To keep up with the dramatic proliferation of mobile traffic, the fifth-generation (5G) systems adopt the millimetre-wave (mmWave) frequency band together with a large-scale antenna array. Although the use of large-scale antenna array can effectively solve the problem of severe signal attenuation at high frequencies, it also derives other issues. For example, the system complexity on spatial domain becomes computationally prohibitive, because the system has to estimate all the channels of each antenna. Also, the ever-growing data rates make the frequency selectivity of channels worst in the spatial domain. Recently, utilising the sparse characteristics of the mmWave band, beam-domain signal processing has drawn increasing interest for future 5G systems. In this study, the authors design multi-user data detection for the mmWave communication on beam domain. To effectively reduce the design complexity, they exploit the salient feature of channel sparsity to propose beam-channel selection and user grouping. Results indicate that the beam-channel selection is a critical step in the design of 5G systems since it can significantly decrease the complexity while maintaining the throughput. User grouping allows us to independently design detectors with lower complexity. Results show that the designed detectors can achieve a good trade-off between throughput and complexity.

Heterogeneous cellular networks (HCNs) present an attractive solution to increased demands in mobile user capacity. Comprehensive studies have been conducted in stochastic geometric models that represent the relatively random placement of base transmitting stations (BTSs) operating at different power levels. This study considers the design of two-tier HCNs for which picocell BTSs from the second tier are separated simultaneously from each other and from their tier-1 macrocell counterparts. These separations, introduced in detail in the study, are termed the co-tier and cross-tier separations, with each parameter characterised by a minimum distance separation. Subsequently, expressions are obtained for distance distributions of BTSs from specific tiers to typical users, followed by conditional probabilities of association with each tier. We show that a minimum radius of association can be guaranteed for a tier-2 BTS based on the values of co-tier and cross-tier separations. Furthermore, we analyse the Laplace transform of interference to the typical user and the resultant formulae for coverage probability, and by extension, area spectral efficiency. Numerical results demonstrating the effect of co-tier and cross-tier separation on these performance parameters support the analysis and provide insights into cell planning based on this concept.

This paper investigates the secure performance of multi-antenna decode-and-forward (DF) relaying networks where the Nakagami-m fading channel is taken into account. In practice, the joint impact of residual transceiver hardware impairments (HIs) and channel estimation errors (CEEs) on the outage probability (OP) and intercept probability (IP) are taken into account. Considering HIs and CEEs, an optimal transmit antenna selection scheme is proposed to enhance the secure performance and then a collaborative eavesdropping scheme is proposed. More specifically, they derive exact closed-form expressions for the outage and intercept probabilities. To obtain more useful insights the asymptotic behaviours for the OP are examined in the high signal-to-noise ratio (SNR) regime and the diversity orders are obtained and discussed. Simulation results confirm the analytical derivations and demonstrate that: (i) As the power distribution coefficient increases, OP decreases, while IP increases; (ii) There exist error floors for the OP at high SNRs, which is determined by CEEs; (iii) The secure performance can be improved by increasing the number of source antennas and artificial noise quantisation coefficient, while as the number of eavesdropping increases, the security of the system is reduced; (iv) There is a trade-off between the OP and IP.

It is known that the acquisition of the complete channel state information at receivers is difficult in multiple-input multiple-output (MIMO) systems. Channel estimation error is unavoidable in practical applications. Under imperfect channel conditions, the channel estimate is directly applied to the equalisation process in the conventional minimum mean-square error (MMSE)-based turbo equalisation scheme. A few studies treat the channel estimation error as an independent component from the channel estimate and slightly enhanced performance is achieved. Unlike the existing work, the authors derive the MMSE-based iterative processing conditioned on channel estimate. Moreover, they note that in low-density parity check coded systems, the parity-check procedure is also involved. The pass in parity check indicates that the message bitstream is successfully recovered. This information can be utilised to reduce the overall computational complexity by degrading the MIMO size since the unknown parameters are reduced. By extending the analysis in a small-scale MIMO system to a large-scale one, they propose to utilise the normalised transmission power in the development. Numerical results show the proposed schemes outperform the existing schemes in terms of system bit error rate and computational complexity performance.

