This paper explores the application of uplink fronthaul compression techniques within Open RAN (ORAN) to mitigate fronthaul load in decentralized distributed MIMO (DD-MIMO) systems. With the ever-increasing demand for high data rates and system scalability, the fronthaul load becomes a critical bottleneck. Our method uses ORAN compression techniques to efficiently compress the fronthaul signals. The goal is to greatly lower the fronthaul load while having little effect on the overall system performance, as shown by Block Error Rate (BLER) curves. Through rigorous link-level simulations, we compare our quantization strategies against a benchmark scenario with no quantization, providing insights into the trade-offs between fronthaul data rate reduction and link performance integrity. The results demonstrate that our proposed quantization techniques not only lower the fronthaul load but also maintain a competitive link quality, making them a viable solution for enhancing the efficiency of next-generation wireless networks. This study underscores the potential of quantization in O-RAN contexts to achieve optimal balance between system capacity and performance, paving the way for more scalable and robust DD-MIMO deployments.

Effective channel estimation (CE) is critical for optimizing the performance of 5G New Radio (NR) systems, particularly in dynamic environments where traditional methods struggle with complexity and adaptability. This paper introduces GraphNet, a novel, lightweight Graph Neural Network (GNN)-based estimator designed to enhance CE in 5G NR. Our proposed method utilizes a GNN architecture that minimizes computational overhead while capturing essential features necessary for accurate CE. We evaluate GraphNet across various channel conditions, from slow-varying to highly dynamic environments, and compare its performance to ChannelNet, a well-known deep learning-based CE method. GraphNet not only matches ChannelNet’s performance in stable conditions but significantly outperforms it in high-variation scenarios, particularly in terms of Block Error Rate. It also includes built-in noise estimation that enhances robustness in challenging channel conditions. Furthermore, its significantly lighter computational footprint makes GraphNet highly suitable for real-time deployment, especially on edge devices with limited computational resources. By underscoring the potential of GNNs to transform CE processes, GraphNet offers a scalable and robust solution that aligns with the evolving demands of 5G technologies, highlighting its efficiency and performance as a next-generation solution for wireless communication systems.

The advent of 5G networks necessitates more flexible and intelligent architectures, prompting a shift from conventional models to Open Radio Access Networks (0-RAN) augmented with integrated network slicing (NS). The combination of O-RAN with a cell-free architecture improves both coverage and performance, while NS facilitates dynamic resource allocation to support diverse services, such as ultra-reliable low-latency communications (uRLLC) and enhanced mobile broadband (eMBB). This paper introduces a novel NS-enabled, cell-free O-RAN framework designed to optimize resource allocation and power control. In contrast to traditional methods, we adopt a Deep Reinforcement Learning (DRL) approach, leveraging the Soft Actor-Critic (SAC) algorithm to dynamically allocate power and resources across distributed access points (APs), while simultaneously ensuring the efficient management of network slices. The proposed framework aims to maximize the number of admitted slices while minimizing network costs, ensuring optimal data rates for eMBB and low latency for uRLLC services. Through this approach, we demonstrate enhanced flexibility, scalability, and performance in dynamic 5G wireless environments.

This paper explores the vulnerability of downlink cell-free massive MIMO systems to passive and active eaves-dropping, focusing on a 5G New Radio framework. To enhance the security of downlink transmissions over the Physical Downlink Shared Channel (PDSCH) against eavesdropping threats, we propose two novel methods based on cooperative artificial noise (AN). The first approach, called cooperative artificial noise (CAN), involves all access points (APs) broadcasting AN in the null space of the users' channel matrix to confuse potential eavesdroppers. The second approach, named partial artificial noise (PAN), divides the APs into two groups: one group cooperatively transmits AN, while the other group serves the legitimate users. Additionally, we implement three different precoding schemes for legitimate users: maximum ratio transmission, zero-forcing, and minimum mean square error. We conduct link-level simulations of wiretap channels under various frequency-selective fading scenarios and noise conditions, using tapped delay line channel models as defined by the 3GPP TR 38.901 standard. The system's security performance is evaluated by analyzing the block error rate of legitimate users and the block success rate of eavesdroppers. Despite the limitation of having only one antenna per access point, our findings demonstrate that AN can be strategically designed through the cooperation of APs. By designing appropriate groups of APs specifically for generating AN, our second approach, PAN, significantly reduces the block successive rate of eavesdroppers, lowering it from 0.2 without AN to 0.1 with CAN and further down to 0.025 with PAN.

We consider a decentralized distributed massive MIMO (DD-mMIMO) system with limited fronthaul capacity. This is a novel architecture of scalable cell-free massive MIMO (CF-mMIMO). In previous studies, the input signal of the quantizer in CF-mMIMO has been assumed to follow the Gaussian distribution based on the central limit theorem. However, this assumption may not hold when the number of variables is not large. In this paper, we derive the probability distribution function (pdf) for the sum of many products of two Gaussian-distributed variables plus an additional Gaussian-distributed variable. Using the actual pdf, we derive closed-form Bussgang decomposition coefficients and determine the optimum step interval by solving a maximization problem. Additionally, we derive an expression for the spectral efficiency (SE) under quantization. Our results indicate that the Gaussian distribution can be appropriately applied in Bussgang decomposition when the number of quantization bits is limited. However, there exists a 7.8% gap between the Gaussian method and our proposed Non-Gaussian method in terms of mean square error of channel estimates when using 8-bit quantization. Furthermore, the SE is significantly influenced by the choice of the number of quantization bits.

This paper contributes by providing a comprehensive set of block error rate (BLER) vs. signal-to-noise ratio (SNR) curves under additive white Gaussian noise (AWGN) channel conditions for 5G new radio (NR) modulation and coding schemes (MCS) belonging to the 3GPP 5G NR TS 38.214 standard, with low-density parity check (LDPC) coded scenario according to TS 38.212. To enhance practical relevance in the context of O-RAN networks, this paper also introduces the effect of optimum quantization and compares the results without quantization, showing that despite system degradation, the performance remains very close to the unquantized case. By providing this comprehensive dataset, the paper offers valuable insights to support the selection of the most appropriate MCS depending on the required BLER-SNR scenario, serving as a guide in the design of 5G communication systems, for the scheduler, and as lookup tables for the physical layer (PHY) abstraction in link-level simulators (LLS).

A fine-grained analysis of the cache-enabled networks is crucial for system design. In this paper, we focus on the meta distribution of the signal-to-interference ratio for the cache-enabled networks where the locations of the base stations are modeled as a Poisson point process. With the application of the random caching and the random discontinuous transmission schemes, we derive the moments of the conditional successful transmission probability, the exact meta distribution and its beta approximation by utilizing stochastic geometry. The closed-form expressions of the mean and variance of the local delay (i.e., the jitter) are also derived. We then consider the maximization of the mean successful transmission probability and the minimization of the average system transmission delay by jointly optimizing the caching probability and the BS active probability. Finally, the numerical results demonstrate the superiority of the proposed optimization schemes over the existing caching strategies and reveal the impacts of the key network parameters on the cache-enabled networks in terms of successful transmission probability, successful transmission probability variance, meta distribution, mean local delay and jitter.

This paper investigates the performance of limited-fronthaul cell-free massive multiple-input multiple-output (MIMO) taking account the fronthaul quantization and imperfect channel acquisition. Three cases are studied, which we refer to as Estimate & Quantize, Quantize & Estimate, and Decentralized, according to where channel estimation is performed and exploited. Maximum-ratio combining (MRC), zero-forcing (ZF), and minimum mean-square error (MMSE) receivers are considered. The Max algorithm and the Bussgang decomposition are exploited to model optimum uniform quantization. Exploiting the optimal step size of the quantizer, analytical expressions for spectral and energy efficiencies are presented. Finally, an access point (AP) assignment algorithm is proposed to improve the performance of the decentralized scheme. Numerical results investigate the performance gap between limited fronthaul and perfect fronthaul cases, and demonstrate that exploiting relatively few quantization bits, the performance of limited-fronthaul cell-free massive MIMO closely approaches the perfect-fronthaul performance.

The uplink of a reconfigurable intelligent surfaces (RIS)-aided cell-free massive multiple-input multiple-output (MIMO) system is analyzed, where the channel state information (CSI) is estimated using uplink pilots. First, we derive analytical expressions for the achievable rate of the system with zero forcing (ZF) receiver, taking into account the effects of pilot contamination, channel estimation error and the distributed RISs. The max-min rate optimization problem is considered with per-user power constraints. To solve this non-convex problem, we propose to decouple the original optimization problem into two sub-problems, namely, phase shift design problem and power allocation problem. The power allocation problem is solved using a standard geometric programming (GP) whereas a semidefinite programming (SDP) is utilized to design the phase shifts. Moreover, the Taylor series approximation is used to convert the nonconvex constraints into a convex form. An iterative algorithm is proposed whereby at each iteration, one of the sub-problems is solved while the other design variable is fixed. The max-min user rate of the RIS-aided cell-free massive MIMO system is compared to that of conventional cell-free massive MIMO. Numerical results indicate the superiority of the proposed algorithm compared with a conventional cell-free massive MIMO system. Finally, the convergence of the proposed algorithm is investigated.

We consider a cell-free massive multiple-input multiple-output (MIMO) system where the channel estimates and the received signals are quantized at the access points (APs) and forwarded to a central processing unit (CPU). Zero-forcing technique is used at the CPU to detect the signals transmitted from all users. To solve the non-convex sum rate maximization problem, a heuristic sub-optimal scheme is proposed to convert the problem into a geometric programme (GP). Exploiting a deep convolutional neural network (DCNN) allows us to determine both a mapping from the large-scale fading (LSF) coefficients and the optimal power by solving the optimization problem using the quantized channel. Depending on how the optimization problem is solved, different power control schemes are investigated; i) small-scale fading (SSF)-based power control; ii) LSF use-and-then-forget (UatF)-based power control; and iii) LSF deep learning (DL)-based power control. The SSF-based power control scheme needs to be solved for each coherence interval of the SSF, which is practically impossible in real time systems. Numerical results reveal that the proposed LSF-DL-based scheme significantly increases the performance compared to the practical and well-known LSF-UatF-based power control.

