ratio (LLR) for iterative decoders. In order to minimize the complexity of the detector, we utilize a polynomial equation using Newton’s method to produce approximate LLRs. The BER performance over frequency-selective, multi-path, Rayleigh fading channels was investigated through simulation, and the results confirm that the proposed detector provided a better BER performance than that of the classical, low-complexity, soft-output detections, especially at the high Eb/N0region. Therefore, the proposed detection is a powerful technique for improving the reliability of LDPC-OFDM-MMIMO systems.

In this paper, we derive an analytical expression for the average symbol error rate for the 4/16-QAM hierarchical modulation (HM), of the mapped signal at the relay during the up-link phase, for the HP and LP streams, respectively, in Rician fading environments. Furthermore, by utilizing HM for the proposed HM-PLNC system, we minimize the computational complexity at the relay node by reducing the number of Euclidean distance computations (EDCs) to 32 EDCs in fading channels. Performance evaluations show that the proposed system can significantly enhance E2E throughput for the TWRN systems compared to an equivalent 16-QAM based PLNC system. The results present a closed-form solution for HP and LP streams over slow, flat, Rician fading channels.

The unmanned aerial vehicles (UAVs) have attracted much attention in modern wireless communication as an effective solution to improve the coverage in the wireless communication networks. In particular, UAVs have been employed as relay nodes to provide low latency and high data rate connection, especially during disasters, where the existing communication networks are damaged. This paper investigates the end-to-end (E2E) performance of a UAV-aided full-duplex (FD) bi-directional relay network in the presence of the residual loop-interference (LI). First, A closed-form expression for the cumulative distribution function (CDF) of the E2E signal-to- interference-and-noise ratio (SINR) is derived and presented in this work. Next, we introduce a closed-form expression for the E2E average symbol error rate (ASER), which is validated using Monte Carlo simulations. Then, this ASER expression is utilized to evaluate the E2E performance of the FD-UAV- assisted bi-directional network in the presence of the residual LI. The evaluated performance gives the network designers a clear comprehension of the impact of the residual LI on the E2E performance of the investigated network.

In this study, non‐orthogonal multiple access (NOMA) is considered for multiusers wireless communications over Rayleigh fading channel. The base station (BS) utilises NOMA technique to secure connectivity, users fairness and high spectral efficiency for multiusers with different channel conditions. Moreover, a power allocation mechanism is applied at the BS by giving each user its required power allocation factor (PAF) in order to share the available power. Therefore, this technique allows the users of interest to communicate with the BS over the same frequency band simultaneously in the power domain. Moreover, successive interference cancellation is applied for users with the lower PAF to remove the strong signal of the other users. Furthermore, exact expressions are derived for different performance metrics, and the probability density function of the signal‐to‐interference‐plus‐noise ratio is derived at each terminal and then exploited to obtain the outage probability and the probability of error. The performance analysis is verified via Monte–Carlo simulations demonstrating closed‐match with theoretical analysis.

In this paper, a low-complexity cell-edge-aware Antenna Selection (AS) algorithm is proposed for a Multi-User (MU) Massive Multiple-Input Multiple-Output (M-MIMO) downlink system with Matched Filter (MF) precoding. We assume that the users are uniformly distributed in the cell, and therefore, have different Signal-to-Interference plus Noise Ratios (SINRs). At each iteration, the proposed algorithm selects one antenna to reduce the highest interference term between any two users to its minimum value. Furthermore, we utilize a Max-Min Power Allocation (MMPA) scheme to further enhance the performance of cell-edge users and achieve higher fairness. In addition, the complexity of the proposed AS algorithm is evaluated in terms of number of floating-point operations (FLOPs) required for its implementation. Finally, our proposed AS method is compared with other low-complexity AS schemes found in the literature and shown to demonstrate an impressive performance-complexity trade-off.

In this study, the performance analyses of the proposed turbo‐coded orthogonal frequency division multiplexing (T‐COFDM) are investigated over the power‐line communication with lognormal channel gain based on derived effective complex‐valued ratio distributions of the individual and combined noise samples at the zero‐forcing equaliser output. The effective noise samples are derived in the presence of Nakagami‐m background interference (BI) noise, Middleton class A impulsive noise (MCAIN) and their combination. The performance of the turbo code has been improved by computing the exact log‐likelihood ratio using derived distributions, with the derivation of pairwise error probability and the average upper‐bounds (AUBs). Moreover, the bit error rate (BER) degradation in the conventional T‐COFDM system has been improved by deriving two clipping thresholds to combat the effect of the non‐Gaussian noise, the first one has been derived in the presence of the impulsive noise only modelled by MCAIN model and the second one in the presence of combined Nakagami‐m BI noise and MCAIN model. Monte Carlo simulations demonstrate the significant BER improvements of the proposed T‐COFDM system compared to the improved conventional T‐COFDM system with a close agreement to the AUBs derivation and analytical BER expression.

To achieve increased capacity over legacy twisted-pair copper, standards have considered use of increasingly high frequencies. The most recent digital subscriber line (DSL) standard, G.fast, carried forward the forward error correction scheme from the previous standards, namely the concatenated Reed Solomon and multi-dimensional trellis coded modulation scheme. In this work, a novel joint code and interleaver optimisation for low-density parity-check (LDPC) coded multicarrier systems with variable bit loading is proposed. This optimisation exploits the effects of both the channel and the modulation scheme on the soft information available at the LDPC decoder, through use of extrinsic information transfer (EXIT) analysis. The performance of the proposed scheme is demonstrated for the discrete multi-tone system operating on a twisted-pair channel.

In this paper, we study the impact of the co-channel interference (CCI) in conjunction with the impact of residual self-interference (SI) on the end-to-end (E2E) performance of a denoise-and-forward full-duplex one-way relay channel (DNF-FD-OWRC) network. The investigated system comprises one source node S, which communicates with one destination node D with the aid of an FD relay node, over Rayleigh fading channels. Closed-form expressions for the cumulative distribution function (CDF) and the distribution of the E2E signal-to-interference and noise ratio (SINR) are derived and presented. Moreover, a closed-form expression for the E2E outage probability is presented and validated using Monte Carlo simulations. The obtained results demonstrate the impact of the residual SI and CCI on the E2E performance of the DNF-FD-OWRC and demonstrate the ability of DNF-OWRC to improve the throughput of a conventional half-duplex (HD) OWRC.

