Abstract This paper investigates joint optimization of antenna selection and beamforming in multiple‐input multiple‐output simultaneous wireless information and power transfer systems with bidirectional communication. The downlink–uplink rate region is used as the performance metric. The formulated optimization problem is non‐convex mixed integer programming, which is challenging to solve. The problem is first converted into a form of a quadratically constrained quadratic program. Given fixed receive and transmit antenna sets at the energy harvesting device, the authors apply the semidefinite relaxation to obtain a convex problem for optimal beamforming which can be solved efficiently. It is proved that the semidefinite relaxation is tight. The authors solve the relaxed problem for every possible receive and transmit antenna sets and find the optimal solution by search. Moreover, a low‐complexity method to alleviate the computational complexity of the optimal solution by deriving effective heuristic algorithms for the beamforming and antenna selection is proposed. Simulation results demonstrate that both the optimal and the low‐complexity algorithms outperform the benchmark power splitting, when the circuit power consumption is sufficiently high or the number of receive antennas at the energy harvesting device is sufficiently large. Also, a near‐optimal performance can be achieved by the proposed low‐complexity method.

Fountain codes are promising forward error correction codes suitable for broadcast and multicast applications where many users with different capabilities are involved in the system. Fixed‐rate codes need a priori information about each channel to decide the best code rate and the code rate is usually chosen according to the worst channel to avoid an outage. Fountain codes are agnostic to the channel conditions and rateless. The rate is realised based on the channel conditions for users separately. Overlapped fountain codes were previously invented over the binary erasure channel to provide more degrees of freedom and better trade‐offs for the rateless‐coded system parameters. In this study, the authors show via analysis and simulations that overlapped fountain codes need fewer decoding steps in comparison with the conventional fountain codes. For example, overlapped fountain codes reduce the number of decoding steps/iterations of belief propagation decoder by even at a source length . They optimise the overlap selection probability of the overlapped fountain codes to maximise the code rate and/or minimise the complexity. At source length, , the proposed analytical and simulation studies show that the highest code rate and lowest average complexity are achieved at an overlap selection probability .

Erasure codes for distributed storage systems (DSS) are required to offer systematic encoding, low repair locality, low encoding/decoding complexity, and low decoding/storage overhead. However, the information theoretical bounds have shown that all these metrics might need to be carefully traded-off with one another. In this paper, we consider systematic Fountain codes with belief propagation (BP) decoding for massive scale DSSs. Analyzing the role of some degrees in the BP decoding process, we propose using the truncated Poisson distribution (TPD) for encoded symbol degrees. Identifying encoded symbol redundancy as a factor that degrades decoding overhead, we derive the probability of redundancy during the BP decoding process and use this as a tool for determining the Poisson parameter. Our proposed solution nicely addresses the first three DSS metrics with a slight toll on storage/decoding overhead. Through simulations, we show that the decoding overhead performance of the proposed scheme exhibits significant improvement over some existing Fountain code degree distributions in the literature. For instance, at a decoding overhead of 60%, we achieve a data loss probability closely approaching 10-4, while other Fountain codes compared are about a factor of 102higher.

This study introduces a novel framework and analysis tool to monitor the evolution of the ripple size during the Luby‐transform (LT) decoding process. It provides a closed‐form probability expression to statistically describe the behaviour of the ripple size at each step of the decoding. The probability function is conditioned on the size of the ripple in the previous step, the number of recovered source symbols and the encoded symbols' degree distribution. The authors further derive a closed‐form expression for the ripple size after new encoded symbols are received by a decoder with an empty ripple. This relates to the activation of belief propagation decoding attempts once premature terminations occur. They validate their analyses through numerical examples of an LT‐coded system. The results show that their analyses precisely coincide with the numerical results.

Luby transform (LT) codes have received less attention in larger non‐binary fields. Robust soliton distribution (RSD) was designed to provide universal optimality over the binary erasure channel in terms of minimising the overhead. In this study, the authors introduce a fundamental degree distribution (FDD), which when used with non‐binary LT codes, outperforms their binary counterparts using the RSD in terms of error rate and realised code rate. For instance, over an additive white Gaussian noise (AWGN) channel at of 12 dB and a rateless criteria (zero error probability), a non‐systematic 4‐ary LT code using the FDD can achieve a code rate of 0.75, compared to its binary counterpart which only achieves a code rate of 0.7.