This paper investigates a secrecy energy efficiency (SEE) optimization problem for a multiple-input multiple-output non-orthogonal multiple access network. In particular, a multi-antenna transmitter intends to send two integrated service messages: a confidential message for the stronger user and a broadcast message for both stronger and weaker users. It is assumed that both users are equipped with multi-antennas. In this secure wireless network, we consider the transmit covariance matrices design of confidential and broadcast message, under broadcast energy efficiency (BEE) constraint. In addition, it is assumed that the weaker user might turn out to be a potential eavesdropper due to the broadcast nature of wireless transmission. We formulate this transmit covariance matrices design as an SEE maximization problem which is non-convex in its original form due the non-linear fractional objective function and constraints. To realize the solution for this problem, we utilize non-linear fractional programming and difference of concave (DC) functions approach which facilitate to reformulate it into a tractable form. Based on the Dinkelbach's algorithm and DC approximation method, we propose iterative algorithms to determine a solution to the original SEE maximization problem. Numerical results are provided to demonstrate the performance of the proposed transmit covariance matrices design to maximize the SEE.

A cell-free massive multiple-input multiple-output (MIMO) uplink is considered, where quantize-and-forward (QF) refers to the case where both the channel estimates and the received signals are quantized at the access points (APs) and forwarded to a central processing unit (CPU) whereas in combine-quantize-and-forward (CQF), the APs send the quantized version of the combined signal to the CPU. To solve the non-convex sum rate maximization problem, a heuristic sub-optimal scheme is exploited to convert the power allocation problem into a standard geometric programme (GP). We exploit the knowledge of the channel statistics to design the power elements. Employing large-scale-fading (LSF) with a deep convolutional neural network (DCNN) enables us to determine a mapping from the LSF coefficients and the optimal power through solving the sum rate maximization problem using the quantized channel. Four possible power control schemes are studied, which we refer to as i) small-scale fading (SSF)-based QF; ii) LSF-based CQF; iii) LSF use-and-then-forget (UatF)-based QF; and iv) LSF deep learning (DL)-based QF, according to where channel estimation is performed and exploited and how the optimization problem is solved. Numerical results show that for the same fronthaul rate, the throughput significantly increases thanks to the mapping obtained using DCNN.

The downlink (DL) of a non-orthogonal-multiple-access (NOMA)-based cell-free massive multiple-input multiple-output (MIMO) system is analyzed, where the channel state information (CSI) is estimated using pilots. It is assumed that the users are grouped into multiple clusters. The same pilot sequences are assigned to the users within the same clusters whereas the pilots allocated to all clusters are mutually orthogonal. First, a user's bandwidth efficiency (BE) is derived based on his/her channel statistics under the assumption of employing successive interference cancellation (SIC) at the users' end with no DL training. Next, the classic max-min optimization framework is invoked for maximizing the minimum BE of a user under per-access point (AP) power constraints. The max-min user BE of NOMA-based cell-free massive MIMO is compared to that of its orthogonal multiple-access (OMA) counter part, where all users employ orthogonal pilots. Finally, our numerical results are presented and an operating mode switching scheme is proposed based on the average per-user BE of the system, where the mode set is given by Mode = { OMA, NOMA }. Our numerical results confirm that the switching point between the NOMA and OMA modes depends both on the length of the channel's coherence time and on the total number of users.

Energy efficiency (EE) and spectral efficiency (SE) are two of the key performance metrics in future wireless networks, covering both design and operational requirements. For previous conventional resource allocation techniques, these two performance metrics have been considered in isolation, resulting in severe performance degradation in either of these metrics. Motivated by this problem, in this paper, we propose a novel beamforming design that jointly considers the trade-off between the two performance metrics in a multiple-input single-output non-orthogonal multiple access system. In particular, we formulate a joint SE-EE based design as a multi-objective optimization (MOO) problem to achieve a good trade-off between the two performance metrics. However, this MOO problem is not mathematically tractable and, thus, it is difficult to determine a feasible solution due to the conflicting objectives, where both need to be simultaneously optimized. To overcome this issue, we exploit a priori articulation scheme combined with the weighted sum approach. Using this, we reformulate the original MOO problem as a conventional single objective optimization (SOO) problem. In doing so, we develop an iterative algorithm to solve this non-convex SOO problem using the sequential convex approximation technique. Simulation results are provided to demonstrate the advantages and effectiveness of the proposed approach over the available beamforming designs.

In this paper, we investigate energy harvesting capabilities of non-orthogonal multiple access (NOMA) scheme integrated with the conventional time division multiple access (TDMA) scheme, which is referred to as hybrid TDMA-NOMA system. In a such hybrid scheme, users are divided into a number of groups, with the total time allocated for transmission is shared between these groups through multiple time slots. In particular, a time slot is assigned to serve each group, whereas the users in the corresponding group are served based on power-domain NOMA technique. Furthermore, simultaneous wireless power and information transfer technique is utilized to simultaneously harvest energy and decode information at each user. Therefore, each user splits the received signal into two parts, namely, energy harvesting part and information decoding part. In particular, we jointly determine the power allocation and power splitting ratios for all users to minimize the transmit power under minimum rate and minimum energy harvesting requirements at each user. Furthermore, this joint design is a non-convex problem in nature. Hence, we employ successive interference cancellation to overcome these non- convexity issues and determine the design parameters (i.e., the power allocations and the power splitting ratios). In simulation results, we demonstrate the performance of the proposed hybrid TDMA-NOMA design and show that it outperforms the conventional TDMA scheme in terms of transmit power consumption.

In this paper, non-orthogonal-multiple-access (NOMA)-based cell-free massive multiple-input multiple-output (MIMO) is investigated, where the users are grouped into multiple clusters. Exploiting conjugate beamforming, the bandwidth efficiency (BE) of the system is derived while the assumption that the users performing realistic successive interference cancellation (SIC) based on only the knowledge of channel statistics. The max-min fairness problem of maximizing the lowest user BE is investigated and an iterative bisection method is developed to determine the optimal solution to the max-min BE problem. Numerical results are presented for validating the proposed design's performance, and a mode switching scheme is conceived for selecting a specific Mode = {OMA, NOMA} that maximizes the system's BE.

We investigate the energy efficiency performance of cell-free Massive multiple-input multiple-output (MIMO), where the access points (APs) are connected to a central processing unit (CPU) via limited-capacity links. Thanks to the distributed maximum ratio combining (MRC) weighting at the APs, we propose that only the quantized version of the weighted signals are sent back to the CPU. Considering the effects of channel estimation errors and using the Bussgang theorem to model the quantization errors, an energy efficiency maximization problem is formulated with per-user power and backhaul capacity constraints as well as with throughput requirement constraints. To handle this non-convex optimization problem, we decompose the original problem into two sub-problems and exploit a successive convex approximation (SCA) to solve original energy efficiency maximization problem. Numerical results confirm the superiority of the proposed optimization scheme.

In this paper, we propose two beamforming designs for a multiple-input single-output non-orthogonal multiple access system considering the energy efficiency (EE) fairness between users. In particular, two quantitative fairness-based designs are developed to maintain fairness between the users in terms of achieved EE: max-min energy efficiency (MMEE) and proportional fairness (PF) designs. While the MMEE-based design aims to maximize the minimum EE of the users in the system, the PF-based design aims to seek a good balance between the global energy efficiency of the system and the EE fairness between the users. Detailed simulation results indicate that our proposed designs offer many-fold EE improvements over the existing energy-efficient beamforming designs.

In this paper, we propose a beamforming design that jointly considers two conflicting performance metrics, namely the sum rate and fairness, for a multiple-input single-output non-orthogonal multiple access system. Unlike the conventional rate-aware beamforming designs, the proposed approach has the flexibility to assign different weights to the objectives (i.e., sum rate and fairness) according to the network requirements and the channel conditions. In particular, the proposed design is first formulated as a multi-objective optimization problem, and subsequently mapped to a single objective optimization (SOO) problem by exploiting the weighted sum approach combined with a prior articulation method. As the resulting SOO problem is non-convex, we use the sequential convex approximation technique, which introduces multiple slack variables, to solve the overall problem. Simulation results are provided to demonstrate the performance and the effectiveness of the proposed approach along with detailed comparisons with conventional rate-aware-based beamforming designs.

In this paper, we evaluate iterative interference cancellation (IIC) as a method to remove the intrinsic interference terms in filter bank multicarrier - quadrature amplitude modulation (FBMC-QAM) systems. We propose an IIC receiver that separates the received signal into even- and odd-numbered subcarrier components and use the demodulated even- and odd-numbered subcarrier symbols to iteratively remove the effect of interference. Numerical results show that the out-of-band emission performance of the IIC FBMC-QAM system is superior to that of OFDM and conventional FBMC-QAM. Bit error rate (BER) simulation results also indicate that the proposed IIC FBMC-QAM can effectively improve BER performance under different time-varying channels.

The availability and accuracy of Channel State Information (CSI) play a crucial role for coherent detection in almost every communication system. Particularly in the recently proposed cell-free massive MIMO system, in which a large number of distributed Access Points (APs) is connected to a Central processing Unit (CPU) for joint decoding, acquiring CSI at the CPU may improve performance through the use of detection algorithms such as minimum mean square error (MMSE) or zero forcing (ZF). There are also significant challenges, especially the increase in fronthaul load arising from the transfer of high precision CSI, with the resulting complexity and scalability issues. In this paper, we address these CSI acquisition problems by utilizing vector quantization with precision of only a few bits and we show that the accuracy of the channel estimate at the CPU can be increased by exploiting the spatial correlation subject to this limited fronthaul load. Further, we derive an estimator for the simple Quantize-and-Estimate (QE) strategy based on the Bussgang theorem and compare its performance to Estimate-and-Quantize (EQ) in terms of Mean Squared Error (MSE). Our simulation results indicate that the QE with few-bit vector quantization can outperform EQ and individual scalar quantization at moderate SNR for small numbers of bits per dimension.

As a novel wireless network architecture, cloud radio access network (C-RAN) can significantly reduce the cost of operations and maintenance as well as providing lower power consumption and higher spectral efficiency. However, the huge load on the fronthaul network which connects the baseband unit (BBU) and the large number of remote radio heads (RRHs) is a significant challenge. To reduce the fronthaul load, this paper proposes a data compression and recovery scheme based on compressive sensing (CS) for the uplink C-RAN scenario. The numerical results show that proposed compression scheme can be effectively applied to the uplink of a cell-free C-RAN system.

Non‐orthogonal multiple access (NOMA) makes multiple users to overload the same wireless resources by utilising the superposition coding principle, so that NOMA can improve the system capacity and spectral efficiency. Therefore, NOMA has recently received considerable attention as a promising candidate to address some of the challenges for 5G. Various NOMA schemes including the power‐domain NOMA (PD‐NOMA) are proposed, and successive interference cancellation (SIC) is applied for detection, which limits the promised performance gain brought by NOMA due to the error propagation. In this study, the authors introduce an iterative interference cancellation (IIC) detection scheme for uplink PD‐NOMA system by using parallel interference cancellation (PIC) scheme. The interleave division multiple access is also employed for improving system performance. A new detection scheme based on IIC is proposed, which is called advanced IIC (AIIC). The simulation results show that the bit error rate performance of AIIC is much better than that of SIC, and is close to that of maximum a posteriori. The AIIC can obtain the promised performance gain brought by NOMA.