Massive Multiple-Input Multiple-Output (MIMO) systems can significantly improve the system performance and capacity by using a large number of antenna elements at the base station (BS). However, having a massive number of radio-frequency (RF) chains at the BS can be costly and energy inefficient. One way to achieve the diversity gain of massive MIMO systems is to employ a massive number of antennas with limited number of RF chains. Thus, antenna selection techniques can be applied to reduce the system complexity and hardware cost. In this paper, a Quantum-inspired Tabu Search (QTS) algorithm is applied to antenna selection in Massive MIMO systems and compared with two well known algorithms; namely, a Classical Tabu Search (CTS) algorithm and a Genetic Algorithm (GA). The QTS algorithm has a great advantage over CTS, since it only requires finding the optimum rotation angle to evolve the system towards a better solution. In contrast, in CTS, the dimensions of the tabu matrix are dynamic and need to be optimized. Moreover, to achieve maximum performance, these dimensions need to be reconfigured when changing the number of antennas or the number of iterations, while no such a problem occurs in the QTS. The QTS algorithm also shows better results in terms of the system capacity compared to CTS and GA. Furthermore, the classical and quantum inspired TS algorithms require much lower complexity than the GA.

In this paper, we derive a tight upper bound on the performance of a coded full-duplex multiple-input multiple-output (MIMO)-based bidirectional transceiver. Iterative detection and decoding (IDD) are proposed to suppress the residual self-interference (SI) remaining after applying different stages of SI cancellation. IDD comprises an adaptive minimum mean-squared error filter with log-likelihood ratio demapping, while the soft decoder by using soft-in soft-out decoding utilizes the maximum a posteriori algorithm. Furthermore, bit-interleaved coded modulation is considered in the presence of additive white Gaussian noise over MIMO frequency non-selective Rayleigh fading channels. Simulation results are presented to demonstrate the bit-error rate (BER) performance as a function of the signal-to-noise ratio showing a close match to the SI-free case for the proposed system. Furthermore, we validate our results by deriving a tight upper bound on the performance of the proposed system using rate-1/2 convolutional codes together with M-ary quadrature amplitude modulation, which asymptotically exhibits a close agreement with the simulated BER performance. Moreover, extrinsic information transfer chart analysis is used to investigate the convergence behavior of the proposed IDD receiver and to determine the number of iterations required for this convergence.

In this paper, the impact of co-channel interference (CCI) on the performance of an underlay cognitive radio (CR) network over Nakagami-m fading channels is presented and analyzed. More precisely, a decode-and-forward (DF) relay protocol for a dual-hop cognitive cooperative network is considered. In this study, the impact of both the primary transmitter and CCI on the secondary system performance are considered. First, an exact expression for the equivalent signal-to-interference-plus-noise ratio (SINR) of the secondary system is obtained. Then, the corresponding exact and asymptotic cumulative distribution function (CDF) are derived. From this, the exact outage performance for the secondary network is investigated. From the results, it can be inferred that the presence of the CCI and primary network interference severely degrades the system performance. Moreover, a higher value of the shape parameter of the desired channel gives better performance and diversity gain. Finally, the analytically derived results have been supported by providing numerical and Monte Carlo simulations results.

In this study, the performance of irregular low‐density parity check (LDPC) coded orthogonal frequency division multiplexing (COFDM) utilising 4096 quadrature amplitude modulation (4096‐QAM) is investigated over multipath power‐line communication (PLC) channel. The effective complex‐valued ratio distributions of the noise samples at the zero‐forcing equaliser output considering both frequency‐selective multipath PLCs, background and impulsive noise are derived, in addition to the condition for optimum detection of 4096‐QAM and the bit error rate (BER). Moreover, the performance of the LDPC decoder is improved by computing the log‐likelihood ratios (LLRs) required for soft decoding based on the derived probability density functions. Numerical results obtained using the newly derived LLRs demonstrate a significant performance improvement compared to the conventional receiver that uses blanking impulsive noise mitigation method and LLR computed based on the Gaussian distribution. Furthermore, EXtrinsic Information Transfer chart analysis demonstrates that the proposed approach requires fewer iterations for convergence compared to the conventional receiver. Finally, utilising channel bandwidth of 22.4 MHz, the proposed system offers an improvement of 111 Mbps over the conventional system to reach a maximum data throughput of 256 Mbps for a signal‐to‐noise ratio of 39 dB and BER of .

In this paper, we derive the bit error rate and pairwise error probability (PEP) for massive multiple-input multiple-output orthogonal frequency-division multiplexing (MIMO-OFDM) systems for different M-ary modulations based upon the approximate noise distribution after channel equalization. The PEP is used to obtain the upper-bounds for convolutionally coded and turbo coded massive MIMO-OFDM systems for different code generators and receive antennas. In addition, complexity analysis of the log-likelihood ratio (LLR) values is performed using the approximate noise probability density function. The derived LLR computations can be time-consuming when the number of receive antennas is very large in massive MIMO-OFDM systems. Thus, a reduced complexity approximation is introduced using Newton's interpolation with different polynomial orders and the results are compared with the exact simulations. The Neumann large matrix approximation is used to design the receiver for a zero-forcing equalizer by reducing the number of operations required in calculating the channel matrix inverse. Simulations are used to demonstrate that the results obtained using the derived equations match closely the Monte Carlo simulations.

In this paper, we present a two-way relay channel (TWRC) network that utilizes a full-duplex physical layer network coding (FD-PLNC) scheme in conjunction with amplify-and-forward (AF) relaying and orthogonal frequency-division multiplexing (OFDM). In order to cope with the self-interference (SI) induced by the FD mode of operation, a self-interference cancellation (SIC) scheme is utilized at each node in the proposed system. The performance of the proposed system is thoroughly investigated in the presence of residual SI by deriving a closed-form expression for the distribution of the tight upper bound end-to-end (E2E) signal to interference and noise ratio (SINR). Furthermore, an exact closed-form expression for the tight upper bound ergodic capacity is derived and used to evaluate the E2E upper bound ergodic capacity of the proposed AF-FD-PLNC system. The obtained results demonstrate the ergodic capacity gain of the proposed AF-FD-PLNC over the ergodic capacity of traditional AF half-duplex (HD) PLNC systems. In particular, the proposed AF-FD-PLNC can increase the ergodic capacity of AF-HD-PLNC by a factor of 2 when the SNR is higher than 25 dB and the SI to noise ratio is less than 0 dB.

The nature of cognitive radio is based on the co-existence of secondary users in the area of primary users. Co-channel interference (CCI), therefore, is a vulnerable phenomenon in such a system. Motivated by this, a more practical scenario has been considered for studying the performance of the single-input-multiple-output (SIMO) underlay cognitive cooperative network. In this investigation, the primary transceiver is considered as well as the impact of the CCI on the secondary network. For this practical scenario, the equivalent signal-to-interference-plus-noise ratio (SINR) of the secondary system is obtained by employing the selection combining (SC) technique at the receiver side. Then, the cumulative distribution function (CDF) of the equivalent SINR is derived. Using the derived CDF, exact outage probability for the secondary network is assessed. From the results, it can be deduced that using a multi-antenna scheme and applying the SC technique has the advantage of improving the system performance. Moreover, besides the impact of the interference power constraint, the presence of the primary transmitter and the CCI will severely reduce the system performance, especially when the CCI linearly increases with the secondary transmit powers. Finally, numerical results and Monte Carlo simulations have also been provided to support the correctness of the analytical derivations.