The development of smart platforms in the Internet-of-Things (IoT) paradigm requires a number of technological advances to go hand in hand. IoT devices and entities have very diverse set of capabilities in terms of memory, power, and processing and are connected via a wide range of links with various qualities and capacities. This work focuses on the design of state-of-the-art data transmission methodology with arguably the highest level of flexibility and adaptability. We present a novel fountain-based encoding technique using overlapped generations of Luby-Transform (LT) codes. The proposed overlapped LT (OLT) codes achieve significant gains in BER and/or code rate. They are highly energy-efficient, scalable, and robust. Our analysis shows in particular that by using OLT codes, we can modify the fountain degree distribution such that it does not contain degree-one packets starting from the second generation. Thus, we introduce new degree distributions to improve the performance of OLT codes; the new scheme is referred to as smart OLT (SOLT). Simulation results are provided to show the improvements of OLT and SOLT codes in AWGN channel in terms of error rate. For example, SOLT codes can achieve the same error performance as LT codes, but they require smaller transmission overhead, for instance, at SNR of 9 dB and error rate of 10-5, SOLT codes require a code rate of 0.476 while LT codes require a code rate of 0.417.

Fountain codes were introduced to provide high reliability and scalability and low complexities for networks such as the Internet. Luby‐transform (LT) codes, which are the first realisation of Fountain codes, achieve the capacity of the binary erasure channel (BEC) asymptotically and universally. Most previous work on single‐layer Fountain coding targets the design via the right degree distribution. The left degree distribution of an LT code is left as a Poisson to protect the universality. For finite lengths, this is no longer an issue; thus, the author's focus is on designing better codes for the BEC at practical lengths. Their left degree shaping provides codes outperforming LT codes and all other competing schemes in the literature. At a bit error rate of 10 −7 and packet length k = 256, their scheme provides a realised rate of 0.6 which is 23.5% higher than that of Sorensen et al. ’s decreasing‐ripple‐size scheme.

The use of multiple description (MD) provides a reliable communications solution over packet loss channels; the polar source coding takes advantage of reasonable complexities in both the encoder and decoder sides. In this study, a polar MD coding is introduced for the binary input sequence with Hamming distortion in which the central decoder is aided by a common description from the encoder. The algorithm for code construction is studied. The performance evaluation demonstrates the effectiveness of the proposed system for MD with polar coding. In addition, the effects of design parameters have been studied.

In this paper, we introduce a method of hyperspectral unmixing in the linear mixing model with the given library of the constituent materials. The proposed algorithm employs an arctan function to approximate the l0norm in the minimization problem. This approximation makes the objective function smooth, facilitates the convergence and results in reduced reconstruction errors. We evaluate the proposed method and compare it with other methods via simulation. This reveals that the proposed method outperforms the state-of-the-art methods and results in higher reconstruction signal-to-noise-ratio.

A team of Unmanned Aerial Vehicles (UAVs) is used for the dynamic encirclement of a moving target in simulation. The encirclement tactic is defined for the situation in which a target is isolated and surrounded by a group of UAVs. It may be employed by a team of UAVs to neutralize the target and restrict its movement. A combination of decentralized Linear Model Predictive Control (LMPC) and Feedback Linearization (FL) is implemented on the team of UAVs in order to accomplish dynamic encirclement around a moving target. The main contribution of this paper lays in the application of LMPC and FL to solve the problem of encirclement of a moving target using an autonomous team of UAVs in simulation.

Error‐prone patterns have been extensively studied for low‐density parity‐check codes yet they have never been fully explored for generator‐based ‘Fountain codes’. It is shown here that these phenomena are related to certain combinatorial structures within the Tanner graph (TG) representation of the code, previously termed absorbing sets. The authors systematically define the ‘absorbing sets’ in the generator‐based TG of a code. They then demonstrate how these substructures are damaging to the ‘realised rate, delay’ and ‘decoding cost’ of Fountain codes particularly at low error rates. They further analyse the existence probability of certain absorbing sets and propose a new encoder/decoder pair forming a new family of Fountain codes. The authors experimental results show that these new codecs lead to improvements in all system features. Typical gains for Luby‐transform codes include 20 % reduction in the decoding complexity and simultaneous coding gains of 0.6 and 0.9 dB at bit error rates of 10 − 5 and 10 − 6 , respectively. As such, this work takes a step towards better rateless code design and construction.