When considering the future generation wireless networks, non-orthogonal multiple access (NOMA) represents a viable multiple access technique for improving the spectral efficiency. The basic performance of the NOMA is often enhanced using downlink beamforming and power allocation techniques. Although downlink beamforming has been previously studied with different performance criteria, such as sum-rate and max-min rate, it has not been studied in the multiuser, multiple-input single-output (MISO) case, particularly with the energy efficiency criteria. In this paper, we investigate the design of an energy efficient beamforming technique for downlink transmission in the context of a multiuser MISO-NOMA system. In particular, this beamforming design is formulated as a global energy efficiency (GEE) maximization problem with minimum user rate requirements and transmit power constraints. By using the sequential convex approximation technique and the Dinkelbach's algorithm to handle the non-convex nature of the GEE-Max problem, we propose two novel algorithms for solving the downlink beamforming problem for the MISO-NOMA system. Our evaluation of the proposed algorithms shows that they offer similar optimal designs and are effective in offering substantial energy efficiencies compared with the designs based on conventional methods.

Cell-free massive multiple-input-multiple-output (MIMO) is considered, where distributed access points (APs) multiply the received signal by the conjugate of the estimated channel, and send back a quantized version of this weighted signal to a central processing unit (CPU). For the first time, we present a performance comparison between the case of perfect fronthaul links, the case when the quantized version of the estimated channel and the quantized signal are available at the CPU, and the case when only the quantized weighted signal is available at the CPU. The Bussgang decomposition is used to model the effect of quantization. The max-min problem is studied, where the minimum rate is maximized with the power and fronthaul capacity constraints. To deal with the non-convex problem, the original problem is decomposed into two sub-problems (referred to as receiver filter design and power allocation). Geometric programming (GP) is exploited to solve the power allocation problem whereas a generalized eigenvalue problem is solved to design the receiver filter. An iterative scheme is developed and the optimality of the proposed algorithm is proved through uplink-downlink duality. A user assignment algorithm is proposed which significantly improves the performance. The numerical results demonstrate the superiority of the proposed schemes.

Physical layer network coding (PNC) has been studied to serve wireless network MIMO systems with much lower backhaul load than approaches such as Cloud Radio Access Network (Cloud-RAN) and coordinated multipoint (CoMP). In this paper, we present a design guideline of engineering applicable PNC to fulfil the request of high user densities in 5G wireless RAN infrastructure. We show that the proposed design criteria guarantee that: 1) the whole system operates over binary system; 2) the PNC functions utilized at each access point overcome all singular fade states; and 3) the destination can unambiguously recover all source messages, while the overall backhaul load remains at the lowest level. We then develop a two-stage search algorithm to identify the optimum PNC mapping functions which greatly reduces the real-time computational complexity. The impact of estimated channel information and reduced number of singular fade states in different QAM modulation schemes are studied in this paper. Numerical results show that the proposed schemes achieve low outage probability with reduced backhaul load.

A cell-free massive multiple-input multiple-output system is considered using a max-min approach to maximize the minimum user rate with per-user power constraints. First, an approximated uplink user rate is derived based on channel statistics. Then, the original max-min signal-to-interference-plus-noise ratio problem is formulated for the optimization of receiver filter coefficients at a central processing unit and user power allocation. To solve this max-min non-convex problem, we decouple the original problem into two sub-problems, namely, receiver filter coefficient design and power allocation. The receiver filter coefficient design is formulated as a generalized Eigenvalue problem, whereas the geometric programming (GP) is used to solve the user power allocation problem. Based on these two sub-problems, an iterative algorithm is proposed, in which both problems are alternately solved while one of the design variables is fixed. This iterative algorithm obtains a globally optimum solution, whose optimality is proved through establishing an uplink-downlink duality. Moreover, we present a novel sub-optimal scheme which provides a GP formulation to efficiently and globally maximize the minimum uplink user rate. The numerical results demonstrate that the proposed scheme substantially outperforms the existing schemes in the literature.

This paper presents a physical layer network coding (PNC) approach for network MIMO (N-MIMO) systems to release the heavy burden of backhaul load. The proposed PNC approach is applied for uplink scenario in binary systems, and the design guideline serves multiple mobile terminals (MTs) and guarantees unambiguous recovery of the message from each MT. We present a novel PNC design criterion first based on binary matrix theories, followed by an adaptive optimal mapping selection algorithm based on the proposed design criterion. In order to reduce the real-time computational complexity, a two-stage search algorithm for the optimal binary PNC mapping matrix is developed. Numerical results show that the proposed scheme achieves lower outage probability with reduced backhaul load compared to practical CoMP schemes which quantize the estimated symbols from a log-likelihood ratio (LLR) based multiuser detector into binary bits at each access point(AP).

In this paper, we consider the max-min signal-to- interference plus noise ratio (SINR) problem for the uplink transmission of a cell-free Massive multiple-input multiple-output (MIMO) system. Assuming that the central processing unit (CPU) and the users exploit only the knowledge of the channel statistics, we first derive a closed-form expression for uplink rate. In particular, we enhance (or maximize) user fairness by solving the max-min optimization problem for user rate, by power allocation and choice of receiver coefficients, where the minimum uplink rate of the users is maximized with available transmit power at the particular user. Based on the derived closed-form expression for the uplink rate, we formulate the original user max-min problem to design the optimal receiver coefficients and user power allocations. However, this max-min SINR problem is not jointly convex in terms of design variables and therefore we decompose this original problem into two sub- problems, namely, receiver coefficient design and user power allocation. By iteratively solving these sub-problems, we develop an iterative algorithm to obtain the optimal receiver coefficient and user power allocations. In particular, the receiver coefficients design for a fixed user power allocation is formulated as generalized eigenvalue problem whereas a geometric programming (GP) approach is utilized to solve the power allocation problem for a given set of receiver coefficients. Numerical results confirm a three-fold increase in system rate over existing schemes in the literature.

We consider a cell-free Massive multiple-input multiple-output (MIMO) system and investigate the system performance for the case when the quantized version of the estimated channel and the quantized received signal are available at the central processing unit (CPU), and the case when only the quantized version of the combined signal with maximum ratio combining (MRC) detector is available at the CPU. Next, we study the max-min optimization problem, where the minimum user uplink rate is maximized with backhaul capacity constraints. To deal with the max-min non-convex problem, we propose to decompose the original problem into two sub-problems. Based on these sub- problems, we develop an iterative scheme which solves the original max-min user uplink rate. Moreover, we present a user assignment algorithm to further improve the performance of cell-free Massive MIMO with limited backhaul links.

This work investigates the performance of user-centric joint transmission coordinated multipoint (JT-CoMP) clustering in a control/data decoupled cell-less architecture taking radio resource assignment into account. In CoMP networks, a trade-off exists between signal to interference noise ratio (SINR) gain and loss of radio resources. To achieve a balance between SINR gain and loss of radio resources, it is essential to find an optimal power level difference (PLD) value that can identify the number of users that can operate under a CoMP mode. Also, CoMP requires a proper radio resource management approach that can support the resource assignment from multiple base stations (BSs). In this paper, we study the effect of choosing a PLD value on the per-user throughput of CoMP and non-CoMP users. Also, we provide a radio resource management scheme that can support a CoMP cell-less architecture. Simulation results demonstrated that a PLD value of 5 dB can provide a good balance between SINR gain and loss of radio resources. Also, efficient radio resource scheduling improves the throughput of 65% of non-CoMP users and 35% of CoMP users when the PLD value is 5 dB.

We consider cooperative radio access network architectures, especially distributed massive MIMO and Cloud RAN, considering their similarities and differences. We address in particular the major challenge posed to both by the implementation of a high capacity fronthaul network to link the distributed access points to the central processing unit, and consider the effect on uplink performance of quantization of received signals in order to limit fronthaul load. We use the Bussgang decomposition along with a new approach to MMSE estimation of both channel and data to provide the basis of our analysis.

Iterative decoding has been widely used to achieve reliable high data rate transmission for broadband multi-carriers communication systems. However, in Multiple-Input Multiple-Output Orthogonal Frequency Division Multiplexing (MIMO-OFDM) systems with insufficient cyclic prefix (CP), there are significant challenges for efficient receiver design under the effect of the time-variant Long-Term Evolution (LTE) multipath channel. It means that the system performance may be degraded due to the inter-symbol interference (ISI) and inter-carrier interference (ICI) resulting from other transmitted signals. In this work, iterative interference cancellation (IIC) and MIMO-IIC with linear and successive interference cancellation (SIC) detection schemes are proposed using a Low-Density Parity-Check (LDPC) decoder for MIMO filter bank multicarrier/offset QAM (MIMO-FBMC/OQAM) and MIMO-OFDM systems. IIC and MIMO-IIC are used to calculate the ICI/ISI components from the estimated decoded signals and remove them from the received signals. SIC is used to reduce the cross interference from the other antenna. The bit error probability is compared with that of the MIMO-OFDM system with insufficient cyclic prefix (CP) under different environments. The results obtained indicate that IIC and MIMO-IIC can effectively mitigate error floors introduced by channel variation and insufficient CP with high bandwidth efficiency. With SIC detection, a second order diversity is approximately achieved.

Recently, non-orthogonal multiple access (NOMA) has received considerable attention as a promising candidate for 5G systems. In this paper, a robust beamforming approach is investigated for NOMA based multiple-input single-output (MISO) downlink transmission. We consider an outage probability based robust scheme by incorporating channel uncertainties, where the total transmit power is minimized while satisfying these outage constraints at each user. Although the original problem is non-convex in terms of beamforming vectors, an intractable optimization problem is reformulated with a linear matrix inequality (LMI) form by exploiting semidefinite relaxation (SDR) technique. Finally, simulation results have been provided to validate the performance of the proposed robust design, where these results confirm that the robust scheme outperforms the non-robust scheme in terms of the rate satisfaction ratio at each user.

Compute-and-Forward (C&F) has been proved to be an efficient approach for multiuser, multihop wireless networks. It allows intermediate relays to infer and forward linear combinations of the transmitted messages, in order to achieve high computation rate. The coefficient selection for each relay is a shortest vector problem (SVP). The most common solutions for such a problem are exhaustive search and the Lenstra-LenstraLovsz (LLL) lattice reduction. The former has a high complexity and the latter proves to be suboptimal for large numbers of users. In this paper, we propose two novel algorithms, of which one can be regarded as a simplified version of the exhaustive search, while the other one selects the coefficients iteratively. Numerical results reveal that both methods achieve the same computation rate as the exhaustive search with much lower complexity. Both outperform the LLL algorithm (especially with a large number of users), and the complexities are lower than the LLL except in the very high SNR region.