In this study, the authors investigate the performance of opportunistic scheduling for the dual‐hop amplify‐and‐forward multi‐user cognitive relaying network. Expressions are derived for the cumulative distribution function (CDF) and probability density function of the equivalent signal‐to‐noise ratio (SNR). From the derived CDF, the outage performance of the cognitive network is investigated. Then, an expression for average error probability is derived. Furthermore, simple and generic asymptotic expressions for the outage and error probabilities are obtained and discussed. In addition, a closed‐form expression for the system's ergodic capacity is derived. Their asymptotic results show that opportunistic scheduling has no impact on diversity gain. It is confirmed that the array gain determines the SNR advantage of opportunistic scheduling over the single‐user scenario. Moreover, they study adaptive power allocation under the total transmit power constraint in order to minimise the average error probability. As expected, the results show that optimum power allocation improves system performance compared with uniform power allocation. Finally, numerical results and Monte Carlo simulations are also provided to support the correctness of the analytical calculations.

In this paper, the performance of a multi-hop underlay cognitive radio network (UCRN) is thoroughly assessed. The co-existence of a primary transceiver and co-channel interference (CCI) is considered along with an uplink single-input multiple-output system utilizing selection combining and maximal ratio combining techniques at the receiver nodes. First, the equivalent per-hop signal-to-interference-plus-noise ratio (SINR) for the UCRN is formulated. Second, the exact cumulative distribution function (CDF) and the probability distribution function of the per-hop SINR are derived and discussed. Furthermore, approximate expressions exhibiting reduced complexity for the per hop equivalent CDF are derived to provide more insights. From the resulting CDF, the exact outage performance of the CR network is thoroughly assessed. In addition, mathematical formulas are derived for the average error probability and system ergodic capacity. Finally, the derived analytical expressions are validated by presenting numerical and simulation results for different network parameters. The results show that several factors contribute to the degradation of the system performance, namely, the interference power constraint, the primary transmitter power, and the presence of CCI, especially in the case where the CCI increases linearly with the secondary transmission powers.

In this paper, we investigate the performance of a coded full-duplex multiple-input multiple-output (FD-MIMO) bi-directional transceiver. To mitigate self-interference (SI), iterative detection and decoding (IDD) are proposed that utilize soft parallel interference cancellation (SPIC) with adaptive Minimum Mean-Squared-Error (MMSE) filtering. Furthermore, Space-Time Bit-Interleaved Coded Modulation (ST-BICM) based channel coding schemes are considered, i.e. convolutional or turbo code based, and the system performance is evaluated in the presence of additive white Gaussian noise (AWGN) over MIMO Rayleigh fading channels. The proposed near-optimal IDD scheme performs cancellation of SI by iteratively exchanging the soft information of the desired and SI signals between the detector, which comprises adaptive MMSE filtering with log-likelihood ratio (LLR) demapping, and the soft-in soft-out (SISO) decoder implementing linear to logarithmic approximation of the maximum a posteriori algorithm. Performance results are presented to demonstrate the Bit-Error-Rate (BER) performance of the proposed coded FD-MIMO as a function of the signal to noise ratio (SNR). Furthermore, a comparison of the proposed IDD system with relevant state-of-the-art approaches is given which shows a significant improvement in performance as a result of the introduced iterative processing that reduces SI considerably.

Cognitive radio allows secondary users to use the same existing frequency spectrum band as primary users. This co-existence has several impacts on the whole network. This has motivated us to study the performance of a more practical dual-hop underlay cognitive network, by considering the interference power constraint, the primary transceiver and the co-channel interference (CCI).We start by determining the equivalent signal-to-interference-plus-noise ratio (SINR) of the secondary network, then, we derive the cumulative distribution function (CDF) of the equivalent SINR. Using the derived CDF, system outage probability has been assessed. Furthermore, an approximate expression for the system average error probability has been derived. From the results it can be observed that besides the impact of the interference power constraint, the presence of the primary transmitter and the CCI will severely reduce the system performance especially when the CCI linearly increases with the secondary transmit power. Finally, numerical results and Monte Carlo simulations are also provided to sustain the correctness of the analytical derivations.

High speed transmission of information suffers inevitably by intersymbol interference (ISI) induced by multipath propagation over frequency selective channels. ISI has been a major obstacle preventing the successful implementation of physical layer network coding (PLNC) systems in these environments. Another major obstacle is the high computational complexity of existing algorithms dealing with ISI, which is a determining factor in the design of relay nodes. In this paper, we propose a novel and computationally efficient decision feedback equalizer structure that is utilized at the end node and in conjunction with a simple amplify and forward (AF) technique employed at the relay. We derive the optimal equations for the decision feedback equalizer (DFE) coefficients and evaluate the end-to-end bit error rate performance in frequency selective channels, and provide both analytical and numerical simulation results that demonstrate the feasibility of the proposed approach under realistic channel conditions. The obtained results show that E2E performance is dominated by the channel with most severe frequency selectivity.

In this paper, a new receiver structure is proposed for uplink interleaved division multiple access (IDMA) on multipath fading channels. In a conventional IDMA rake detector, jointly removing inter symbol interference (ISI) and multiple access interference (MAI) is achieved by exchanging extrinsic log-likelihood ratio (LLR) chips between an elementary signal estimator (ESE) and a posteriori probability decoders (DEC)s in a turbo-like manner. The same exchanging principle takes place between a centralized decision feedback equalizer (CDFE) and the DECs in CDFE-IDMA systems. However, the proposed IDMA receiver can be considered a mixture between the two mentioned receivers as it employs an adaptive DFE for each user to remove the ISI effects while MAI is eliminated by a parallel interference canceller (PIC). The PIC utilizes the same ESE principles in removing MAI effects from received symbols which is more efficient than cross-over filters in a CDFE-IDMA system. Moreover, the ISI abstraction in DFE is more active in removing ISI than ESE. Simulation results demonstrate the superiority of DFE-IDMA over the other systems' performances found in the literature for both optimal and adaptive algorithms (AA).

We propose and analyze the performance of the full-duplex multiple-input multiple-output singular value decomposition (FD-MIMO-SVD) based relay with self-interference-cancellation (SIC). The effects of channel estimation errors for the source-to-relay and self-interference channels are considered. The performance of the system is investigated in the presence of additive white Gaussian noise (AWGN) over Rayleigh fading channels. Analytical results are presented for this system by exploiting SVD as a dominant eigenmode transmission for maximizing the signal-to-noise ratio (SNR) of the desired signal, in addition to mitigating the self-interference (SI). Furthermore, exact, closed-form solutions for the signal-to-interference-plus-noise-ratio (SINR) distribution and outage probability are derived and evaluated along with the average symbol error rate (ASER) for M-ary phase-shift keying (MPSK) modulation schemes.

