This work considers a code division multiple access (CDMA)-based femtocell system where a fixed set of subscribed users communicate simultaneously to a femtocell access point (FAP) in an asynchronous fashion during the uplink. The main goal of this paper is to present an augmentation protocol for the physical layer of the CDMA2000 femtocell standard with focus on the multiple access interference (MAI) suppression. The above-closed access femtocell uses a unique set of cyclic orthogonal binary codes to eliminate the MAI caused by packet collisions. This property ensures that the time and data rate asynchronicity of active nodes in a femtocell produces a zero MAI situation at the FAP. The work investigates the optimality and the effectiveness of such codes in femtocells from the link bit error rate performance in a practical Rayleigh-fading environment, where Kalman filtering is used at the FAP for the channel estimation. Theoretical findings are verified by simulation evaluations and it is shown numerically a significant improvement in the performance of the proposed scheme when compared with conventional non-cyclic orthogonal codes in a Rayleigh-fading channel in the asynchronous femtocell.

The recent explosive growth of voice over IP (VoIP) solutions calls for accurate modelling of VoIP traffic. This study presents measurements of ON and OFF periods of VoIP activity from a significantly large database of VoIP call recordings consisting of native speakers speaking in some of the world's most widely spoken languages. The impact of the languages and the varying dynamics of caller interaction on the ON and OFF period statistics are assessed. It is observed that speaker interactions dominate over language dependence which makes monologue-based data unreliable for traffic modelling. The authors derive a semi-Markov model which accurately reproduces the statistics of composite dialogue measurements.

Most of the earlier approaches for frequency-hopping (FH) signals sorting with a single sensor do not adapt to synchronous network, whereas the multiple-sensor-based algorithms request the number of sensors must be more than that of signals. Since the number of sensors is limited in many practical applications, it is important to sort synchronous or asynchronous FH networks with as little as possible sensors. This study introduces the underdetermined blind source separation (UBSS) algorithm to solve this problem. Considering the time–frequency (TF) sparsity of FH signals, the problem is formulated as one of UBSS based on sparse TF representation. First, an improved k-means clustering algorithm is developed to estimate the mixing matrix, according to the TF properties of FH signals. Secondly, to separate more signals overlapped in the TF domain using given sensors, an improved subspace-based algorithm utilising the information of the comparative power is proposed. In the proposed method, the sparsity condition of the sources in the TF domain is relaxed, and the number of FH signals that exist at any TF point simultaneously is allowed to equal that of the sensors. Simulations demonstrate that the proposed method can separate FH signals efficiently and outperforms the previous methods.

Since joint source-channel decoding is capable of exploiting the residual redundancy in the source signals for improving the attainable error resilience, it has attracted substantial attention. In this treatise, the authors study iterative source-channel decoding (ISCD) aided video communications, where the video signal redundancy is modelled by a first-order Markov process. Firstly, the authors derive reduced-complexity formulas for the first-order Markov modelling (FOMM) aided source decoding. Then they propose a bit-based iterative horizontal–vertical scanline model (IHVSM) aided source decoding algorithm, where a horizontal and a vertical source decoder are employed for exchanging their extrinsic information using the iterative decoding philosophy. The iterative IHVSM aided decoder is then employed in a forward error correction (FEC) encoded uncompressed video transmission scenario, where the IHVSM and the FEC decoder exchange softbit-information for performing turbo-like ISCD for the sake of improving the reconstructed video quality. Finally, the authors benchmark the attainable system performance against a near-lossless H.264/AVC video communication system and the existing FOMM-based softbit source decoding scheme. The authors simulation results show that E_b /N ₀ improvements in excess of 2.8 dB are attainable by the proposed technique in uncompressed video applications.

The authors investigate the relay-aided multicell multiple-input–multiple-output (MIMO) cellular network by comparing both the signal forwarding and interference forwarding relaying paradigms, each employing the adaptive MIMO relay scheme. The spectral, energy and economic efficiency values are utilised as key performance metrics. Furthermore, both radio frequency and circuit power consumption are considered in the energy calculation. They demonstrate that there is a tradeoff between spectral and energy efficiency. Thus, economic profitability is used to find a balance in the tradeoff as profitability is important to the long term deployment of a scheme. They introduce the economic efficiency metric which considers the inherent tradeoff as a complementary performance measure to obtain maximum economic profitability while maintaining gains in both spectral and energy efficiency.