We analyze the performance of multiple input/multiple output (MIMO) communications systems employing spatial multiplexing and zero-forcing detection (ZF). The distribution of the ZF signal-to-noise ratio (SNR) is characterized when either the intended stream or interfering streams experience Rician fading, and when the fading may be correlated on the transmit side. Previously, exact ZF analysis based on a well-known SNR expression has been hindered by the noncentrality of the Wishart distribution involved. In addition, approximation with a central-Wishart distribution has not proved consistently accurate. In contrast, the following exact ZF study proceeds from a lesser-known SNR expression that separates the intended and interfering channel-gain vectors. By first conditioning on, and then averaging over the interference, the ZF SNR distribution for Rician-Rayleigh fading is shown to be an infinite linear combination of gamma distributions. On the other hand, for Rayleigh-Rician fading, the ZF SNR is shown to be gamma-distributed. Based on the SNR distribution, we derive new series expressions for the ZF average error probability, outage probability, and ergodic capacity. Numerical results confirm the accuracy of our new expressions, and reveal effects of interference and channel statistics on performance.

In this paper, we examine the marriage of Fountain coding and network coding (NC). Fountain codes are capacity achieving erasure codes designed for point-to-point transmissions. NC is a throughput-optimal data dissemination technique, but its high-complexity decoding makes it unattractive for applications where limited resources are available. In this paper, we consider Fountain network coding to take advantage of efficient fountain decoders. Protocols such as Soliton-like rateless coding (SLRC) have previously addressed this issue, yet the re-encoding at the relay is expensive while there is still room for improving the performance. Extending SLRC, we propose the Improved Soliton-like Rateless Coding (ISLRC) protocol, where the relay is designed to perform distribution shaping given limited resources. ISLRC preserves the same properties as SLRC, but also makes the aggregate degree distribution more efficient for Fountain decoding. We analyze ISLRC's degree distribution and perform an asymptotic error analysis for the case where resources are most scarce. The ISLRC scheme is compared against other existing schemes. Simulation results show that even under the worst-case scenario of ISLRC, better performance can be achieved compared to SLRC and other existing schemes.

For the binary erasure channel, Luby Transform (LT) and Raptors codes have been shown to achieve capacity by carefully designed degree distributions for multicasting scenarios. Generalizing fountain codes to multihop networks requires transport nodes to perform network coding (NC). However, if intermediate nodes perform decentralized NC blindly, the statistical properties imposed by the fountain code are lost, and thus, a Gaussian elimination decoder must be used at the sink at the cost of significant increase in complexity compared to a belief propagation (BP) decoder. Addressing this problem, in this paper, we propose a new protocol, namely Soliton-like rateless coding (SLRC), by exploiting the benefits of fountain coding and NC coding over a Y-network. Ensuring key properties of the fountain code are preserved; BP can be effectively applied when transport nodes perform NC. Additionally, the proposed coding protocol is resilient to nodes churn rates. The SLRC scheme is evaluated against buffer-and-forwarding, and the distributed LT (DLT) codes; SLRC exhibits a 5% reduction in overhead compared to the state of the art DLT code at high decoding success rates. Simulations show that the proposed scheme preserves the benefits of NC and fountain coding.

Soft iterative detection and decoding techniques have been shown to be able to achieve near-capacity performance in multiple-antenna systems. To obtain the optimal soft information by marginalizing over the entire observation space is intractable: one must resort to suboptimal methods to implement such receivers. Although list-type detectors such as those founded upon the sphere decoding algorithm provide outstanding error performance, issues such as the optimal initial sphere radius, optimal radius update strategy, and their highly variable computational complexity are still unresolved. In this paper, a new detection scheme is proposed addressing the above issues. Our simulation results show that by sacrificing less than 2 dB at error rate of 10-5, we are able to gain up to 38.6% complexity reduction as well as a detector structure that is more suitable for practical system implementation.

Network coding notions promise significant gains in wireless networks' throughput and quality of service. Future systems employing such paradigms are known to be also highly scalable and resilient to node failure and churn rates. We propose a simple framework where a single relay listens to two nodes transmitting simultaneously over the same band in the presence of Nakagami-m fading. For this multiple-access channel (MAC), we derive in closed-form the exact bit error rate of antipodal signaling with maximum-likelihood detection. As the MAC is the bottleneck in error of the overall system, this provides a good performance measure of the aggregate architecture. Using the new error expressions derived, we then propose a simple closed-loop cooperation strategy where via a ternary feedback from the relay node, significant gains in signal to noise ratio at the relay can be achieved. Our novel error analysis method is applicable to a number of other systems such as the vertical Bell labs spacetime (V-BLAST) scheme and synchronous multi-user systems.