In this paper iterative interference cancellation (IC) is introduced to eliminate the inherent intersymbol interference (ISI) and intercarrier interference (ICI) terms in filter bank multicarrier/offset quadrature amplitude modulation (FBMC/OQAM). An iterative interference cancellation receiver is proposed using a Low-Density Parity-Check (LDPC) decoder with a maximum likelihood (ML) detector. Different channel conditions for different environments are simulated. Bit error probability is compared with the conventional FFT-OFDM system for LTE multipath channels. The obtained results show that the probability of error in the FBMC/OQAM scheme is improved in many scenarios with a noticeable increase in the system complexity.

This paper introduces promising millimetre wave backhaul deployment options that serve an ultra-dense outdoor radio access network installed on street-level fixtures. A backhaul architecture which is based on either Cloud-RAN (C-RAN) or Distributed-RAN (D-RAN) configuration is introduced. We investigate the advantages and disadvantages of utilising millimetre wave in bands 71-76 and 81-86 GHz and free space optics (FSO) to fronthaul/backhaul links. As an initial study, the proposed architecture based on D-RAN is applied to a dense urban city area where moving vehicles and other users are served mixed traffic, including high resolution on demand and real time video. The analysis shows that the unevenly distributed traffic caused by different user types and mobility requires that the location and number of backhaul links need to be carefully designed to overcome the problems of bottlenecks on the backhaul links.

In this paper we present a physical-layer network coding (PNC) scheme based on the recently developed complex low density lattice codes (CLDLC). CLDLC has high coding gain, good algebraic properties, and better coding gain at low dimension than real LDLC, which make it a good candidate for PNC. We show a parametric decoder for CLDLC, and demonstrate, via simulation that CLDLC-based PNC achieves good performance in a two way relay channel.

The code design problem for multilevel coded modulation with iterative decoding (MLCM-ID) has been left unsolved over a decade. In this paper, we define the code design criterion for MLCM-ID based on a novel concept-parametrically-mapped EXIT (PM-EXIT) function. We derive the EXIT functions for MLCM-ID, and present the mathematical work by which the three area theorems of PM-EXIT function are proved. This gives theoretical support of the curve-fitting techniques used in MLCM-ID, and also provides firm proof that the PM-EXIT function design rule allows in principle capacity-achieving code assignment. The simulation results perfectly match the theoretical analysis, and also confirm that the design rule proposed fully exploits the flexibility of MLCM-ID in the choice of codes. Both in theory and simulations, our code design is verified.

The performance of a dual-hop MIMO relay network is studied in this paper. The relay is assumed to have access to the statistical channel state information of its preceding and following channels, and it is assumed that fading at the antennas of the relay is correlated. The cumulative density function (cdf) of the received SNR at the destination is first studied, and closed-form expressions are derived for the asymptotic cases of the fully correlated and noncorrelated scenarios; moreover, the statistical characteristics of the SNR are further studied, and an approximate cdf of the SNR is derived for arbitrary correlation. The cdf is a multipartite function, which does not easily lend itself to further mathematical calculations, e.g., rate optimization. However, we use it to propose a simple power allocation algorithm, which we call “proportional power allocation.” The algorithm is explained in detail for the case of two antennas and three antennas at the relay, and the extension of the algorithm to a relay with an arbitrary number of the antennas is discussed. Although the proposed method is not claimed to be optimal, the result is indistinguishable from the benchmark obtained using exhaustive search. The simplicity of the algorithm combined with its precision is indeed attractive from the practical point of view.

We consider linear mapping functions for physical layer network coding (PNC), using a generalised description of linear mapping, and considering alternative algebraic structures within which a linear mapping can be defined. We discuss the requirements on a linear mapping for PNC in terms of ensuring unambiguous decoding, and hence consider the requirements this imposes on the coefficients of the linear mapping. We then consider an alternative forms of linear mapping, based on coefficients from rings, and show that this generalizes the more common approach using fields. We then consider the performance of the mappings in the two-way relay channel using QPSK as an example, and evaluate the information loss in terms of the equivocation at the destination under the possible singular fade states of the source-relay channels.

In this contribution, we study the property of FEC-coded differential PSK schemes with iterative non-coherent detection suitable for high mobility applications. Two distinct iterative non-coherent reception algorithms are proposed, in which decision feedback differential detection (DFDD) is used either to generate symbol probabilities or to predict the channel estimates. Turbo processing is employed in both schemes to progressively bridge the performance gap between coherent and non-coherent receivers by iteratively exchanging extrinsic information. Simulation results suggest that our proposed DFDD assisted iterative non-coherent DPSK trellis detection scheme is capable of delivering performance very similar to previous schemes reported in the literature, while being much simpler.

In this study, a new iterative interference cancellation (IIC) multiuser detection method is proposed for overloaded multiple‐input multiple‐output (MIMO) coded orthogonal frequency division multiplexing systems. A channel analyser is used to detect those channels for which the IIC detector will not converge. For these we propose two adaptive methods to enable detection. The first is to use a lower code rate for these channels. The second is to divide the transmitters into several groups which transmit in separate slots. Low‐complexity matched filter is applied, and both successive interference cancellation and parallel interference cancellation are considered for interference reconstruction. The simulation results show that the proposed technique can achieve near‐optimum bit error rate performance and optimum frame error rate performance, with lower complexity than optimum maximum‐likelihood methods.

Dynamic pilot allocation (DPA) for discrete Fourier transform (DFT)‐based channel estimation in multi‐input–multi‐output orthogonal frequency division multiplexing (MIMO‐OFDM) systems with spatial multiplexing can significantly improve the bit error rate performance compared with systems with uniform pilot allocation. However, the exhaustive search for optimum pilot allocation leads to very high complexity. The authors devise a multi‐input–multi‐output iterative pilot search (MIPS) algorithm applied with different MIMO‐OFDM receivers (linear, successive interference cancellation (SIC) and maximum likelihood (ML)), which significantly reduces the complexity of DPA. Exact derivations are also given based on the receivers. They also propose a novel stacked vector quantisation technique to reduce feedback burdens for DPA in MIMO‐OFDM system. Simulation results illustrate that the proposed MIPS algorithm with limited feedback can improve the performance of MIMO‐OFDM systems.

In this paper, we propose a novel linear physical-layer network coding scheme over hybrid finite ring (HFR-LPNC) for Rayleigh fading two-way relay channels. The relay maps the superimposed signal of the two users to a linear network coded combination (LNCC) in hybrid finite ring, rather than using the simple bit-wise eXclusive-OR mapping. The optimal linear coefficients are selected to generate the LNCC, aiming to: 1) maximize the sum-rate in the MAC phase; and 2) ensure unambiguous decoding. To avoid the performance degradation caused by high-order irregular mappings, properly designed source coding is used for compressing the LNCC alphabet over the hybrid finite ring into the unifying 4-ary alphabet. We derive the constellation constrained sum-rates for HFR-LPNC in comparison with 5QAM denoise-and-forward (5QAM-DNF), which we use as a reference scheme. Furthermore, we explicitly characterize the rate difference between HFR-LPNC and 5QAM-DNF. Our analysis and simulation show that: 1) HFR-LPNC has a superior ability to mitigate the singular fading compared with 5QAM-DNF; and 2) HFR-LPNC is superior to 5QAM-DNF over a wide range of SNRs.

In this paper, we propose a novel multilevel coded linear physical-layer network coding scheme with extended mapping (LPNC-EM) for Rayleigh fading two-way relay channels (TWRC). The relay node adaptively selects the linear generator matrix and directly maps the superimposed signal of the two users into the linear network coded combination over the hybrid Galois Field (GF(22) or GF(23)). The selection criterion ensures unambiguous decoding and maximizes the individual rate of each user. The LPNC-EM scheme forms two or three independent coding levels which facilitate the use of multilevel coding. This enables the hierarchical decode-and-forward paradigm as in [3]. The numerical results show that uncoded LPNC-EM outperforms the original physical-layer network coding (PNC) and can achieve a error performance as good as the 5QAM denoise-and-forward in [2]. Furthermore, the multilevel coded LPNC-EM also provides a superior error performance compared with the coded original PNC.

In this paper, anew iterative interference cancellation multiuser detection (MUD) method is proposed for overloaded multiple-input multiple-output (MIMO) coded orthogonal frequency division multiplexing (OFDM) systems. In the first iteration, a channel analyzer and selector are employed, which ensure that non-convergent channels are not used. Then low complexity RAKE reception is applied, and a successive interference cancellation (SIC)-based approach is used such that the strongest user is decoded first. In each iteration, the soft output of the convolutional decoder is fed back to cancel inter-user interference using parallel interference cancellation (PIC). The simulation results show that, this technique can achieve near-optimum bit error rate (BER) performance, and optimum frame error rate (FER) performance, with lower complexity than optimum maximum likelihood (ML) methods at the cost of 4% of channels rejected.

Rapidly time-varying channels introduce a signifi- cantly detrimental effect on conventional OFDM systems, which results in inter-carrier interference (ICI) and degrades the bit error rate (BER) performance, and makes channel estimation more difficult. In this paper, we propose a simple iterative receiver (MF-PIC) with multi-segmental channel estimation (MSCE) to improve the channel estimation and data detection performances over such high mobility scenarios. A matched-filter (MF) with parallel interference cancellation is employed to combat the ICI, and the symbol estimates are fed back for iterative channel estimation (MSCE). Simulation results demonstrate that the proposed receiver design can achieve a better BER performance over a wide range of normalised Doppler frequencies.

We consider distributed spatial multiplexing, in which a group of single-antenna terminals cooperate to transmit information to another such group using spatial multiplexing, thus increasing the capacity of the link between them. We focus on the link between relays and final destination, making use of Slepian-Wolf coding to compress the data and thus increase overall spectral efficiency. Here we implement the Slepian-Wolf coding using a Repeat- Accumulate-Repeat (RAR) code, and also apply an outer code.

In this contribution, we propose a novel differential distributed space-time block coding (DDSTBC) scheme for multirelay assisted two-way cooperative networks. A low-complexity non-coherent Physical-layer Network Coding (PNC) algorithm is first investigated, which allows direct extraction of network coded symbols from the received superimposed signal at the relay node without knowledge of Channel State Information (CSI). We show that, although the DDSTBC codewords are constructed by a group of single antenna aided cooperating nodes, the proposed scheme is still capable of attaining full transmit diversity order. The negative effect of error propagation suffered at the relay-to-destination link is addressed using a simple CRC-based selective relaying protocol. In addition, the employment of differential PNC at the intermediate relay node significantly improves the overall network throughput by exchanging information between two users simultaneously.