Mobile edge computing (MEC) is an innovative computing paradigm to enhance the computing capacity of mobile devices (MDs) by offloading computation-intensive tasks to MEC servers. With the widespread deployment of wireless local area networks, each MD can offload computation task to server via multiple wireless access points (WAPs). However, computation offloading can bring a higher system cost if all users select the same access points to offload their tasks. This study proposes a computation offloading strategy and resource allocation optimisation scheme in a multiple wireless access points network with MEC, which aims to minimise the system cost by providing the optimal computation offloading strategy, transmission power allocation, bandwidth assignment, and computation resource scheduling. The proposed scheme decouples the optimisation problem into subproblems of offloading strategy and resource allocation since the problem is NP-hard. The offloading strategy involves the optimal access point selection, which is analysed by the potential game. The resource allocation is obtained using Lagrange multiplier. The authors' analysis and simulation results verify the convergence performance of the proposed scheme, and the proposed scheme outperforms the simple resource allocation scheme and the offloading strategy optimisation scheme in terms of the system cost.

Next generation satellite systems are required to perform robust frame synchronisation in the presence of large frequency offsets at low carrier-to-noise ratios. Differential correlation-based frame acquisition is an appealing choice for these systems as it provides adequate performance with reasonable complexity. However, the theoretical characterisation of the multi-span differential correlation metric is still an open problem due to the fact that the correlation outputs with multiple delays are correlated. In this study, the authors derived novel closed-form approximations for the distribution of the multi-span differential correlation metric as well as the probabilities of miss-detection and false alarm. The close agreement between the simulated and theoretical receiver operating curves validates the analysis. This analysis can be used to characterise the performance of multi-span differential correlation-based frame synchroniser in terms of the number of delays without running computationally extensive Monte Carlo simulations.

Communication using relay node (RN) cooperation is attractive research interest since it supports wide area coverage and high data rates. RNdeployment problem in multiple users long-term evolution-advanced (LTE-A) network is a challenging issue. In this article, the RN deployment problem for a single carrier-frequency division multiple access uplink system is considered. The total energy efficiency (EE) and average EE for multi-user single-relay in the LTE-A network are considered as the performance measures to select the optimum position of RN. Two types of users are deployed: guaranteed bit rate and non-guaranteed bit rate when performing load balancing that can influence the selection of the optimum position of RN. Simulation results show that the EE is increased by 10% based on load balancing compared to unbalanced loaded network. The optimum position of RN at 75% of a cell radius towards the cell edge can significantly improve the EE.

The authors consider a scenario in which two wireless nodes communicate via a single access-point with two buffers using network coding. The access point first pairs each data packet being sent from each node and then performs the network coding operation. Packets arriving at the access point that are unable to be paired are instead loaded into one of the two buffers at the access point. When one of the buffers is empty and the other is not, network coding is not possible. When this happens, the access point must either wait for a network coding opportunity, or transmit the unpaired packet without coding. The authors analyse the trade-off that arises between decreasing packet delay time, and increasing efficiency of the wireless spectrum usage as double-ended push-out queueing theory problem under phase type data arrivals. They use this model to resolve the optimal threshold policy and analyse the performance of the system.

Communication industry demands the frameworks, which allow significant improvement in energy efficiency with spectral efficiency, however, these two do not always coincide and may even conflict sometimes in cognitive radio networks. In addition to this, the distributed network structures are preferred over centralised structures due to ease of deployment as well as less information exchange between the cognitive users which reduce the network-overhead. Therefore, in this study, the authors have proposed a framework to enhance the spectral as well as energy efficiency by exploiting the novel frame structure in the distributed cognitive radio networks. A self-scheduled multichannel-medium access control (SMC-MAC) protocol has been proposed in which the contention and sharing intervals are exploited for the efficient spectrum and energy utilisation. Moreover, the closed-form expressions of the spectral efficiency, power consumption and energy efficiency for the proposed SMC-MAC protocols are derived. Furthermore, the relation between energy and spectral efficiency for the proposed framework is also derived. The numerically simulated results are presented to validate the proposed work and Monte-Carlo simulations are performed for the random events in order to support the numerically simulated results.