A new cost efficient automated planning and optimization method is proposed for OFDMA future-generation cellular networks targeting throughput maximization. The mathematical formulation is a non-linear multi-objective optimization problem subject to minimum interference, cost and similar resource constraints at each cell within a defined heterogeneous traffic environment. The fundamental objective is to maximize the individual cell throughput without deteriorating it over other cells, which results in a throughput equilibrium maximization over multiple cells. This implicitly implies traffic and co-channel interference congestion avoidance across the network whilst maintaining both cost efficiency and quality of service (QoS) policies. Optimal solution existence is subject to the network size, traffic and computational complexity constraints which converges to a throughput equilibrium or alternatively to the well known Nash Equilibrium (NE).

In this work, a new low complexity linear precoded orthogonal frequency division multiplexing (LP-OFDM) system, called Haar-OFDM (H-OFDM), is proposed. The proposed system employs a fast precoder, denoted as inverse D-precoder (IDP), which is derived by merging the operations of the fast Haar precoder (FHP) and inverse fast Fourier transform (IFFT) as one transform. Interestingly, the number of arithmetic operations required by the H-OFDM system are noticeably smaller than the conventional OFDM. Furthermore, extensive simulation results demonstrate that the H-OFDM system is robust against the frequency-selectivity of the channel.

Throughput maximization is generally the major objective when allocating resources in orthogonal frequency division multiple access (OFDMA)networks. Traditionally, dynamic allocation methods were developed to exploit multi-user diversity in these networks. These techniques achieved significant gain in throughput by adopting relaxed convex models to define system upper bound capacity. Frequency diversity, on the other hand, is only considered to a certain extent in order to meet user service constraints. The vast majority of existing research relies on these techniques. Separately, research considering combining frequency diversity and multi-user diversity in full has been scarce. The results of our research in this paper show that using this dual diversity combining can substantially maximize system capacity and resource efficiency, and minimize outage probability whilst users' quality of service (QoS) demands are maintained.

In this letter, a Sum-Product algorithm (SPA) utilizing soft distances is shown to be more resilient to impulsive noise than conventional likelihood-based SPAs, when the noise distribution is unknown. An efficient version of the soft distance SPA is also developed but with half the storage requirements and running time.

In this work, a new technique for mitigating the impulsive noise impact on the orthogonal frequency division multiplexing (OFDM) system is proposed, and its performance is compared with a previously published technique (referred to as time-domain interleaving (TDI) technique). In the TDI technique, the samples contaminated by impulsive noise are spread in timedomain over N OFDM symbols by using an interleaver after the inverse fast Fourier transform (IFFT) process. Accordingly, the effect of the impulsive noise burst will be averaged over N OFDM symbols, which reduces the impact on the bit error rate (BER) considerably. However, to achieve the same goal, the proposed system is using an additional orthogonal transform in form of an IFFT at the output of the interleaver. In general, the two techniques have shown a superior improvement in BER performance compared to that of the standard OFDM system, which suffers from error floors at high values of signal to noise ratio (SNR). However, for quadrature phase shift keying (QPSK) modulation with low signal to impulsive noise ratio (SIR), the proposed technique outperforms the TDI technique for different impulsive noise distributions. For high modulation order 16 and 64 quadrature amplitude modulation (QAM) in severe impulsive noise channels, the proposed technique demonstrates more robustness than the TDI, which suffers from error floors for the considered values of SIR and impulsive noise distributions.

Due to the nonlinear characteristics of the high power amplifier (HPA), the employment of orthogonal frequency division multiplexing (OFDM) based modulation schemes results in significant amplitude and phase signal distortion due to the high peak-to-average power ratio (PAPR) nature of the OFDM. To overcome this problem, PAPR reduction methods are commonly applied at the transmitter. Among the plenitude of methods available, partial transmit sequences (PTS) and selected mapping (SLM) are the most powerful schemes. The computational complexity for these schemes is considered as the main disadvantage. In this paper, we propose a low-complexity scheme based on iterative PTS (IPTS) that employs two inverse fast Fourier transforms (IFFT) and two circulant transform matrices. Numerical results demonstrate that the proposed scheme using a partition vector for IPTS with an odd number of ones can achieve both a reduction in PAPR of approximately 2 dB and an improvement of 1.4 dB in terms of signal-to-noise ratio (SNR) to achieve a bit error rate (BER) of 10-4. A further simplification can be achieved by omitting one of the circulant transform matrices in order to improve the computational complexity reduction ratio (CCRR) by 30% and reduce the number of side information bits by 1-bit compared with the IPTS, however, at the cost of a small reduction in PAPR and BER performance.

In this work, an elegant interleaving process is used not only to mitigate the impact of bursty impulsive noise on the performance of orthogonal frequency division multiplexing (OFDM) systems but also to break bursty multipath fading channel errors. While, conventional OFDM systems implement the interleaving process in the frequency domain, the system proposed here uses a block interleaver of size N2samples in the time domain. As a result, time diversity has been exploited through the use of the interleaver by spreading the samples contaminated by impulsive noise over the impulse-free OFDM symbols and breaking the correlated behaviour of the multipath fading channel. Nevertheless, the results, given in this work, have shown that the performance of the proposed system depends on the kind of equalization process used. A serious degradation in the performance is noticed when zero forcing (ZF) equalizer is utilized. However, a simple and low complexity solution to improve the ZF equalizer performance is also proposed. On the other hand, utilizing a minimum mean square error (MMSE) equalizer demonstrates better performance than the ZF equalizer. The simulation results have confirmed the validity of the proposed system over different scenarios of the channels considered in this work.

In this paper, a new network planning framework is proposed for orthogonal frequency-division multiple access (OFDMA) cellular systems based on co-channel interference and traffic congestion avoidance. The network planning is formulated as a non-linear multi-objective optimization problem subject to minimum interference and related resource constraints at each cell under heterogeneous traffic. The multi-objective problem is represented by the throughput maximization of each single cell without penalizing the remaining cells, which results in a throughput equilibrium over the whole network. The fundamental objective is to maximize the throughput balance and, hence, traffic and co-channel interference congestions are avoided across the network. In order to maximize the equilibrium, the optimization problem is decomposed into a positioning problem and a resource allocation problem, which are solved by parallel heuristics and convex optimization. Additionally, a novel rotated polarization assignment method is proposed to minimize further the effect of the co-channel interference.

This paper presents an efficient technique to eliminate the inter-layer interference (ILI) inherent in hierarchical modulation (HM) schemes operating over nonlinear satellite channels. The HM considered in this work is used in conjunction with an orthogonal frequency division multiplexing (OFDM) system. The proposed technique is based on an enhanced version of the selective mapping (SLM) scheme used for peak-to-average power ratio (PAPR) reduction. The enhanced SLM is constructed by using a new metric, which is more informative than the conventional PAPR metric. Simulation results confirmed that a noticeable bit error rate (BER) and interference reductions can be achieved by using the proposed technique.