This study extends an algorithm, previously proposed by the present authors, for ‘linear minimum-mean-squared error’ estimation of phase noise of (possibly) temporal non-stationarity, large magnitude, ‘non’-identical increments that have a Levy distribution, of which the Wiener distribution represents a special case. This estimator-taps may be pre-set to any number, may be pre-computed offline with no matrix inversion, based on the prior knowledge of only the signal-to-(additive)-noise ratio and the phase-noise's characteristic function. That estimator may be set to various degrees of latency. This is here generalised to allow observables at irregular time-instants (e.g. because of the irregular placement of pilot symbols in the transmitted waveform), under which the phase-noise increments become non-identically distributed. This study handles this more complicated scenario.

This work addresses an optimal pre-equalisation scheme to provide power and phase compensation in multi-carrier code division multiple access wireless systems under quality of service (QoS) restrictions. Two assignation schemes are studied: independent and uniform pre-equalised transmission (IPT and UPT) per subcarrier. First, the QoS was quantified in terms of the signal-to-interference noise ratio (SINR) after using a linear detector in the receiver. The SINR expressions for IPT and UPT were explicitly derived, to highlight their dependence on the pre-equalisation factors. These relations are exploited to derive analytical procedures to obtain the required pre-equalisation factors that satisfy an objective SINR per active user. The author's proposal for IPT achieves the lowest power while requiring a simple detector independent of the channel state information (CSI). For IPT, two minimum norm solutions are derived by translating the SINR restrictions into linear equations: one based on spectral factorisation, and a second one based on a simultaneous zero-forcing effect plus an energy scaling. On the other hand, for UPT, multi-user detectors like zero-forcing (ZF) and minimum-mean-square error (MMSE) have to be employed at the receiver to achieve a solution to the QoS requirements. In the numerical evaluations, IPT attained roughly a 2.5–3% reduction in the overall transmission power compared to UPT with ZF and MMSE by varying the objective SINR and noise variance. Although this reduction is further expanded as the number of active users increases, achieving a reduction in transmission power larger than 50% for a fully-loaded system.

A novel optimisation procedure for the location of the transmitter in 3 × 3 multiple input multiple output wireless local area network wireless communication systems is presented. The optimal antenna location for maximising the channel capacity is searched by particle swarm optimiser (PSO) and asynchronous particle swarm optimisation (APSO). There are two different receiver locations considered in the simulation. These two cases are: (i) the transmitter is mobile in the whole indoor environment and the receivers are located on the tables spaced in intervals uniformly distributed (ii) the transmitter is mobile and the receivers are space in uniformly distributed intervals in the whole indoor environment. Numerical results have shown that the proposed PSO and APSO methods are transmit antenna location is optimised to increase channel capacity. The APSO has better optimisation results compared with the PSO and numerical results also show that the APSO outperforms the PSO in convergence speed.

An adaptive-weighted multibit-flipping decoding algorithm, which flips multiple bits in each iteration, is proposed for low-density parity-check codes. The multibit-flipping criterion is devised based on the least reliable positions and ordered statistics, in which the flipping threshold is dynamically adapted during the decoding process. The proposed decoder converges faster and provides better performances than the conventional weighted bit-flipping and multibit-flipping decoders. Simulation results demonstrate that the proposed algorithm achieves a good tradeoff between performance and complexity.

This study is concerned with the application of non-binary low-density parity-check (NB-LDPC) codes to binary input inter-symbol interference channels. Two low-complexity joint detection/decoding algorithms are proposed. One is referred to as max-log-MAP/X-EMS algorithm, which is implemented by exchanging soft messages between the max-log-MAP detector and the extended min-sum (EMS) decoder. The max-log-MAP/X-EMS algorithm is applicable to general NB-LDPC codes. The other one, referred to as Viterbi/GMLGD algorithm, is designed in particular for majority-logic decodable NB-LDPC codes. The Viterbi/GMLGD algorithm works in an iterative manner by exchanging hard-decisions between the Viterbi detector and the generalised majority-logic decoder (GMLGD). As a by-product, a variant of the original EMS algorithm is proposed, which is referred to as µ-EMS algorithm. In the µ-EMS algorithm, the messages are truncated according to an adaptive threshold, resulting in a more efficient algorithm. Simulations results show that the max-log-MAP/X-EMS algorithm performs as well as the traditional iterative detection/decoding algorithm based on the BCJR algorithm and theQ-ary sum–product algorithm, but with lower complexity. The complexity can be further reduced for majority-logic decodable NB-LDPC codes by executing the Viterbi/GMLGD algorithm with a performance degradation within one dB. These algorithms provide good candidates for trade-offs between performance and complexity.