Maximal ratio combining (MRC) diversity is fundamental in wireless communication theory and widely implemented in practice. There are limited results in the theory for the probability density function (PDF) of MRC diversity on Nakagami channels when the branches have unequal powers. In addition to being restricted, the known solutions are complex and in some cases unwieldy. Novel, complete solutions for the PDF of MRC signal-to-noise ratio (SNR), valid for integer values of the Nakagami fading parameter m and arbitrary branch powers, are derived. In addition to being solutions for the unsolved cases, the new solutions give different and much simpler expressions for the known restricted cases than previous solutions. The effects of branch channel power imbalances on the PDF of MRC and on the outage probability are investigated quantitatively. The new solutions are used to derive asymptotic large SNR performance measures for MRC diversity with unequal branch powers, insights not obtainable from previous solutions. The new solutions are used to derive intuitive simple approximations for the densities and distributions of MRC output signal power and amplitude, as well as for the outage probability. The approximations are shown to have excellent accuracies for power imbalances 30% and good accuracies for power imbalances 60%.

Users of the Tor anonymity system suffer from less-than-ideal performance, in part because circuit building and selection processes are not tuned for speed. In this study, the authors examine both the process of selecting among pre-built circuits and the process of selecting the path of relays for use in building new circuits to improve performance while maintaining anonymity. First, the authors show that having three pre-built circuits available allows the Tor client to identify fast circuits and improves median time to first byte (TTFB) by 15% over congestion-aware routing, the current state-of-the-art method. Second, they propose a new path selection algorithm that includes broad geographic location information together with bandwidth to reduce delays. In shadow simulations, 20% faster median TTFB and 11% faster median total download times over congestion-aware routing for accessing web page-sized objects were found. The proposed security evaluations show that this approach leads to better or equal security against a generic relay-level adversary compared to Tor, but increased vulnerability to targeted attacks. The authors explore this trade-off and find settings of the proposed system that offers good performance, modestly better security against a generic adversary, and only slightly more vulnerability to a targeted adversary.

The authors propose an optimal joint power control and multi-band spectrum sensing scheme for cognitive radio (CR) systems to increase the spectral efficiency and to overcome the spectrum-sensing errors, in the presence of primary user emulation attacker (PUEA). This optimisation problem is solved to maximise the opportunistic CR data rate under interference and power budget constraints. To solve the formulated optimisation problem, they convert it to a convex problem, and then derive an optimal strategy for joint power control and spectrum access in the considered CR system. They show that the optimal strategy follows a quasi-underlay signaling, which is equipped with spectrum sensing. They evaluate the performance of the optimised scheme for the CR system in the presence of PUEA, and compare it with the conventional underlay scheme. For more comparison, they compare the proposed approach to that of a similar system, which does not consider the PUEA in the formulation of the joint spectrum sensing and power allocation. They show that the proposed optimal joint power control and spectrum sensing can significantly improve the system performance in terms of average achievable CR data rates compared with the considered conventional methods.

This study presents a probabilistic model to assess the co-channel interference produced by multiple transmitters of a fixed wireless access network into a high altitude platform stations (HAPS) victim receiver. The authors propose an alternative probabilistic approach that avoids the worst case assumptions usually considered in traditional interference calculation methods, by considering the random modelling of some of the technical parameters involved. More specifically, the geographic positions of fixed wireless access system transmitters are modelled by a two-dimensional point process and their antenna gains in the sidelobe region are modelled as gamma distributed random variables. The proposed method is validated by comparing the minimal operating distance resulting from the traditional deterministic interference calculation methods and that obtained with th proposed approach. Results corresponding to the four possible interfering scenarios indicate that the proposed probabilistic approach leads to a reduction in coordination distances.