Two adaptive receivers for jointly detecting active users in an interleave division multiple access (IDMA) system are considered for highly dispersive underwater acoustic channels (UACs) using a continuous pilot approach. A direct adaptive interference cancellation (IC) IDMA receiver is proposed and compared with the standard Rake-IDMA receiver that performs adaptive semi-blind channel estimation developed by the authors. Both iterative decoding receivers incorporate a phase locked loop (PLL) and are optimized based on the minimum mean square error (MMSE) criterion. The theoretical basis of both receivers is presented along with experimental results obtained by processing data from actual underwater communication experiments. The transmission results of 3 active users at a data rate of 441.3 b/s per user within 4 kHz bandwidth demonstrate that the IC-IDMA receiver has better performance and significantly mitigates the bit errors associated with Rake-based IDMA receiver.

In this paper, a time varying Doppler-shift compensation scheme for wideband orthogonal frequency division multiplexing (OFDM) suitable for shallow water communications is proposed. This scheme accommodates a channel model having velocity that accelerate and de-accelerate during a packet of multiple OFDM frames. Furthermore, it assumes that the Doppler-shift varies linearly during the symbol time. To deal with this variation, the time expansion/compression is measured within a fraction of the sample period and then compensated using sample-by-sample interpolation. The Doppler-shift and its residual are frequently estimated during the symbol time to mitigate the inter-carrier interference (ICI) by estimating the first order moment of the cyclic prefix correlation. Additionally, in this technique, the fractional deviation of the sub-carrier spacing, which is considered to be the source of ICI, is estimated by exploiting the fractional part of the normalized sampling frequency offset. The proposed algorithm performance is investigated with real data obtained from an experiment that took place in the North Sea in 2009. In addition, results show that the technique is robust and more pragmatic than existing cyclic prefix (CP)-based algorithms.

This paper presents a robust timing recovery scheme for orthogonal space-time block coding (OSTBC) multi-input multi-output (MIMO) orthogonal frequency division multiplexing (OFDM) systems with constant modulus constellation. In the proposed system, the symbol timing is achieved either by minimizing the power difference between adjacent subcarriers in one STC block or between subcarriers with similar indices in consecutive STC blocks. The proposed technique is totally blind because it does not require any prior information about the channel state or the transmitted data. The early-late gate (ELG) configuration is utilized to realize the proposed timing recovery scheme efficiently. Monte Carlo simulations are used to assess the performance of the two realizations of the proposed system over fading channels with different frequency-selectivity conditions. Simulation results demonstrated the superiority of the proposed technique to provide accurate symbol timing even in severe frequency-selective fading channels which remarkably outperforms other timing metrics.

In this study, new mathematical formulations and algorithms for joint scheduling and hybrid resource allocation are derived and investigated for a multi-user downlink orthogonal frequency division multiple access system. A three-sectored multi-cellular heterogeneous traffic environment is considered where users are randomly distributed and categorised under different priority levels. Traffic consists of time delay-sensitive and time delay-insensitive services. Three practical scheduling and resource allocation methods are proposed to address the balance between throughput, outage probability and resource efficiency under varying channel conditions. The proposed methods are based on the Lagrangian duality framework, and are formulated as mixed integer programming problems constrained by the total power of the base station and users' data rate while maintaining the quality of service for each user. Both dynamic and fixed resource allocation approaches are included in the main problem formulation. The complexity of the resource allocation problem is minimised by approximating the well-known water level. Simulation results show that the total system throughput is penalised for the method that aims to minimise the outage probability of the highest priority level. This is because of the severe channel conditions experienced by some users, whereas the alternatively proposed methods maintain system efficiency under a similar amount of constrained resources and required traffic.

This paper introduces a new multicarrier system that uses a low computational complexity transform developed by Boussakta to combine the Walsh-Hadamard Transform (WHT) and Discrete Fourier Transform (DFT) into a single orthogonal transform or as a transition from one transform domain to another. The proposed transform is used in a new orthogonal frequency division multiplexing (T-OFDM) system, across fixed and mobile multipath channel models. Use of the proposed transform with OFDM has been found to achieve high diversity gain by spreading each subcarrier with all the others. Consequently, severe distortion arising from channel fading on the subcarrier power is minimised. Simulation results confirm that the proposed T-OFDM system outperforms the conventional OFDM system when utilizing the minimum mean square error (MMSE) equalizer. The main, merits of such a transform are low computational complexity, no bandwidth expansion, the same average transmitted power, and a high ability to mitigate the influence of multipath channel dispersion.

In this work, an efficient interleaving process is proposed for orthogonal frequency division multiplexing (OFDM) systems over impulsive noise channels. Unlike the conventional OFDM systems where the interleaving process is implemented before the inverse discrete Fourier transform (IDFT), the proposed scheme is based on performing the interleaving process post the IDFT. The aim of this process is to average the effect of the impulsive noise burst over a large number of OFDM symbols, which can reduce its impact on the bit error rate (BER) significantly. For the system and channel models considered in the work, simulation results have confirmed that the proposed system can effectively reduce the BER degradation due to the impulsive noise to about 1 dB as compared to the impulsive noise-free case.

We propose a cross-layer strategy that jointly optimizes user scheduling and resource allocation for adaptive modulation and coding (AMC) based orthogonal frequency multiple access (OFDMA). The objective of this paper is to maximize the system throughput as a function of the bit error rate (BER) and the spectral efficiency based on selected modulation and coding schemes (MCSs). The proposed optimal user scheduling and resource allocation (OSRA) strategy arranges the users in distinct queues according to their priorities and selects users in an optimal manner that guarantees fair services for users among different priority levels. Moreover, it allocates the available resources optimally over the utilized sub-channels. The transmitter of the investigated AMC-OFDMA system at the assigned base station (BS) divides the transmitted OFDMA frame into sub-channels depending on the number of the considered priority levels. Simulation results show that the performance of the investigated AMC-OFDMA system based on the proposed OSRA strategy outperforms the conventional approaches.

In this paper, a new joint scheduling and hybrid resource allocation method is derived and investigated for a multi-user downlink Orthogonal Frequency Division Multiple Access (OFDMA) system that provides Time Delay-Sensitive services (TDS) and Time Delay-Insensitive services (TDI). A three sectored multi-cellular heterogeneous traffic environment is considered where users are randomly distributed and categorised under different priority levels. The method is proposed to address the balance between throughput, outage probability, and user priorities under varying channel conditions. The proposed method is based on the Lagrangian duality framework, and have been formulated as a Mixed Integer Non Linear Problem (MINLP) constrained by the total power of the Base Station BS and users' data rate while maintaining the Quality of Service (QoS) for each user. The hybrid resource allocation includes dynamic and fixed allocations in the main problem formulation. Simulation results show that the outage probability gaps between the priority levels are reasonably balanced. This is due to the optimality conditions which restrict the resource allocation domain for each priority level to avoid sever penalisation of one priority level over the others.