In this contribution, we investigate the properties of serially-concatenated coding (SCC) schemes with differential PSK modulation. The differential encoder (DE), which can be interpreted as a recursive non-systematic convolutional code, serves as a component encoder of the SCC system. A novel non-coherent reception algorithm is proposed, which is capable of bridging the performance gap between coherent and noncoherent receivers by iteratively exchanging extrinsic information. Since no prior channel state information (CSI) is available for the proposed non-coherent decoding approach, a low-complexity APP channel estimator is devised and incorporated to provide estimated channel coefficients using the a posteriori probability (APP) generated by the inner decoder. Results of SCC schemes with absolutely-encoded coherently-detected PSK are also presented to demonstrate that differential systems do not necessarily cause performance degradation.

Physical-layer Network Coding (PNC) can effectively improve the overall throughput of a multi-hop cooperative network communicating over two-way relay channels. In this contribution, we present a novel non-coherent/differential PNC scheme, which inherits the advantages provided by conventional PNC. We show that, although the assisting relay node has no access to the Channel State Information (CSI), our proposed non-coherent PNC detector with a low-complexity dual-branch structure is still capable of acquiring the network-coded symbols directly from a linearly superimposed signal. Compared with conventional two-way relay systems employing an inefficient four time-slot scheduling protocol, non-coherent PNC aided bidirectional cooperation scheme is able to double the throughput by elimination of two transmission periods. Therefore, significant improvements in the spectral efficiency and network capacity can be attained by incorporating this novel non-coherent PNC technique in the two-way relaying scenario.

In this paper, we propose a novel fading correction and relaying scheme for physical layer network coding (PLNC) in the two-way relay (TWR) fading channel. The fading correction on the soft-bit level at nodes can eliminate the effect of fading on the TWR channel. In order to broadcast the soft-bit in an optimal way, we design a quantize-and-forward scheme which is robust for the TWR fading channel. In addition, an optimized mapping is used to implement unequal error protection (UEP) for bits with different significance in the quantization index. The soft-bit correction and the robust quantize-and-forward scheme are fully compatible with one another. Both low complexity and good performance can be provided.

Adding fixed relay nodes (RNs) to wireless access networks requires additional costly infrastructure. Utilising mobile RNs, that is, user terminals that relay signals intended for other users being the destination nodes (DNs), is an appealing cost-effective solution. However, the changing node topology increases the required signalling for relay selection (RS). The signalling overhead consists of control signals that need to be exchanged between the RNs, the source node (SN) and the DN, to achieve the objectives of cooperation. To reduce signalling without penalising performance, the authors propose a three-step approach exploiting statistical knowledge on the likelihood of attaining performance gains by using RNs as a function of the node position (position of DNs and RNs). In the first step only the cell DNs that are likely to gain from relaying request the assistance of RNs. In the second step, for each DN that requests relaying, a limited set of RN candidates is formed. These decisions are made with the aid of thresholds applied to inter-node distances whose values are based on the acquired statistical knowledge. In the final step, RN candidates feed back the relevant channel state information to the SN that performs RS. Furthermore, the authors investigate the attained gains from mobile RNs as a function of the fading environment and they show that mobile RNs can help overcome the effects of severe fading.

In cooperative communication networks, owing to the nodes' arbitrary geographical locations and individual oscillators, the system is fundamentally asynchronous. This will damage some of the key properties of the space-time codes and can lead to substantial performance degradation. In this paper, we study the design of linear dispersion codes (LDCs) for such asynchronous cooperative communication networks. Firstly, the concept of conventional LDCs is extended to the delay-tolerant version and new design criteria are discussed. Then we propose a new design method to yield delay-tolerant LDCs that reach the optimal Jensen's upper bound on ergodic capacity as well as minimum average pairwise error probability. The proposed design employs stochastic gradient algorithm to approach a local optimum. Moreover, it is improved by using simulated annealing type optimization to increase the likelihood of the global optimum. The proposed method allows for flexible number of nodes, receive antennas, modulated symbols and flexible length of codewords. Simulation results confirm the performance of the newly-proposed delay-tolerant LDCs.

This paper investigates the performance degradation of Hierarchical Decode-and-Forward (HDF) Turbo Coded Physical Layer Network Coding (PLNC) on the Two-Way Relay Channel (TWRC) compared to a single user end-to-end Turbo coded system, which provides a simple upper bound on the performance. We have analyzed the basis of this degradation by both Information Theory and numerical derivation, also using EXIT charts. This results in a tighter performance bound, and shows that the degradation inherently results from the superposition of the electromagnetic signals.

In this paper, we investigate a dynamic pilot allocation algorithm for Discrete Fourier Transform (DFT)-based channel estimation in MIMO-OFDM systems, which employs feedback to adapt pilot locations to mobile channels for different receivers (ZF-linear, ZF-SIC, MMSE-linear, MMSE-SIC). The pilot allocation is dynamically controlled by feedback of the pilot allocation index so to optimize SER performance. Furthermore, mathematical expressions of the instantaneous signal to interference and noise ratio (SINR) in the presence of channel estimation error for different receivers are derived to obtain the error probabilities of data subcarriers through an approximate error probability function for MPSK modulation. The pilot locations are based on these error probabilities to avoid data symbols transmitted over these subcarriers with high error probabilities instead of pilots over them. Simulation results are provided to illustrate the performance gains achieved with these receivers by this dynamic pilot allocation.

In this contribution, we present a novel distributed space-time block coding (DSTBC) scheme with the aid of an error detection code based selection relaying protocol for multi-relay assisted two-way cooperative communication systems. We show that our proposed scheme can achieve full diversity order without employing any strong channel codes to protect the source-to-relay link. This simple selection relaying strategy can effectively mitigate the error propagation inflicted by the relay nodes for the sake of retaining the orthogonality of the space-time block code which is constructed and transmitted in a distributed fashion. Also, physical-layer network coding (PNC) is employed to guarantee that the information exchange between two users via a single or multiple relays can be fulfilled within two time slots. Hence, this novel cooperative communication scheme for two-way relay channels can achieve significant throughput and spectral efficiency improvements.

We propose a new analytical approach to evaluate the average packet error rate (PER) of a conventional packet transmission system over a quasi static fading channel, by presenting an integral inequality lemma. The basic idea of the approach is that, given the PER for the AWGN channel as a function of signal-to-noise ratio (SNR), the average PER over Rayleigh fading channel can be generally upper bounded by a quite simple inequality, i.e.,1 - exp(-wo/γ̅), for both coded and uncoded schemes, where wo, defined by an integral expression, corresponds exactly to the inversion of coding gain; and this bound is tight in the high SNR region or for long packet systems. We further apply the integral inequality to extend our research to more general Nakagami-m fading channel.

Despite the very substantial body of research on the performance analysis of cooperative relay systems, most studies focus on either the symbol error ratio (SER) or outage behavior. This paper analyzes the asymptotic average packet error rate (PER) of the packet cooperative relay system for both AF (Amplify-and-Forward) and DF (Decode-and-Forward) schemes in the high signal-to-noise ratio (SNR) region, and studies the effect of packet length on average PER performance. It is shown that the system achieves the same diversity gain in terms of PER as in terms of SER, but with different coding gain depending on packet length. If we consider practical packet lengths, the DF scheme always achieves better performance than the AF scheme; with shorter packet length, the advantage of DF over AF is more significant. For large enough packet length, AF performance approaches that of DF.

Despite the very substantial body of research on the performance analysis of cooperative relay systems, most studies focus on either the symbol error ratio (SER) or outage behavior. This paper first analyzes the asymptotic average packet error probability (PEP) of uncoded packet cooperative relay system for DF (Decode-and-Forward) schemes in the high signal-to-noise ratio (SNR) region. In particular, the effect of packet length on optimum power allocation roptis studied. It is found, with a symmetrical links assumption, the optimum power allocation ratio is in the region of 1/2optoptvalue converges to (3-√3)/2.

The paper addresses wireless the 2-Way Relay Channel (2-WRC) system with a Hierarchical Decode and Forward strategy. This strategy uses a Hierarchical eXclusive Code (HXC) that allows full decoding of the hierarchical symbols at the relay. The HXC represents two data sources only through the exclusive law and requires side information on the complementary data at the destination (which naturally holds for the 2-WRC). The HDF strategy has the advantage over classical MAC stage relaying with joint decoding that its rate region extends beyond the classical MAC region. We evaluate the hierarchical MAC capacity regions for various alphabets, constellation point indexing and various channel parametrization and compare that to the alphabet limited and unconstrained cut-set bounds.

In earlier paper we proposed a differential spatial multiplexing (SM) scheme based on complex square orthogonal designs, referred to as differential orthogonal spatial multiplexing (DOSM). The receiver of DOSM does not require estimation of channel fading coefficients, channel power, signal power, or noise power to decode the data symbols and the decision is based on the two consecutively received codewords. In, the transmission matrix of DOSM is based on complex square orthogonal designs which cannot achieve full data rate. Hence, we presented a constellation rotation strategy to enhance the rate of DOSM. In this paper, we construct the transmission matrix of DOSM from complex rectangular orthogonal designs and find that full-rate DOSM can be achieved with increased encoding block length. An upper bound of the pair-wise error probability (PEP) for DOSM in Rayleigh fading channels is derived. Simulation results show that the proposed DOSM outperforms the differential space-time block code (DSTBC) with full diversity and the existing differential SM schemes in terms of error-rate performance over quasi-static Rayleigh fading channels.

In a closed-loop multiple-input multiple-output orthogonal frequency division multiplexing (MIMO-OFDM) system, the receiver estimates the channel and sends updates on the channel state back to the transmitter. The issue of deciding when to send updates is addressed in this paper and two metrics for making this decision are compared. One is obtained from the correlation matrix distance (CMD) which measures how far the MIMO channel has moved over a time interval, the other is a novel approach using mutual information (MI), whereby two calculations of MI are made, the first assuming that water-filling is employed at the transmitter and the second assuming that it is not. Using CMD, updates are sent when the correlation distance becomes greater than a given threshold. Using MI, updates are sent when the channel changes to the extent that the capacity with water-filling becomes less than that without. Matlab simulation results for a 2 * 2 MIMO system show that the two metrics result in a similar overhead, both being more efficient than constant interval. Extension to larger antenna arrays should be straightforward. MI, although computationally more intensive, can extend easily to decide when to switch between spatial multiplexing (SM) and diversity modes using space-time block coding (STBC) if the channel rank collapses.

Most research on distributed space-time block coding (D-STBC) has so far focused on the case of 2 relay nodes and assumed that the relay nodes are perfectly synchronised at the symbol level. This paper applies STBC to 4-relay node systems under quasi-synchronisation and derives a new detector based on parallel interference cancellation, which proves to be very effective in suppressing the impact of imperfect synchronisation.