In urban canyons, multipath (MP) signals have some problems such as short time delay, high dynamic, and uncontrollable. To solve this problem and mitigate the interference of MP effect on positioning, the authors proposed a new method which uses gated recurrent unit (GRU) neural networks (NNs) aided by compressed sensing algorithm to estimate parameters of MP signal accurately. They showed how to build the GRU – deformation of recurrent NNs (RNNs) – in a dynamic environment, and estimated the MP signals parameters accurately. Also, considering the special cases in a dynamic environment, they used the adaptive wavelet filter to optimise the NNs, compensated pseudo-distance, and improved the accuracy of positioning. Like other NNs, the learning process of this machine learning method in the dynamic environment can be summarised as obtaining data from different environmental conditions. For this, they collected signal data from different speeds to train GRU–RNN model, which correctly estimated the MP signal's parameter value in a different environment and different speeds. By experimental verification, when the speed is slower than 20 km/h, GRU–RNN can reduce code tracking error to 0.08 chips, and increased the positioning accuracy by about 13%.

Cognitive radio (CR) plays an important and promising role in solving wireless spectrum scarcity problems by exploiting wireless spectrum bands that have been underutilised thus far. CR is a type of wireless communication in which wireless devices use environmental sensing to detect and change transmission parameters. The authors propose the probabilistic and deterministic path detection (PDPS) Protocol for CR networks in this study. PDPS aims to increase the probability of finding the path of best quality between any source and any destination. The performance of the proposed protocol is evaluated by conducting comprehensive simulation scenarios and experiments using a special simulator, which was built using Java. The simulation results highlight the benefits of the proposed path selection technique in comparison to state-of-the-art protocols. Comparisons are carried out using several performance metrics; namely throughput, stability and end-to-end delay.

This work presents a new cross-layer cooperative medium access control (CMAC) protocol with hybrid radio frequency (RF) energy-harvesting (EH) capability to enhance the energy efficiency and network lifetime of energy-constrained wireless ad-hoc networks. The proposed protocol employs an adaptive transmission process and integrates the hybrid time–power splitting wireless EH technique at the relay node. The relay node can also assist using its own power (traditional cooperation) provided its battery level is sufficiently adequate and there is no need for RF-EH. The best transmission mode among direct transmission, cooperative transmission and TPSR cooperation is selected based on power allocation. Two techniques namely the outage probability quality-of-service requirement and transmit power optimisation are considered. In addition, the distributed relay selection process is proposed to select the best helper based on location, residual energy and EH information that can significantly enhance the energy efficiency and network lifetime of the wireless network. The results indicate that the proposed protocol can extend the lifetime and improves the energy efficiency of the network.

Space-terrestrial integrated networks consisting of low earth orbit (LEO) satellites and terrestrial users are widely developed for potentially diversified requirements of content distribution. With an obviously time-varying topology, however, designing a distribution strategy faces several explicit challenges, such as prolonged content access latency and significant transmission overheads, due to lack of contact opportunities and limited on-board storage space. In this study, therefore, a novel back-tracing partition directed on-path caching distribution mechanism (BPDM) is proposed for the file distribution in the hybrid LEO constellation and terrestrial network. In the proposed strategy, a group of feasible on-path cache nodes is iteratively selected by utilising a well-designed cross-timeslot graph, as well as a collaborative cached content placement strategy, called as multiple regions cooperative cache algorithm, by carefully considering diversified popularity of target files. As a result, the proposed BPDM could efficiently reduce redundant transmissions of content access for different users by fetching objective file mainly from limited quantities of intermediate caching nodes. Through the simulation results, the proposed method can obviously decrease the holistic overheads and access delay compared with the minimum spanning tree algorithm and Network Central Location (NCL) node selection metric.

The authors analyse and investigate the effectiveness of frequency domain equalisation (FDE) for single-carrier (SC) transmission over a line-of-sight multiple-input multiple-output (LOS-MIMO) channel with frequency selective fading. For this purpose, they propose a LOS-MIMO system model employing SC-FDE techniques together with a data frame structure having a cyclic prefix and postfix (CPP) overhead. The channel capacity of the proposed system is derived taking into account system design parameters, such as symbol rate and roll-off factor, as well as multipath fading channel parameters. An efficient channel estimation method is also proposed for implementing and simulating the proposed system. Signature curves estimated in simulations are consistent with those expected from the theoretical capacity analysis. The simulation results show that the SC-FDE approach to the LOS-MIMO system can, with small CPP overhead, effectively reduce intersymbol and interstream interference.