This paper presents a new blind symbol timing offset (STO) estimation scheme for wireless orthogonal frequency division multiplexing (OFDM) systems with constant modulus constellation. In the proposed scheme, the STO estimation is performed by minimizing the power difference between either adjacent or consecutive subcarriers, which basically depends on the assumptions made on the channel conditions. Monte Carlo simulation is used to assess the two realizations of the proposed system. The system performance is evaluated by means of mean squared error (MSE) over additive white Gaussian noise (AWGN) and frequency selective mobile radio channels. The simulation results demonstrate that the MSE of the proposed system is well below the MSE of other well-established estimators reported in the literature.

In this paper, we propose a bit and power allocation strategy for adaptive modulation and coding (AMC) based spatial multiplexing multi-input-multi-output (MIMO) orthogonal frequency division multiple access (OFDMA) systems. This strategy aims to maximize the average system throughput by allocating the available resources optimally among the utilized bands depending on the corresponding channel conditions and the total transmission power constraints. The average system throughput is represented as a trade-off criterion between the spectral efficiency and bit error rate (BER). The considered AMC technique utilizes distinct modulation and coding scheme (MCS) options rather than adopting fixed or uncoded approaches. The transmitter divides the OFDMA frame at each transmit antenna into bands depending on the number of active users in an assigned base station (BS). The simulation results show superior performance of the MIMO-AMC-OFDMA system, which adopts the proposed strategy, over other conventional schemes.

In this paper, a new planning method is proposed for the next generation wireless networks that are based on Orthogonal Frequency Division Multiple Access (OFDMA). As a consequence of the wide variety service demands in terms of data rate and Quality of Service (QoS), the traffic pattern is considered to be heterogeneous. Therefore, the complexity of obtaining Base Stations (BSs) positions increases with the randomness of the traffic distribution. In addition to this challenge, the capacity of each BS is limited due to power and bandwidth constraints, propagation losses, Gaussian antenna pattern, and the Co-Channel Interference (CCI), which in turn increase the complexity measures for an efficient network design. According to Nash Equilibrium, combined efficient systems must perform equally to achieve certain performance. This implies that the traffic of a cellular system should be equally distributed over all the BSs to achieve the highest network performance. Hence, we formulate the planning problem as a non-linear multi-objective optimization problem. The optimum solution should not dominate the throughput of one BS over the others and this is referred to as Pareto optimal. However, loading all cells equally may not be possible in certain traffic distributions. Therefore, the proposed method tends to approach the optimal solution by tackling the problems of BS positioning and resource allocation simultaneously. We adopt a hybrid approach, i.e. Pareto-Metaheuristic (PMH) that achieves a balanced throughput over all cells as well as minimizing the number of the installed BSs targeting a certain service outage probability. Simulation results show that, in addition to maximizing the individual cell throughput, the network throughput variation decreases as the number of iteration increases.

This study presents an iterative carrier frequency offset estimator for orthogonal frequency division multiplexing (OFDM) systems. The proposed estimator is based on the efficient Viterbi-and-Viterbi (VAV) algorithm. The proposed estimator is blind and can be used with non-constant modulus subcarrier modulations such as quadrature amplitude modulation (QAM). The performance of the proposed estimator is assessed theoretically and via Monte Carlo simulations over various channel models and compared to the performance of other well established blind techniques in addition to the Cramèr–Rao lower bound. The comparison results demonstrate that the proposed estimator outperforms other well-established blind estimators by more than 12 dB at moderate and high signal-to-noise ratios (SNRs).

This study presents a new blind carrier frequency offset (CFO) estimation technique for multi-input multi-output (MIMO) orthogonal frequency division multiplexing (OFDM) systems employing space–time coding (STC). CFO estimation is crucial for OFDM systems to avoid the performance degradation because of the inter-carrier interference that results when the CFO is not estimated and compensated accurately. Based on the assumptions that the data symbols are selected from a constant modulus constellation and the channel is varying slowly over time, a new blind CFO estimator is proposed by minimising the power difference between all subcarriers in two consecutive STC blocks. Therefore the proposed system exploits all subcarriers in time and frequency domain, which provides a remarkable performance improvement over other techniques reported in the literature. The complexity of the proposed estimator is substantially reduced by approximating the cost function by a sinusoid that can be minimised using direct closed-form computations within one OFDM symbol period. Monte Carlo simulations are used to assess the performance of the proposed system by means of mean squared error (MSE) in both static and time-varying frequency-selective fading channels. The simulation results demonstrate that the proposed estimator can eliminate the MSE error floors that usually appear at moderate and high signal-to-noise ratios for the estimators that work only in frequency domain.

Precoded spatial multiplexing multiple-input multiple-output (MIMO) systems using limited feedback are mainly based on the notion of delay-free feedback channels. In this paper, we take into account the time varying nature of the channel, and consider the feedback delay problem. In order to reduce performance degradation of spatial multiplexing systems in the presence of feedback delay, we propose the use of a Kalman filter linear predictor at the receiver to provide the transmitter with the predicted channel state information, and hence, mitigate the effect of feedback delay. The performance of this method is assessed using computer simulation, and the obtained results for the proposed channel prediction scheme demonstrate improved bit error rate performance for time varying Rayleigh fading channels.

Fourth generation (4G) mobile access is drawing particular attention as it promises to deliver high data rates and reliable coverage for broadband wireless access. In this paper, Orthogonal Frequency Division Multiplexing Access (OFDMA) and Multi-Carrier Code Division Multiplexing Access (MC-CDMA) are investigated to highlight their strengths and weaknesses as candidates for 4G wireless access. Using a multi-cell environment, MC-CDMA and OFDMA coverage is dimensioned based on the value of the Signal to Interference plus Noise Ratio (SINR). The results show that OFDMA system offers cell coverage of 92.5% and a maximum actual throughput of 24.2 Mbps/cell (fade margin 10 dB). Using the same assumptions for MC-CDMA, the results show better coverage only with complete orthogonal spreading codes which can guarantee 97% of user coverage and actual throughput of 28.8 Mbps. These measurements decrease as the orthogonality between the spreading codes is reduced. In the case of 94% orthogonality the MC-CDMA system achieved 89.3% coverage and 21.9 Mbps throughput while with a 60% orthogonality 47% coverage and 5.8 Mbps throughput was achieved.

