Multi-hop relaying is well known to extend the range of wireless communications. However, the end-to-end performance of the multi-hop relaying channel degrades compared to that observed at the first hop. This performance degradation mainly arises due to: 1) half-duplex loss and 2) hopping or relaying loss. In this paper, we analyze the degradation in outage probability and ergodic capacity due to hopping loss in a multiple-input multiple-output (MIMO) dual-hop decode-and-forward relaying network over Rayleigh fading channels. In particular, we characterize analytically the performance degradation by deriving closed-form approximations of ergodic capacity and outage probability in the single-source single-relay single-user, single-source multiple-relay single-user, and single-source single-relay multiple-user topologies. These approximations also provide insights on how to overcome performance degradations due to hopping loss. Moreover, we show that cooperative relaying schemes can recover a significant portion of the hopping loss.

It is well-known that relaying can extend the communication range. However, the performance of the relaying network is inferior compared to a single-hop system where the destination is placed hypothetically at the relay. The gap between the single-hop and relay network, dubbed the multi-hopping or relaying loss, is studied in this paper. In particular, we investigate the increase in outage probability and the degradation in ergodic capacity incurred due to the multi-hopping loss in a dualhop multiple-input multiple-output decode-and-forward relaying network operating in the single-source single-relay single-user topology. Moreover, we show that a cooperative relaying scheme, called the best relay scheme, in the single-source K-relays single-user topology can recover a significant portion of the multi-hopping loss. In both topologies, we derive closed-form approximations for the outage probability and ergodic capacity using the well-known Gaussian approximation.

Multibeam satellite communication (SatCom) with full or aggressive frequency re-use is one of the most promising candidates for next-generation high throughput satellite systems. However, frequency re-use creates interbeam interference which needs to be managed using multiuser precoding techniques in the forward link and multiuser detection techniques in the reverse link. This work considers the forward link of multibeam Sat-Com systems and proposes a novel zero-forcing (ZF) precoding technique that makes use of users' physical location and antenna radiation pattern available at the gateway. Contrary to conventional precoding techniques in multibeam SatCom systems, the proposed precoding technique does not require feedback from user terminals. Numerical results show that the proposed ZF precoder achieves higher ergodic capacity than the conventional ZF precoder. We provide a closed-form approximation for the ergodic capacity of the proposed ZF precoder under rain fading. We also provide a closed-form approximation for computing the moments of the rain fading attenuation which enables us to derive high and low signal-to-noise ratio (SNR) expressions of the ergodic capacity in closed-form. Furthermore, an upper bound on the ergodic capacity is obtained. Monte Carlo simulations are used to validate the accuracy of our analysis.

Stochastic routing offers a promising substitute to deterministic routing in wireless sensor networks, mainly due to its randomized nature. Still, most of the stochastic routing algorithms are heuristic, while the optimality for a given degree of randomness is difficult to find. In this paper, we propose a theoretical framework to find the optimal stochastic routing policy that maximizes the packet delivery ratio for a given degree of randomness in routing. Our model consists of directed acyclic networks with unreliable communication links. The degree of randomness is quantified by the global entropy of routing. By employing the Lagrangian approach, a simple iterative algorithm to find the optimal stochastic routing policy is proposed. This can be used as a benchmark for performance comparison of stochastic routing algorithms.

In systems with parallel analogue-to-digital converters (ADC), diversity combining can improve the signal to noise ratio (SNR) of the digitised signal. We consider a novel architecture, where the parallel ADCs operate on differently attenuated signals, in conjunction with maximal ratio combining and gain weighted combining. Both schemes reduce the effective quantization noise and provide significant SNR improvements over a single ADC and signal averaging, which takes the unweighted average of the ADC output signals. The key to achieving these SNR gains is to carefully select branch attenuations that lead to negative correlation of the quantization noise across branches.

We develop an estimator of time offset (or time-of-arrival) of a transmitted communications signal that contains both pilot symbols, known to the receiver, and data symbols, unknown to the receiver. We focus on signalling constellations that have symbols lying on the complex unit circle, such as M-ary phase shift keying (M-PSK). We describe an algorithm for computing the estimator that requires O(L log L) operations in the worst case, where L is the number of transmitted symbols. Our estimator integrates information from the pilot symbols more effectively than popular estimators from the literature that usually split estimation into two subproblems called symbol timing and frame synchronisation. Our estimator combines these subproblems into a single operation, that of estimating time offset. We hypothesise that our estimator will be statistically more accurate. Monte-Carlo simulations support this hypothesis.

We consider the estimation of signal amplitude, time offset, and the parameters of a polynomial-phase signal from a continuous-phase modulated (CPM) signal that contains both unknown data symbols and known pilot symbols. Transformation of the polynomial-phase signal into an orthogonal basis allows us to derive the modified Cramér-Rao bounds (MCRB) for the problem of vector-parameter estimation in closed form. Numerical results demonstrate that the achievable estimation accuracy significantly depends on the burst structure and highlight the need for properly designed pilot sequences. Since our bounds are easy to evaluate, they can aid the design of pilot and burst configuration for CPM systems.

We consider least squares estimators of carrier phase and amplitude from a noisy communications signal. We focus on signaling constellations that have symbols evenly distributed on the complex unit circle, i.e., M-ary phase shift keying. We show, under reasonably mild conditions on the distribution of the noise, that the least squares estimator of carrier phase is strongly consistent and asymptotically normally distributed. However, the amplitude estimator is not consistent, but converges to a positive real number that is a function of the true carrier amplitude, the noise distribution and the size of the constellation. The results of Monte Carlo simulations are provided and these corroborate the theoretical results.