A user-centric wireless cellular network has recently emerged as a pragmatic network model for better reflecting the traffic demand-based deployment. To the best of authors' knowledge, however, the coverage probability with composite – shadowed and lognormal shadowed fading [termed the doubly-selective (DS) fading] in downlink user-centric wireless cellular networks is unknown. Most importantly, another significant performance metric, i.e. the average rate, until now has not been investigated. To study the influence of the DS fading on performance metrics and avoid unnecessary handovers caused by the random fluctuation of the lognormal shadowing at the cell-association phase, this work considers the downlink user-centric wireless cellular network with the DS fading and the closest cell-association rule. Furthermore, the closed-form expressions for the coverage probability and average rate in downlink user-centric wireless cellular networks are successfully derived. Numerical results demonstrate that the user-centric wireless cellular network not only provides a high coverage probability but also promotes the average rate compared to the Poisson point process-based network with independent uniformly distributed users.

Nowadays, the main focus of emergency communication research is directed to the use of cognitive radio ad-hoc networks for disaster scenarios. This study addresses an efficient cooperative game-theoretic channel access scheme for data offloading and cooperation of emergency user using cooperative cognitive ad-hoc controllers in order to reduce the blocking probability of the newly incoming emergency user. The main objective is to connect all the users who are in need of urgent spectrum and it is considered that their data size is too large. Also, a hybrid overlay–underlay approach was undertaken which provides higher spectrum flexibility. A distributed algorithm is proposed which comprises a criterion assignment, merge and split algorithm and an auction mechanism to provide incentives to those controllers who participate in cooperation. An aggregate throughput of 18% is obtained as an improvement when compared with other conventional heuristics algorithm.

Internet of Things (IoT) as a new technological revolution has been proposed recently wherein the things are connected over the Internet. Because of the inherent characteristics of IoT for storage of data at untrusted and heterogeneous hosts, data replication across large geographic distances for efficient data management is unavoidable. The selection of appropriate replication things in the IoT, which reduces response time and cost is one of the most important issues of data management. Since this problem is an NP-hard problem, classic approaches are not efficient to solve this issue, and evolutionary algorithm such as ant colony optimisation (ACO) and genetic algorithm (GA) seems to be very useful. This study offers a method based on a combination of ACO and a GA to solve this problem. In the proposed method, the ACO has been used to create diversity, and afterwards, the GA is performed to provide a full search over the search space. The obtained results have shown the better performance of the proposed method in comparison with ACO, the High-QoS First-Replication (HQFR), and the Response Time-based Replica Management algorithms with regard to waiting time. In addition, the obtained results have revealed the better performance of the hybrid method in comparison with HQFR and the Dynamic Cost-aware Re-replication and Re-balancing Strategy.

Here, the authors propose a robust blind digital modulation classification (BDMC) algorithm for space time block coding (STBC)-based MIMO-OFDM system in the presence of carrier frequency offset (CFO) and channel estimation errors. Previous papers published on the topic of modulation identification were limited to single-carrier systems operating over frequency-flat channels. The problem of joint channel and CFO estimation in conjunction with blind digital modulation classification for STBC-OFDM in frequency selective channel and in the presence of the impulsive noise has not been addressed before to the best of their knowledge. To cope with performance degradation of BDMC due to CFO and channels errors, they propose joint semi-blind CFO and channels estimation methods. Higher order statistics (HOS), used for feature extraction, are combined with pattern recognition methods to solve the modulation identification problem. The main contribution of their work is the development of estimators, the study of their impacts on the blind classification capability, and the use of simulations to demonstrate the superior performance of the proposed algorithms.