In this paper, we consider the effect of impulsive noise on the performance of multicarrier code division multiple access (MC-CDMA) systems and analyze the performance by examining the MC-CDMA system model in time domain. We have discovered that conventional Walsh-code based MC-CDMA is less robust to the presence of impulsive noise than the corresponding direct sequence (DS) CDMA and multicarrier modulation based (MCM) systems. Furthermore, it is demonstrated that the performance of MC-CDMA depends strongly on the selection of the utilized spreading codes. A modified MC-CDMA structure, called MC-SI-CDMA, is proposed and investigated in impulsive noise that employs subcarrier interleaving (SI) to reduce the cross- correlation between the time-domain MC-CDMA waveforms and the impulsive noise. Computer simulation results conducted to support our analysis indicate that the proposed MC-SI- CDMA system in impulsive noise can provide a performance improvement of 2.5 dB at a bit error rate (BER) level of 10-3compared with the DS-CDMA system.

Selected mapping (SLM) is a technique used to reduce the peak-to-average power ratio (PAPR) in orthogonal frequency-division multiplexing (OFDM) systems. SLM requires the transmission of several side information bits for each data block, which results in some data rate loss. These bits must generally be channel-encoded because they are particularly critical to the error performance of the system. This increases the system complexity and transmission delay, and decreases the data rate even further. In this paper, we propose a novel SLM method for which no side information needs to be sent. By considering the example of several OFDM systems using either QPSK or 16-QAM modulation, we show that the proposed method performs very well both in terms of PAPR reduction and bit error rate at the receiver output provided that the number of subcarriers is large enough.

Selected mapping (SLM) is a technique used to reduce the peak-to-average power ratio (PAPR) in orthogonal frequency-division multiplexing (OFDM) systems. SLM requires the transmission of several side information bits for each data block, which results in some data rate loss. These bits must be channel-encoded because they are particularly critical to the error performance of the system. This increases the system complexity and transmission delay, and decreases the data rate even further. In this paper, we propose a novel SLM method for which no side information needs to be sent. By considering the example of several OFDM systems using either QPSK or 16-QAM modulation, we show that the proposed method performs very well in terms of bit error rate at the receiver output provided that the number of subcarriers is large enough.

Precoded spatial multiplexing multiple-input multiple-output (MIMO) systems using limited feedback have been extensively studied to reduce the feedback information based on the notion of delay-free feedback channel. In order to reduce performance degradation of precoded spatial multiplexing MIMO systems due to delay in the feedback channel, in this paper, we take into account the time varying nature of the channel, and consider the feedback delay problem. We propose the use of a linear predictor at the receiver to provide the precoder at the transmitter with predicted channel state information, and hence, mitigate the effect of feedback delay. The predictor is implemented using Kalman filter. The performance of this method is evaluated using computer simulation, and the achieved results demonstrate improved bit error rate performance in frequency selective Rayleigh fading channels.

Making distance measurements with RSS can be challenging in indoor environments. The effect of multipath and shadowing introduces ambiguity into the readings, leading to a range of distances that can be inferred from a single measurement. This contribution highlights the frequency dependancy of these effects. Lower and upper bounding constraints are introduced to achieve an practical operational range and mitigate the possibility of ambiguous RSS measurements. In the results section we verify our theoretical limits with practical based experimental results. We also highlight the gains in RMSE when our thresholding approach is transferred to a localisation scheme.

In wireless sensor networks, the use of energy efficient infrastructure such as clustering may be used to lengthen the network lifetime and prevent network connectivity degradation. In such systems, the performance of the clustering scheme is generally influenced by the cluster head selection method and the number of clusters. This paper presents a dynamic clustering method with multi-objectives that automatically determines the optimum number of clusters in the network. The algorithm, which is based on binary Particle Swarm Optimization (PSO), eliminates the need to set the number of clusters a priori. In addition, a multi-objective approach is utilized in the cluster head selection algorithm in order to select the best set of cluster heads. Simulation results demonstrate that the proposed protocol can achieve an optimal number of clusters, as well as prolong the network lifetime and increase the data delivery at the base station when compared to other well known clustering algorithms.

Selected mapping (SLM) is a well-known method for reducing the peak-to-average power ratio (PAPR) in orthogonal frequency-division multiplexing (OFDM) systems. The main drawback of this technique is that, for each data block, it requires the transmission of several side information bits, which results in some data rate loss. These redundant bits are so critical to the error performance of the system that they need in practice to be protected by a powerful channel code. This increases the system complexity and transmission delay, and decreases the data rate even further. In this paper, we propose a novel SLM method for which no side information needs to be sent. By considering the example of an OFDM system using 16-QAM modulation, it is shown that the proposed method performs very well both in terms of PAPR reduction and bit error rate at the receiver output.

In this paper, the performance of a downlink synchronous MC-CDMA system with joint frequency-time domain spreading over time-variant frequency-selective Rayleigh fading channels is investigated. We propose an adaptive two dimensional MMSE (minimum mean square error) receiver, which works in decision-directed model after the initial training period. Due to the time variability, a subcarrier phase tracker, which comprises a bank of phase locked-loops (PLLs), is employed in the proposed receiver to track the fading phase variability. Furthermore, a simplified phase tracker structure is proposed to reduce the complexity of system. The theoretical bit error rate (BER) is derived and simulation results indicate that the proposed receiver can achieve good frequency diversity and subcarrier synchronisation, compared to the conventional MCCDMA structures.

Selected mapping (SLM) is a well-known method for reducing the peak-to-average power ratio (PAPR) in orthogonal frequency-division multiplexing (OFDM) systems. The main drawback of this technique is that, for each data block, it requires the transmission of several side information bits, which results in some data rate loss. These redundant bits are so critical to the error performance of the system that they need in practice to be protected by a powerful channel code. This increases the system complexity and transmission delay, and decreases the data rate even further. In this paper, we propose a novel SLM method for which no side information needs to be sent. By considering the example of an OFDM system using 16-QAM modulation, it is shown that the proposed method performs very well both in terms of PAPR reduction and bit error rate at the receiver output.

Implementing positioning systems for indoor environments is notoriously difficult. The vast array of interacting parameters such as furniture, room shape and materials mean that the simulation of such an environment is of limited value. We present in this paper results from an empirical investigation as to the attainable accuracy of a Radio Frequency (RF) positioning system based on received signal strength (RSS). Methods to improve confidence, such as frequency averaging and bi-directional ranging, are explored. Finally we present and evaluate a novel method for calibrating the channel propagation exponent with no prior knowledge of the sensor network layout or room shape.

Clustering in wireless sensor networks (WSNs) is one of the techniques that can expand the lifetime of the whole network through data aggregation at the cluster head. This paper presents performance comparison between particle swarm optimization (PSO) and genetic algorithms (GA) with a new cost function that has the objective of simultaneously minimizing the intra-cluster distance and optimizing the energy consumption of the network. Furthermore, a comparison is made with the well known cluster-based protocols developed for WSNs, LEACH (low-energy adaptive clustering hierarchy) and LEACH-C, the later being an improved version of LEACH, as well as the traditional K-means clustering algorithm. Simulation results demonstrate that the proposed protocol using PSO algorithm has higher efficiency and can achieve better network lifetime and data delivery at the base station over its comparatives.