Improving convergence rate is one of the major challenges in stochastic routing for wireless sensor networks. Randomized approach of node selection results in a higher convergence time which is not desirable for delay-sensitive applications. In [4], we proposed a novel routing algorithm that performs better than the existing methods in terms of the convergence rate. In this paper, we analyze the basic concept behind our proposed routing algorithm, improving the rate of routing out of the neighborhood for any given node, which will improve the convergence rate. Furthermore, we derive bounds for transition probabilities which will improve the convergence rate with reference to the random walking strategy and formulate a closed-form expression for optimal transition probability selection.

The use of discrete Hartley transform (DHT) pre-coding was recently shown to achieve peak to average power (PAPR) reduction for OFDM. In this paper, we show that DHT precoding also achieves full diversity. We consider the sparse matrix formed by the combination of DHT and the discrete Fourier transform (DFT) and propose a receiver configuration that minimizes complexity. Furthermore, we present a detailed account of the system complexity to show that it is slightly more than uncoded conventional OFDM. Also, since this system saves the complexity required for achieving diversity gain and reducing the peak to average power (PAPR), it reduces the system complexity when the PAPR reduction and diversity techniques are taken into account for conventional OFDM. We analytically show that this system achieves full diversity and then verify it using simulation results. Simulations results also show that the system has a substantial improvement in bit error performance over conventional OFDM.

A major challenge in wireless sensor networks (WSN) is that spatially distributed nodes need to achieve a global task in a completely decentralised manner. Motivated by the fact that optimisation problems in WSNs can often be formulated as Markov random field (MRF) energy minimisation, a general MRF-based framework for the design of distributed WSN algorithms was proposed recently. Building upon this framework and the theory of dual decomposition, we develop a novel WSN optimisation algorithm that is applicable to a wide variety of network problems such as routing and power control. Our algorithm is completely distributed and is characterised by simple, deterministic and identical per-node processing. Routing of control information through the network is avoided as nodes exclusively process information from their local neighbourhoods. We apply our algorithm to a multiple access resource allocation problem and demonstrate rapid convergence to the global optimum.

This paper tackles the speech separation problem in a meeting room using a new acoustic beamforming method – adaptive blocking (AB) beamformer. The proposed method is an optimum beamforming with a structure similar to the generalized sidelobe canceller (GSC) structure, but simpler. Thus, it inherits the flexibility of GSC and functions well in dynamic environments. We investigate the performance of the proposed method through different experiments and compare the results with a GSC beamformer for minimum variance distortionless response (MVDR). The experimental setups include one wanted speaker, two interferers, air conditioner noise and uncorrelated sensor noise. AB provides improvement over MVDR-GSC.

Recently, a T-transform based multicarrier communication system with significant uncoded BER performance improvement over conventional OFDM in a Rayleigh fading channel was proposed. However, due to the involvement of Walsh Hadamard transform (WHT), the T-transform OFDM system does not satisfy the cyclic convolution property and hence fails to diagonalize the channel matrix, resulting in an enormous equalization complexity. In this paper, we propose a new receiver processing mechanism where the T-transform is replaced by two equivalent transforms and the equalization is carried out in between them. The new approach diagonalizes the channel matrix and single tap equalization is possible without any compromise in the performance. The detailed computational complexity of the proposed approach is also presented and compared with some other schemes.

In communication systems that use orthogonal frequency-division multiplexing and multiple transmit and receive antennas, beamforming (BF) is conventionally carried out on a subcarrier basis. The computational requirements are high as dedicated discrete Fourier transform (DFT) processors are needed for each antenna. Considerable complexity reductions can be achieved by symbol-wise BF, which performs the transmit and receive BF operations in the time domain, and therefore requires only one DFT processor per terminal. In this paper, we investigate symbol-wise BF for the mitigation of co-channel interference on spatially correlated channels, which are modelled with the Kronecker model. We show analytically that symbol-wise BF is the optimal BF scheme when the channel is frequency-flat or fully correlated, and present a novel iterative algorithm for the computation of the optimal antenna weights. Monte-Carlo simulations confirm that the relative performance loss of symbol-wise BF becomes negligible when approaching full correlation.

In MIMO-OFDM communications over channels subject to co-channel interference, beamforming (BF) is conventionally applied independently to all subcarriers. Whilst this approach maximises mutual information, it is highly computationally complex. Symbol-wise BF considerably reduces the complexity by carrying out BF in the time domain. In this paper, we generalise symbol-wise BF to take co-channel interference into account. Maximising the mutual information is infeasible in this case and instead, we propose a novel iterative algorithm that maximises the SINR before OFDM demodulation. Computer simulations show that the performance loss relative to subcarrier-wise BF reduces with decreasing frequency selectivity or increasing spatial correlation.

When realizing carrier frequency offset estimation at low signal-to-noise ratios, a typical feed-forward synchronization unit solely relies on known pilot symbols. The importance of the position of these pilot symbols within the burst has been elaborated on in the literature. In this paper, we discuss the importance of the pilot symbol constellation for iterative code-aided synchronization. Furthermore, we investigate the transmission order of data symbols for a turbo coded system with code-aided synchronization.