In this paper, we propose a novel and simple approximate maximum likelihood detector (A-ML-D) for single input and single output (SISO) systems over frequency-selective fading channels based on Tomlinson-Harashima pre-equalizer. By assuming full channel state information (CSI) at the transmitter side, the pre-equalizer can remove some inter-symbol interference (ISI) at the transmitter. At the receiver, we implement a Gaussian approximation, a pre-whitening filter and a matched filter to realize a set of parallel SISO schemes, and thus, facilitate single symbol detection. The proposed scheme can obtain full multi-path diversity and achieve near-optimal performance with a complexity lower than linear MMSE and MMSE-DFE. Analytical symbol error rate (SER) is derived to further justify the proposed detector.

In this paper, we propose several power control schemes for MIMO systems using spatial multiplexing (SM) with a minimum mean square error (MMSE) receiver under slow fading, to improve the bit error rate (BER) performance, both for an individual link and within a cellular system. After comparing the performance of these proposed power control schemes, we find that a further scheme which effectively combines the two methods with the best performance will provide better results than employing them individually.

Significant performance gain can potentially be achieved by employing distributed space-time block coding (D-STBC) in ad hoc or mesh networks. So far, however, most research on D-STBC has assumed that cooperative relay nodes are perfectly synchronized. Considering the difficulty in meeting such an assumption in many practical systems, this paper proposes a simple and near-optimum detection scheme for the case of two relay nodes, which proves to be able to handle far greater timing misalignment than the conventional STBC detector.

Most research on differential MIMO is based on space-time block codes, aiming to achieve maximum transmit diversity and thus make the transmission more robust by the aid of the special orthogonal or quasi-orthogonal code structures. However, a differential scheme based on a spatial multiplexing approach such as the Bell-Labs layered space time (BLAST) wireless architecture would be likely to provide a much greater capacity. To this end, in this paper, we derive a simple differential modulation scheme based on BLAST for any number of transmit antennas and receive antennas. A special symbol mapping method is developed to avoid amplitude variation of the transmitted signals, which can also improve the system performance. This differential scheme can significantly reduce the system complexity, since it avoids the need for channel estimation. Moreover, an improved sub-optimal detection algorithm based on a Gaussian approximation is applied to greatly reduce computational complexity at the receiver, otherwise prohibitive, with only very slight performance loss.

The realistic performance of a multi-input multi-output (MIMO) communication system depends strongly on the spatial correlation properties introduced by clustering in the propagation environment. Simulating realistic correlated channels is essential to predict the performance of real MIMO systems. Since the modeling method of the correlated channels suggested by the Third Generation Partnership Project (3GPP) channel model can result in considerable implementation complexity for large networks, this paper presents a computationally efficient method to approximately calculate the spatial correlation matrix for channel models such as the 3GPP channel model, which are based on clusters of scatterers. This proposed approximation method is on the basis of using the Taylor series expansion to the steering vectors for uniform linear arrays (ULAs) and a moderate angle spread of the cluster. The approximation method is evaluated in terms of the mean square error (MSE) of the approximated correlation matrix, and by the cumulative distribution function (CDF) of the mutual information of the MIMO channel. This shows that the proposed approximation method is close for angle spread of the cluster within 10deg, with high efficiency and low complexity.

This paper compares the relative performance of coded single carrier frequency domain equalisation (SC-FDE) and orthogonal frequency-division multiplexing (OFDM) on frequency-selective fading channels. We focus on the extent to which the two schemes can exploit the frequency diversity inherent in such channels. Channels with different impulse response lengths, and therefore available diversity order are considered, with convolutional codes of different rates and constraint lengths, and also turbo-codes. We show that on all channels SC-FDE has better performance with codes having smaller minimum distance. However with more powerful codes, which enable it to exploit the full frequency diversity available in the channel, OFDM has better performance, particularly on channels with greater diversity.

Most research on distributed space time block coding (STBC) has so far focused on the case of 2 relay nodes and assumed that the relay nodes are perfectly synchronised at the symbol level. By applying STBC to 3- or 4-relay node systems, this paper shows that imperfect synchronisation causes significant performance degradation to the conventional detector. To this end, we propose a new STBC detection solution based on the principle of parallel interference cancellation (PIC). The PIC detector is moderate in computational complexity but is very effective in suppressing the impact of imperfect synchronisation.

This paper discusses the application of adaptive modulation and adaptive rate turbo-coding to OFDM (orthogonal frequency-division multiplexing), to enable a closer approach to the Shannon capacity of the time and frequency selective channel. The adaptive turbo-code scheme is based on a subband adaptive method, and compares two adaptation algorithms: a conventional, conservative approach where modulation and code rate is chosen based on the poorest subcarrier in a subband, and an optimal approach based on a prediction of the average BER over all sub-carriers. Four modulation schemes (BPSK, QPSK, \8AMPM and 16QAM) and four code rates (1/3, 1/2, 2/3 and uncoded) are employed. Systems employing different numbers of combinations of these schemes are compared. Simulation results for throughput and BER show that 8 schemes are sufficient to approach the maximum capacity: a small reduction in throughput occurs with only 4 schemes (all 1/2 rate coded). The optimal adaptation algorithm provides a significant improvement.

A general and simple differential modulation scheme that can be applied to both partial-diversity quasi-orthogonal space–time block codes and full-diversity quasi-orthogonal space–time block codes is reported. A new class of quasi-orthogonal coding structures is presented for various number of transmit antennas. Differential encoding and decoding can be simplified to differential Alamouti codes by grouping the signals in the transmitted matrix and decoupling the detection of data symbols, respectively. For the codes with partial transmit diversity, the new scheme can achieve constant amplitude of transmitted signals, and avoid signal constellation expansion; in addition, it has a linear signal detector with very low complexity. Simulation results show that these partial-diversity codes can provide very useful results at low signal-to-nose ratio for current communication systems. For codes with full transmit diversity achieved by constellation rotation, the proposed scheme has performance equal to the best full-rate quasi-orthogonal schemes previously described in the literature with the benefit of a simpler detector. Moreover, a simple linear detector is also presented for the case when two orthogonal ASK constellations are used. Extension to more than four transmit antennas is also considered.

We propose novel low-complexity iterative channel estimators based on B-splines. Local splines are adopted for computational simplicity. Minimum mean square error (MMSE) local splines with integral sampling are derived. The MSE of the proposed estimators depends on signal-to-noise ratio, fading rate, sampling interval, spline order and the number of weighting coefficients; these dependencies are investigated. The linear and cubic local splines with as few as seven weighting coefficients are capable of achieving MSE and BER performance comparable to those of the Wiener filter and the spheroidal basis expansion. However, a significantly lower complexity is achieved using B-splines

In this letter, we propose a simple differential space-time block code with a quasi-orthogonal structure. A simple and general encoding procedure is presented, which differentially encodes the signal transmission matrix as a whole at the transmitter end. A novel power estimator is derived at the receiver to allow for the non-constant amplitude of the received signals. Simulation results show that our scheme has performance equal to the best full rate quasi-orthogonal schemes previously described, along with a simpler decoder

To carry out simple linear decoding, it is usually assumed in space-frequency block coded orthogonal frequency division multiplexing (SFBC-OFDM) systems that the channel frequency responses between sub-carriers remain constant within a block length [1]. However, this assumption becomes unreliable when the system operates in a severe multipath environment. The conventional linear decoder [1] gives rise to inter-channel interference (ICI) due to variations of channel frequency response between sub-carriers. In this paper, we propose a turbo-based interference cancellation scheme to mitigate this effect. While the implementation complexity is higher than for conventional detection, the proposed scheme can effectively eliminate ICI, and exploit the increased diversity available in channels with long delay profile.

In this paper, the short-term time variation of wideband channels is investigated based on some extensions to the WINNER interim beyond-3G (IB3G) spatial channel model (SCM), using the full channel correlation matrix. These extensions mainly include some modifications of the generation of the wideband fast fading channel matrix, such as the consideration of the time variant sub-path phases at the mobile station (MS), and of the time variant path powers, and the generation of different last bounce distances (LBDs) for the mid-paths within each path. In order to measure the short-term time variation of the wideband channels, this paper presents a redefinition of the correlation matrix distance (CMD) metric, which was originally proposed for the narrowband fast fading scenario. By comparing the simulated CMD generated from the newly extended 3GPP (NE-3GPP) SCM with that of the measurements taken in the FLOWS project, we find the following main conclusions: (1) The Kronecker assumption can not be applied in calculating the instantaneous full channel correlation matrix, since it leads to significant deficiencies in the simulated CMDs from the NE-3GPP SCM. (2) The simulated CMDs generated from the NE-3GPP SCM compares better to the measurements taken in the FLOWS project than that of the IB3G SCM

The aim of this paper is to explore techniques to achieve spatial diversity based on per-antenna rate control (PARC) and develop more flexible schemes that can effectively achieve easy switching between spatial multiplexing and transmit diversity for future mobile systems. The basic idea is to input the same data in each PARC sub-stream and de-correlate these sub-streams via scrambling and/or interleaving techniques with the aim of diversity improvement. After comparing variants of PARC, it has been shown that transmitting the same data in each sub-stream and subsequently de-correlating the sub-streams with different interleaving and/or scrambling not only obtains very promising performance, but also has extremely low computational complexity.

The uplink capacity of cellular systems, where the co-channel interference (CCI) limits the system capacity more than thermal noise, is investigated in this paper. We evaluate the overall system capacity under slow fading when Space-time block codes (STBC) are employed. A power control technique suited for STBC is proposed to improve the bit error rate (BER) performance on the target link and the system capacity. Handover is also considered to provide further improvement on the system capacity.

In this paper, the short-term time variation of wideband channels is investigated based on some extensions to the interim beyond-3G (IB3G) spatial channel model (SCM), which was developed for a multi-input multi-output (MIMO) system and used within the European WINNER project. These extensions mainly include some modifications of the generation of the wideband fast fading channel matrix, such as the consideration of the time variant sub-path phases at the mobile station (MS), the consideration of the powers of the time variant multi-paths, and the generation of different last bounce distances (LBDs) for the mid-paths within each path. In order to measure the short-term time variation of the wideband channels, this paper redefines the correlation matrix distance (CMD) metric, which was originally for the narrowband fast fading scenario. The simulated CMD generated from the newly extended Third Generation Partnership Project (NE-3GPP) spatial channel model (SCM) compares better to the measurements taken in the FLOWS project than that of the IB3G SCM.