Wireless sensor networks (WSNs) are mainly characterized by their limited and non-replenishable energy supply. Hence, the need for energy efficient infrastructure is becoming increasingly more important since it impacts upon the network operational lifetime. Sensor node clustering is one of the techniques that can expand the lifespan of the whole network through data aggregation at the cluster head. In this paper, we present an energy-aware clustering for wireless sensor networks using particle swarm optimization (PSO) algorithm which is implemented at the base station. We define a new cost function, with the objective of simultaneously minimizing the intra-cluster distance and optimizing the energy consumption of the network. The performance of our protocol is compared with the well known cluster-based protocol developed for WSNs, LEACH (low-energy adaptive clustering hierarchy) and LEACH-C, the later being an improved version of LEACH. Simulation results demonstrate that our proposed protocol can achieve better network lifetime and data delivery at the base station over its comparatives.

The process of WIMAX radio network design and deployment is greatly affected by the nature of the customer premises equipment and the intended access service, which may be fixed, nomadic or indoor. This paper advances network design methodologies, traditionally used for fixed access, in the scope of hybrid fixed outdoor / indoor-nomadic networks. With the main objective being performance, time-to-market and cost optimisation, a dual layer outdoor / indoor coverage deployment is proposed which allows for co-existence and performance balancing of different customer profiles. By comparing to purely outdoor or indoor deployments, this approach provides benefits, both in terms of equipment reduction and spectrum usage and optimises the deployment costs, especially in the initial phases of the network. This approach is applicable both for OFDM and future OFDMA systems.

Mobile ad hoc networks in road transport applications exhibit special characteristics, mainly due to their dynamic chain behaviour. In this paper, we introduce a node decision algorithm in both the routing and packet priority mechanism, based on the node's driving direction with respect to the next hope towards packet destination. In the routing algorithm, a router direction index (RDI) parameter is introduced to enhance the performance of AODV in updating its routing table, as well as to assist the destination nodes to choose route requests from different paths in inter-vehicular ad hoc network scenarios. A packet transmission priority is set according to the driving direction of both transmitter and receiver of the packet. Simulation results of the proposed algorithm for 200 vehicles travelling at speeds between 60 ~ 120 km/h on a 2-directional highway demonstrate a performance increase in the packet delivery ratio, and decrease in the packet end to end delay and routing overhead for the proposed algorithm

In this paper, iterative detection is applied in the receiver for downlink of both direct sequence (DS) and multi-carrier (MC) code division multiple access (CDMA) systems in the flat Rayleigh fading channels. A joint iterative detection and phase recovery scheme is proposed. Unlike the conventional bit-interleaved coded modulation with iterative decoding (BICM-ID) structure, the proposed receiver feeds the extrinsic information from soft-input soft-output (SISO) decoder back to update both the adaptive minimum mean squared error (MMSE) correlator and phase locked-loop (PLL) instead of de-mapper. We also investigate how the second-order PLL benefits from the iterative process over the time-varying flat Rayleigh fading channel. Simulation results illustrate that the iterative process significantly improves the performance of the adaptive detector by suppressing multiple access interference (MAI). Additionally, the tracking capability of PLL is enhanced by reducing the equivalent noise power.

This paper introduces a new technique for combining constellation shaping and bit-interleaved turbo-coded modulation (BITCM) over additive white Gaussian noise channel. The proposed scheme consists of serial concatenation of a binary turbo code, short-length binary shaping code, and mapping function using Gray labeling. The corresponding receiver is made up of four blocks (demapper, shaping decoder, and two constituent RSC decoders) exchanging extrinsic information in order to optimize error performance. A BITCM scheme employing 16-PAM constellation to achieve a rate of 3 bits/dim is considered as an example. It is shown that, by careful selection of the shaping code parameters, shaping gains almost equal to 0.8 dB can be obtained at a little cost in terms of system complexity.

In this paper, a new adaptive, closed-loop power control algorithm is proposed for wideband code-division-multiple-access (W-CDMA) communication systems. The adjustment of power is carried out through knowledge of the past values of signal strength and signal-to-interference ratio (SIR). The gradient nature of Rayleigh fading channel is estimated in order to alleviate the effect of fast fading and to enable the channel to be tracked more effectively, hence providing stable received signal power and SIR for each user. Simulation results show that the proposed algorithm has superior convergence performance compared to existing approaches

In this paper, the performance of a computationally efficient adaptive MMSE receiver is investigated for asynchronous MC-CDMA systems over multipath fading channels. According to Wiener filter and LMS algorithm theories, we prove that the proposed computationally efficient MMSE receiver has the same BER and convergence performance as that of the conventional MMSE receiver, assuming the sampling rate per symbol is equal to the number of subcarriers. When the sampling rate per symbol is increased, the proposed receiver can outperform the conventional MMSE receiver without sacrificing the convergence speed. The theoretical analysis is verified by the results through Monte-Carlo simulation

We investigate the association between constellation shaping and bit-interleaved coded modulation with iterative decoding (BICM-ID). To this end, we consider a technique which consists of inserting shaping block codes between mapping and channel coding functions in order to achieve constellation shaping. By assuming the example of a 2-bit/s/Hz 16-QAM BICM-ID, it is demonstrated using computer simulations that this technique can improve the performance of BICM-ID schemes by a few tenths of decibels.

A linear transmitter precoding technique based on partial equalization receiver (TP-PER) is proposed for time-duplex division (TDD) downlink multi-carrier code-division multiple-access (MC-CDMA) systems to pre-suppress multiple access interference (MAI) in frequency selective Rayleigh fading channels. Given that the channel state information (CSI) is known to the transmitter and the channel is slowly varying, the proposed transmitter precoding algorithm can outperform conventional precoding schemes, such as transmitter precoding with equal gain combining (TP-EGC), transmitter precoding with maximum ratio combining (TP-MRC), and the linear equalization receiver. Numerical results show that the proposed algorithm achieves optimal performance by using an appropriate partial equalization factor that depends on the system specification

An Adaptive minimum bit error rate (MBER) based linear multiuser detection scheme is proposed for an asynchronous multicarrier code-division multiple-access (MC-CDMA) system in frequency selective Rayleigh fading channels. In general, a MC-CDMA system employs the minimum mean square error (MMSE) receiver due to its good performance and amenability to adaptive implementation. However, the MSE cost function is nut optimal in terms of the bit error probability performance of the system. The proposed multiuser detector (MUD) that directly minimizes the BER can significantly improve the performance by employing an adaptive stochastic gradient algorithm based on the estimation of kernel density function in order to adjust the weights in the receiver. Simulation results demonstrate a clear performance improvement by using the proposed multiuser detection scheme.