The authors propose a generalised framework that analytically compares different sub-carrier allocation (SA) or sub-channelisation schemes (such as interleaved SA (ISA), localised SA (LSA) or hybrid schemes) in uplink (UL) orthogonal frequency division multiple access (OFDMA). The ultimate goal of the proposed framework is to systematically determine the best SA scheme among the considered candidates for a given condition of inter-user frequency offsets (IUFOs) and the target bit error rate (BER). As an illustration, two typical SA schemes are considered, that is, ISA and LSA for comparison. First, based on the well-known fact that multiple access interference by IUFO and frequency diversity gain are both dictated by the employed SA scheme, the authors propose a semi-analytic approach to derive coded BER curve formula as a function of frequency offset bound (FOB) for each scheme. Then, the signal-to-noise ratio gain of ISA over LSA for various target BERs and FOBs is derived. Finally, the cutoff FOB over which ISA obtains worse than LSA is obtained and its functional relationship with the target BER is investigated. By following the overall procedure in the proposed framework, the best SA scheme among the various SA candidates for the general UL OFDMA systems with arbitrary system parameters can be chosen.

Multiple-input–multiple-output (MIMO) wireless technology is a viable option likely to be able to meet the demands of the ever-expanding mobile networks. For MIMO system, channel estimation is still a challenging area due to several difficulties. Soft-computational approaches can be additions to the list of traditional methods of MIMO channel modelling primarily because these tools, for their ability to learn, are better placed to use channel side information for improved performance. One of the viable means of such innovative channel estimation is the use of the artificial neural network (ANN) in a feedforward format known as multi-layer perceptron (MLP). But as these ANNs prove to be suitable for static and slowly varying cases, time-varying MIMO channels are modelled using modified MLP with temporal attributes developed using finite impulse response (FIR) and infinite impulse response (IIR) blocks in place of the synaptic links. Six sub-classes of each of the FIR-MLP and the IIR-MLP are formulated, which show better performance than the conventional MLP in modelling the MIMO channels.

Random beamforming (RBF) has received much attention recently in downlink beamforming because of its simple structure, low-feedback load and same throughput scaling as that obtained using dirty paper coding at the transmitter. In this study, the authors analyse the performance of RBF for cognitive downlink multi-antenna system in terms of the throughput of the secondary network. The authors consider a secondary broadcast station with multiple antennas utilising the licensed spectrum of each primary receiver to broadcast information to multiple secondary users (SUs) simultaneously, as long as the interference power inflicted at each primary receiver is less than a predefined threshold. Firstly, they derived the secondary network closed-form throughput approximation of a single-beam RBF by exploiting extreme value order statistics. Then, closed-form approximation for secondary network throughput on multiple-beam RBF is presented. Simulation results verify the validity of the authors approximation results analysis even with fewer SUs.

Relay selection has been considered as an effective method to improve the performance of cooperative communication. However, the channel state information (CSI) used in relay selection can be outdated, yielding severe performance degradation of cooperative communication systems. In this study, the authors investigate how to select relays under outdated CSI in an amplify-and-forward cooperative communication system to improve its outage performance. The authors adopt maximum a posteriori (MAP) estimation to predict the actual signal-to-noise ratio (SNR) of each relay during data transmission and propose a single-relay selection (SRS) strategy based on the MAP estimation (SRS-MAP). To reduce the computational complexity, we approximate the a posteriori probability density of SNR and obtain a closed form of the predicted SNR. Simulation shows that SRS-MAP outperforms the relay selection strategies given in the literature. In order to further improve the outage performance, a new multiple-relay selection (MRS) method for outdated CSI is proposed, and by applying it to existing SRS strategies the corresponding MRS strategies are obtained. The authors find that the MRS strategies perform much better than their corresponding SRS ones and the MRS method improves the outage performance of cooperative communication system more effectively under outdated CSI than under non-outdated CSI.