One major assumption in all orthogonal space-time block coding (O-STBC) schemes is that the channel remains static over the length of the code word. However, time-selective fading channels do exist, and in such case conventional O-STBC detectors can suffer from a large error floor in the high signal-to-noise ratio (SNR) cases. As a sequel to the authors' previous papers on this subject, this paper aims to eliminate the error floor of the H/sub i/-coded O-STBC system (i = 3 and 4) by employing the techniques of: 1) zero forcing (ZF) and 2) parallel interference cancellation (PIC). It is. shown that for an H/sub i/-coded system the PIC is a much better choice than the ZF in terms of both performance and computational complexity. Compared with the, conventional H/sub i/ detector, the PIC detector incurs a moderately higher computational complexity, but this can well be justified by the enormous improvement.

A novel B-spline iterative channel estimation technique over fast flat fading channels is proposed. Both local linear and parabolic splines are considered. The optimal sampling interval is found by simulations and then approximated by a simple equation. Comparisons with the Wiener filtering approach in mean square error (MSE), bit error rate (BER) and complexity are given. The BER performance of the iterative receiver with the proposed estimators is very close, within 0.3 dB for BER = 10/sup -4/ of that of the Wiener estimator for fading rates up to f/sup d/T/sup s/ = 0.02. However, the proposed estimators require only a few multiplications per symbol per iteration which is only a small fraction of that of the Wiener filter.

The deployment of dual-polarized antennas in multiple-input multiple-output (MIMO) systems is a promising technique, allowing two spatially separated unipolarized antennas to be replaced by a single dual-polarized antenna element. In this paper, we use the four-dimensional (4-D) trellis coded modulation (TCM) as a channel code to jointly encode the parallel-transmitted dual-polarized signals. A joint decoding algorithm is proposed to jointly decode the received signals on the two orthogonal polarizations. The system performance is evaluated for both the Rayleigh fading channel and the Ricean fading channel representing the typical suburban environment of broadband fixed wireless access at 2.5 GHz.

This paper investigates the performance of different spreading factors for uplink WCDMA in frequency selective channels. Comparison of perfect channel knowledge with estimated channel is performed and analysed. The performance is also analyzed for different Doppler frequencies corresponding to different speeds. A conventional Rake receiver was developed whose performance improved with an increase in diversity and when the paths that arrived were separated by one chip duration. To estimate the channel parameters, that are needed to correct the phase rotations and attenuations caused by the fading channel, a Wiener filter was employed which produced estimates in agreement with the actual channel parameters. The performance of various spreading codes were analysed which showed that codes with higher spreading gain performed better than those with lower gains due to the high cross correlation between shorter code lengths. High intersymbol interference (ISI) was experienced by signals with high data rates (low spreading factors) than signals with low data rates. Performance of BER of signals experiencing higher Doppler frequencies were high than those with low Doppler frequencies.

In this paper, we propose a simple differential spacetime block code with a quasi-orthogonal structure, which can offer full rate and full diversity. At the transmitter, we divide the codes into sub-coding blocks, and combine the sub-coding blocks at the receiver to employ differential decoding by channel power estimation instead of decoding each sub-coding block separately. Our general approach can be extended to the recently-proposed quasi-orthogonal codes with full rate and half diversity. Moreover, this scheme is not limited to PSK constellations but can also utilize QAM constellations, so that additional coding gain can be obtained.

In order to simplify the decoding algorithm, it is usually assumed in previously reported work on space-frequency block coded orthogonal frequency division multiplexing (SFBC-OFDM) systems utilizing space-time block codes (STBC) that the frequency responses of adjacent subchannels are approximately constant for a STBC block length (K.F. Lee and D.B. Williams, 2000). Under this assumption, the conventional linear decoder proposed for STBC in V. Tarokh et al. (1999) can be equivalently used in SFBC-OFDM systems to achieve the maximum diversity gain with the lowest computational complexity. However, this assumption is not accurate when the number of OFDM sub-carriers is small or the system operates in a severe multipath environment. The conventional decoder will give rise to interference due to the channel frequency response variations in adjacent subchannels. This result in an irreducible error floor in the high signal-to-noise ratio (SNR) region of the bit error rate (BER) curve and decreased diversity gain. In this paper, we propose a parallel interference cancellation (PIC) detection scheme with inner and outer iterations for G4(V. Tarokh et al., 1999) coded SFBC-OFDM transmit diversity systems over frequency selective fading channels. Simulation results will show that the proposed scheme can mitigate the interference effect and make the error floor occur at a very low BER, which can be neglected

One major assumption in most existing space-frequency (SF) OFDM systems is that neighboring OFDM sub-channels (SC) have the same channel transfer functions (CTF). However, this assumption might be not feasible for small number of SC or long code block length because in such cases the channel gains between adjacent SC will not be approximately constant. Even if the number of SC is large enough, in some parts of the OFDM spectrum, or in a severe multipath environment, the variation of the channel gain cannot be ignored. Because of this the linear ML decoder in Tarokh et al. (1999) cannot be readily used to achieve maximum diversity, and it will cause an irreducible error floor in the high signal-to-noise ratio (SNP) region. To this end, this paper proposes an interference cancellation (IC) signal detector to reduce the error floor. While the computational complexity of the IC detector is a little higher than that of the conventional ML linear detector, the new IC detector provides much better performance by subtracting the interference resulting from variations between the adjacent SC.

One major assumption in all orthogonal space-time block coding (O-STBC) schemes is that the channel remains static over the entire length of the codeword. However, time selective fading channels do exist, and in such case the conventional O-STBC detectors can suffer from a large error floor in the high signal-to-noise ratio (SNR) cases. This paper addresses such an issue by introducing a parallel interference cancellation (PIC) based detector for the G/sub i/ coded systems (i=3 and 4).

One major assumption in all space-time block coding (STBC) schemes is that the channel remains static over the length of the codeword. However, time selective fading channels do exist, and in such case the conventional STBC detectors can suffer from a large error floor in the high signal-to-noise ratio cases. As a sequel to our previous papers on this subject, this paper aims to eliminate the error floor of the H/sub i/ coded STBC systems (i = 3 and 4) by employing the technique of parallel interference cancellation (PIC). Compared with the conventional H/sub i/ detector, the PlC detector incurs a moderately higher computational complexity, but this can be justified by the enormous performance improvement.

We consider MlMO schemes with N/sub t/ transmit and N/sub r/ receive antennas using BPSK modulation in quasi-static fading. We show that space-time (ST) bit-interleaving coded-modulation (BICM) approaches mapping binary codes to BPSK ST codes show a loss over coded-modulation (CM) MIMO capacity. This is despite the use of an optimal inner detector and is illustrated using capacity CDFs for the CM and ST-BICM cases. The CDFs are translated to plots of outage probabilities as functions of SNR. For capacity-achieving schemes, these indicate that SNR losses of ST-BICM over CM approaches decrease with N/sub r/ and increase with N/sub t/. Finally, we amend our method for where the outer binary code is only capacity-approaching - we find this provides accurate predictions of FERs for ST-BICM using an outer turbo code.

A pilot symbol assisted modulation (PSAM) based iterative channel estimation method - applied in conjunction with turbo equalization - over time and frequency selective fading channels is proposed. Initial channel estimates are derived from periodic optimal pilot sequences by maximum likelihood (ML) acquisition and Wiener filtering. In the iterative channel estimator, soft decisions from the decoder are used to cancel inter-symbol-interference (ISI) and thus the frequency selective channel is decoupled into multiple flat fading sub-channels. Refined channel estimates of individual multipath taps are obtained independently from each sub-channel which is treated as a flat fading channel. Simulation results using a continuously time-variant channel model show bit error ratio (BER) performance gains and normalized mean squared error (MSE) improvements achieved by the iterative channel estimation scheme over those of the non-iterative scheme for normalized fade rates f/sub d/T/sub s/ = 0.01 and f/sub d/T/sub s/ = 0.005.

The paper establishes a general framework for iterative separate CSE in general iterative decoding networks. Two particular cases of CSE are examined - SDD (soft-decision directed) and EM (expectation-maximization) based one. Both have capabilities for exploiting the iteratively improved backward measure from the decoding network, however both exhibit different properties and provide different possibilities for iteration scenarios. An example application with simple serially concatenated code with QPSK mapping in AWGN channel with phase rotation is investigated to demonstrate the differences between the algorithms in terms of MSE, ambiguity resolution, and convergence behavior.

Up to now most research on the capacity of MIMO systems has been carried out on a point-to-point link. However the capacity and BER performance of such systems in a cellular environment have not been much investigated. In this paper, we investigate the BER performance of a space-time block coded MIMO system in the presence of an interferer, which is treated as unknown, and interferers in a cellular system. The concept of a spatially pre-whitened matched filter is used to improve the BER performance of the system in which interference will not in general be spatially white.

This work investigates the up-link capacity of a multiple-input multiple-output (MlMO) wireless channel subject to finite multipath scattering in the presence of co-channel interference (CCI). We first consider single interferers with fixed position and then extend to cellular systems. We observe that the average capacity of MlMO system in the presence of interference is significantly greater than that of a single-input single-output (SISO) system and a single-output multiple-output (SIMO) system at moderate SNRs. It is presented that the link capacity of a MIMO system could be maximised by means of a spatially-whitened matched filter, which converts the interference uncorrelated between receive antennas. It is shown that the capacity of the finite scatterers channel can be even larger than that of the independent Rayleigh channel through the use of spatial pre-whitening filter.

This paper examines the problem of carrier phase recovery in turbo-coded systems. We introduce a new concept of "a priori probability aided phase estimation", where the extrinsic information (log-likelihood ratio) obtained from turbo decoder is used to aid an iterative phase estimation process, which is based on a maximum-likelihood strategy. The phase estimator operates jointly with the turbo decoding rather than separately prior to the decoder as in traditional approaches. This technique provides reliable phase estimation with variance of estimation errors approaching the Cramer-Rao bound at very low signal-to-noise ratio and allows robust decoding with a wide range of phase errors. This paper addresses its application in turbo-coded binary phase-shift keying and quaternary phase-shift keying systems over the additive white Gaussian noise channel. The bit-error-rate performance is investigated and shows that the performance of this technique is very close to the optimally synchronised system and significantly outperforms the traditional non-data-aided method without using additional pilot symbols.

A key assumption in all orthogonal space-time block coding (O-STBC) schemes is that the channel remains static over the length of the codeword. However, time selective fading channels do exist, and in such case the conventional O-STBC receiver will not function properly: even a relatively small variation in channel state can result in a large error floor. This paper presents an effective solution to this issue for the case of four transmit antennas. At the receiver, a simple zero forcing decoder is derived. To improve the performance of the decoder under certain channel conditions, the original O-STBC encoder is also modified accordingly. Computer simulations confirmed the effectiveness of the new procedure.