The maximum-likelihood (ML)-detected vertical bell-labs layered space-time (V-BLAST) architecture over a Nakagami-m fading channel is considered. This fading model encompasses many fading scenarios as special cases (e.g., Rayleigh). The ML detection of BLAST systems waives the requirement of not having smaller number of receive antennas than transmit antennas: a primary limitation using other sub-optimal linear processing receivers. Using exact BER expressions, a two-by-one antipodal V-BLAST system is optimized by phase precoding requiring only a single bit of feedback from the receiver. Numerical results demonstrate that the proposed single-bit feedback scheme improves the BER performance dramatically.

The metric expression for a generic linear space-time block code (STBC) is studied using a different approach to vectorization and a new representation of the metric. The new representation lends itself to a simple measure of reliability based on the sum of inner products, and provides a quantifiable definition for minimum distance of a STBC. This provides the framework for a new family of near-maximum-likelihood (ML) and ML decoding algorithms. It also has applications in the development of optimality test criteria for STBCs, as well as in the design of STBCs with low decoding complexity.

For the large family of quasi-orthogonal space-time block codes, it is not clear when is best to decode using an exhaustive search, and when the sphere decoding algorithm (SDA) should be applied. In investigating this practical issue, a generic maximum-likelihood metric expression is utilized which is more conducive to lowering the decoding complexity. It is then shown that for smaller constellations and/or number of transmit antenna, the complexity advantage of smart exhaustive search in comparison with sphere decoding can be significant.

This paper addresses the following question: for the large family of quasi-orthogonal space-time block code (QOSTBCs), when is it best to decode using an exhaustive search, and when should the sphere decoding algorithm (SDA) be applied? First, a simple and intuitive generic metric expression for QOSTBCs is proposed. The new metric expression makes it easier to find the simplified and partially decoupled metric than if working from the Forbenius norm. A new rate-one full-diversity 8 antenna QOSTBC is then constructed that has lower decoding complexity than that in [3]. Finally, the question of when to use the SDA is considered.

Space-time codes can be decoded by the sphere decoding (SD) algorithm to reduce the complexity and retain maximum-likelihood (ML) performance. In this letter, the ML metric of quasi-orthogonal space-time block codes is written into two independent Euclidean norms, thus SD can be applied to each function independently. The new scheme reduces the complexity by at least 85% for systems with four or more transmit antennas, compared with the conventional SD algorithm.

The error probability of maximum-likelihood (ML) soft-decision decoded binary block codes rarely accepts nice closed forms. In addition, for long codes, ML decoding becomes prohibitively complex. Nevertheless, bounds on the performance of ML decoded systems provide insight into the effect of system parameters on the overall system performance as well as a measure of goodness of the suboptimum decoding methods used in practice. Using the so-called Gallager's first bounding technique (involving a so-called Gallager region) and within the framework of tangential sphere bound (TSB) of Poltyrev, we develop a general bound referred to as the generalized TSB (GTSB). The Gallager region is chosen to be a general hyper-surface of revolution (HSR) which is optimized to tighten the bound. The search for the optimal Gallager region is a classical problem dating back to Gallager's thesis in the early 1960s. For the random coding case, Gallager provided the optimal solution in a closed form while for the nonrandom case the problem has been an active area of research in information theory for many years. We prove that for a sphere code, the optimal HSR within the proposed GTSB is a hyper-cone. This will climax to the TSB of Poltyrev, one of the tightest bounds ever developed for binary block codes, and therefore terminates the search for a better Gallager region in the groundwork of the GTSB.

Performance evaluation of maximum-likelihood (ML) soft-decision-decoded binary block codes is usually carried out using bounding techniques. Many tight upper bounds on the error probability of binary codes are based on the so-called Gallager's first bounding technique (GFBT). The tangential sphere bound (TSB) of Poltyrev which has been believed for many years to offer the tightest bound developed for binary block codes is an example. Within the framework of the TSB and GFBT, we apply a new method referred to as the "added-hyper-plane" (AHP) technique, to the decomposition of the error probability. This results in a bound developed upon the application of two stages of the GFBT with two different Gallager regions culminating in a tightened upper bound beyond the TSB. The proposed bound is simple and only requires the spectrum of the binary code.