For the quasi-static Rayleigh fading multiple-input/multiple output (MIMO) channel, we consider BPSK space-time (ST) codes with rates /spl ges/ 1 and diversity /spl les/ L derived from linear binary codes where L is the number of transmit antennas. For L = 2,3 and 4, we derive conditions on both the generator matrix G and the parity-check matrix H for a code to achieve diversities 2, ..., L. we then introduce the concept of duals of linear binary-based ST codes, since a particular relationship between the conditions on G and on H shows that rate 1, diversity L and rate L - 1, diversity 2 codes are duals. Thus, a matrix G (or a matrix H) of a rate 1, diversity L BPSK ST code may also be used as the matrix H (or matrix G) of a rate L-1, diversity 2 code. Example codes for 3 and 4 antennas are given along with decoding results from simulations.

In this paper we consider a multiple-input multiple-output (MIMO) downlink multi-cell CDMA system employing BLAST space-time turbo codes (STTuC) over the frequency-selective fading channel. The system performance is measured in terms of system spectral efficiency (bits/s/Hz/cell). A space-time RAKE receiver and a space-time turbo receiver are proposed. The turbo receiver is based on space-time parallel interference cancellation (ST-PIC), which can reconstruct and subtract all the types of interference in the multipath MIMO CDMA channel at the same time. In each iteration, the soft output of the space-time turbo decoder is fed back to improve the PIC's performance. The simulation shows that the turbo PIC receiver enhances the STTuC CDMA system spectral efficiency by 50% over the RAKE receiver. This result suggests that, with the turbo reception technique, the MIMO CDMA system can serve much more users in a cell or provide much higher rate downlink packed data service to one user.

We consider the limits to the capacity of the multiple-input-multiple-output wireless channel as modeled by the finite scatterers channel model, a generic model of the multipath channel which accounts for each individual multipath component. We assume a normalization that allows for the array gain due to multiple receive antenna elements and, hence, can obtain meaningful limits as the number of elements tends to infinity. We show that the capacity is upper bounded by the capacity of an identity channel of dimension equal to the number of scatterers. Because this bound is not very tight, we also determine an estimate of the capacity as the number of transmit/receive elements tends to infinity which is asymptotically accurate.

In this paper a synchronous multiple-input multiple-output (MIMO) uplink CDMA system employing space-time turbo codes is considered. We introduce a multiuser-antenna receiver structure to detect the multiuser and multi-antenna signal in this system. The linear minimum mean-squared error (MMSE) detector and an MMSE-based turbo parallel interference cancellation (PIC) detector are respectively utilized to suppress the multiple access interference (MAI) between users and the crosstalk between antennas at the same time. In the turbo PIC detector, the soft output of the space-time turbo decoder is fed back to improve the PIC's performance. Using computer simulation, we examine the multiuser-antenna detectors' performance in the block Rayleigh flat fading channel. The simulation results suggest the two multiuser-antenna receivers can both combat the interference between different users and antennas. However the iterative detector achieves a substantial performance gain over the MMSE one.

This paper investigates three techniques for optimising the capacity of cellular communication schemes: power control, dynamic channel assignment and adaptive modulation and coding. Each scheme, and combination of schemes, is investigated under the same assumptions for channel model, number of cells and quality of service provision; and simulation is used to derive the number of simultaneous users that can be supported in each case. It is shown that the additional complexity of adaptive modulation and coding is rarely justified, and that the facility for intracell handoffs is the most important technique to include in an efficient resource allocation algorithm.

In this paper we consider an uplink CDMA system employing multiuser detection to suppress multiple access interference (MAI) at the base station. An iterative parallel interference cancellation (PIC) multiuser receiver structure utilizing the minimum mean-squared error (MMSE) detection as its first stage is used, including turbo decoders. We use this structure on a slow, flat Rayleigh fading channel, as well as the AWGN channel, but find that its performance is relatively poor, limited by the single user bound. Accordingly we develop an improved turbo multiuser receiver that can be used in systems with multiple receive antennas. The simulation results demonstrate that this diversity technique allows the turbo PIC receiver to recover its ability to enhance the system performance, even in the presence of severe multipath fading.

A timing recovery system is proposed based on maximum likelihood estimation, suited to coding systems employing iterative soft-in/soft-out decoding like turbo codes, as this method utilises the soft-output from the decoder to assist in the timing estimation. Timing recovery is combined with decoding through an iterative technique in contrast to the traditional approaches where timing recovery is carried out prior to decoding. The timing estimate is one of the zeros on the S-curve (the log-likelihood function derivative) corresponding to the maximum of the log-likelihood function. It is resolved using an interpolation algorithm based merely on four samples and avoids generating the whole S-curve for every block. The synchroniser has effectively no acquisition period. The performance of the estimator is analysed in terms of the mean and the variance of the timing estimate, and it is shown that it provides a significant improvement over the non-data aided (NDA) method and approaches the results obtained from the data aided (DA) method (which ideally assumes the data is known and available all the time) after 5 iterations.

A new method of carrier phase recovery is implemented with the assistance of the extrinsic information from the turbo decoder. BPSK systems using turbo-codes over an AWGN channel with unknown phase are investigated. The phase recovery and turbo-decoding is implemented jointly and iteratively. The phase error can be corrected up to 82/spl deg/. The decoding can be made robust against phase uncertainty. The results show that this joint method gives a great improvement over the traditional techniques, which implement separate synchronisation prior to feeding the signal to the decoder. A further improvement of this method is also proposed, which can remove most of the phase errors completely or recover any phase error over 2/spl pi/ although it sacrifices some performance.

This paper proposes a carrier phase recovery approach when turbo codes are used. The phase estimation is implemented with the aid of the extrinsic information from the turbo decoder. A series of look-up tables are pre-computed to reduce the computation complexity, and thereby we avoid introducing delay to the decoding. Simulations are carried out both in BPSK and QPSK systems. If the block size is 1024, a phase error up to 82/spl deg/ in a BPSK system, and up to 37/spl deg/ in a QPSK system can be removed completely. Compared with the conventional method, which has separate phase recovery and decoding, this approach exhibits a great improvement. The effect of block size is also considered. The results demonstrate that the longer the block size, the better the performance.

This paper shows the comparable performance of Tomlinson-Harashima precoding (1971, 1972) and MMSE-DFE (minimum mean square error-decision feedback equaliser) over a broadband wireless access (BWA) channel, for several Doppler frequencies. The system is operating in the 2.6 GHz MMDS (multichannel multipoint distribution service) band, which requires multipath equalisation techniques. Precoding is an equalisation technique requiring accurate information of the channel characteristics. The accuracy of the channel estimate, which ultimately determines the convergence and performance of the equalisation scheme, can be affected either by the length of the training or pilot sequence, or the duration between channel estimations. This paper examines both the minimum required training sequence length and the effects of increasing the equaliser up-date period as a function of the number of data packets. It is shown through simulation, that precoding can be used as an alternative equalisation strategy for multipath channels with slow fading characteristics.

Methods of substantially reducing call dropping in networks which use distributed dynamic channel assignment (DDCA) schemes are discussed. Interference and received power thresholds coupled with power control are used to maintain performance, without the need for intra-cell handoffs. It is shown that the schemes reduce call dropping and increase capacity compared to those using fixed transmitter power. The schemes are developed with the aid of mathematical analysis and a pictorial model. Results are presented which show that call dropping may be virtually eliminated in shadowing environments with the median transmitter power being reduced by 15 dB. The various call dropping mechanisms are discussed, and it is suggested that the residual level of call dropping is principally a result of multiple additional call arrivals close to an active link. Methods to make further reductions in the call dropping probability are also proposed.

This paper compares the performance of three techniques for providing tolerance to slow Rayleigh fading channels in cellular communication schemes: regular cyclic frequency hopping, adaptive modulation and coding, and dynamic carrier assignment (frequency jumping). It is assumed for the channels considered that the fading rates are slow enough that simple feedback adaptive techniques are applicable. The theoretical maximum performance of each scheme is evaluated as a function of the number of conversations supportable and the average received power required, and in terms of the effects on overall system capacity. Various combinations of these schemes are also evaluated, and found to provide greater advantages.

This correspondence examines the performance of block-coded modulation (BCM) at finite decoded bit error rates (BER). We consider the optimum geometric structure to optimize coding gain at finite BER, rather than asymptotic coding gain. We introduce the concept of the "row BER" and show that this structure may be implemented by a BCM scheme in which the row bit-error rates are equalized. We present a design procedure for such schemes, and show that significant improvements over conventional schemes are possible.

The effects of building geometric placement error have been considered both theoretically and using a two dimensional ray based model. The ray based model implements both reflection and diffraction and operates on a uniform, 1 km square grid of building data. Placement error is modelled by randomly displacing the building coordinates using a truncated Gaussian distribution. It has been found both theoretically and verified with results from a computer testbed that, when reflection predominates, the effect of angular error (rather than spatial error) is most significant as this causes rays to deviate away from their true route. It has been found that close to the transmitter, with an RMS deviation of 2.0 m in the building vertex position, that path loss peaks, caused by reflection, and corresponding path loss "nulls" can be moved up to 50 m.

This paper reports work carried out, largely within the COST 231 programme, on the uplink capacity of cellular multiple access schemes, and in particular CDMA and TDMA. It determines the probability density function of the interference in the various types of system, and hence estimates the capacities attainable with "industry standard" FEC codes of various rates. This shows that under the assumptions made, conventional CDMA can give a capacity about 65% greater than TDMA. The paper then introduces a new multiple access scheme called adaptive TDMA (A-TDMA) which adapts the code rate to the interference conditions encountered. A proposed A-TDMA system is outlined, using a packet reservation multiple access (PRMA) protocol, and an initial capacity estimate is given, and compared with the conventional schemes. The estimated spectral efficiency obtained is more than twice that of conventional CDMA.

We present bounds and estimates of the uplink spectral efficiency of cellular systems employing various multiple access schemes, in particular TDMA and CDMA in conjunction with FEC coding. We determine the cumulative distribution function of co-channel interference using a Monte Carlo technique and use this in conjunction with Shannon's (1949) bound on channel capacity to obtain upper bounds. Estimates are also obtained using simulated performance of practical codes. We show that coded TDMA with 100% re-use gives a greater capacity than with cluster size 3, and that CDMA with voice activation has approximately twice the capacity of either. Adaptive TDMA is identified as promising scheme for further capacity improvement.>

The capacity of a bandlimited phase-only modulated system in additive white Gaussian noise is calculated, where the phase is not restricted to a finite alphabet and the demodulator supplies only phase measurements. The results match a known asymptote at high signal-to-noise ratios and form an upper limit on the capacities of MPSK for finite M.>