In this study, a new scheme called adaptive hierarchical coding and modulation has been proposed, based on Adaptive Coding and Modulation (ACM) and hierarchical modulation (HM). The primary contribution of this study is summarised as the following aspects. Firstly, 16- to 64-APSK constellations with size and labelling optimisation method are proposed for HM, which can be adapted to transmitting multiple hierarchies with different QoS streams and to the non-linear satellite channels due to a lower peak-to-average power ratio compared to traditional hierarchical QAM modulation. Bit channel capacity and Chernoff error bound are introduced to optimise size and labelling of the constellation with interior-point algorithm and modified binary switch algorithm for a specific channel model to get a better performance. Secondly, combining with optimised constellations, coding and modulation modes set is obtained from using constellation design and optimisation method, with different modulation orders and code rates. And over satellite channels with rain and location attenuation, the proposed scheme is able to adapt itself to a changing channel condition and increase the transmission rate compared with ACM schemes of DVB-S2 and DVB-S2X standard.

In this study, the authors analyse the performance of a massive multiple-input multiple-output network with N-antenna users. Equipping the user terminal (UT) with a multiple of antennas is usually challenging since it increases the overhead of the channel estimation process (linearly with N). In this study, the authors use semi-blind (data-aided) channel estimation that significantly reduces the pilot overhead and analytically obtains the optimal number of antennas that can be mounted at the UT. The proposed channel estimation algorithm is especially useful in cases where a UT can be assigned a single, or generally a few numbers of, pilot sequence(s) although it might have a number of antennas greater than the number of sequences (as the case of 5G proposed solutions); therefore the network does not have to assign more pilots to the user in order to estimate the additional antennas. The authors also characterise the user outage performance when a part of its data is used for the blind channel estimation.

Edge Computing (EC) has been proposed as a promising approach to fulfil the requirements of high bandwidth and ultra-latency of mobile applications. However, existing researches on resource allocation only consider the computing resource of mobile devices and EC servers, while ignored the constraint of the networking resources once spreading applications among multiple EC servers via wireless and wired networks. Fibre-Wireless access networks (FiWi) combine the huge bandwidth of optical fibre networks and flexible access of wireless networks to address the above issue and bridge the coexistence of multiple EC servers. They propose a Virtualisation-based Architecture converging EC over FiWi (VAECFW) to centralise control and allocate networking and computing resources for serving requested services. In addition, they study the problem of resource allocation of EC over FiWi and propose two algorithms Revenue-based Virtual Network Embedding (R-VNE) and Balanced Central Processing Unit Resource Allocation with Virtual Network Embedding (BCRA-VNE). Simulation experiments show that the services acceptance ratio is increased about 35% under their proposed architecture, and the average service requests bandwidth utilisation of R-VNE is increasing from 50 to 66%, and the BCRA-VNE is from 37 to 48%. The two algorithms not only achieve higher revenue but also get better profit rate.

With the ellipsoid-bounded channel state information (CSI) errors, this study investigates the robust secrecy energy efficiency (SEE) optimisation in a wireless powered heterogeneous network. Specifically, the authors consider the network where multiple femtocell base stations (FBSs) are deployed under the coverage of one macrocell base station (MBS). Meanwhile, the MBS serves multiple macrocell users in the presence of a malicious multiple-antenna eavesdropper (Eve) while each FBS serves a pair of information receiver (IR) and energy receiver (ER) with multiple antennas, where the ER attempts to wiretap the information of IR in the same femtocell. To promote the secrecy performance, artificial noise (AN) is aided into the downlink signal at the MBS and FBSs, and the problem of maximising SEE is formed in a cross-tier multi-cell AN-aided transmit beamforming design. This problem is non-convex while containing infinite constraints caused by CSI errors, which cannot be solved directly. In this regard, the authors resort to the successive convex approximation, semi-definite relaxation techniques and Lagrange duality theory to acquire its solvable form. Moreover, to reduce the overhead of information exchange among coordinated BSs, they further propose a distributed approach based on alternative direction multiplier method. Finally, simulation results validate the effectiveness of the proposed design.

With the continual increase of storage density, NAND flash memory cells are particularly vulnerable to channel noise, which significantly degrades the storage reliability. To overcome this issue, low-density parity check (LDPC) codes have been considered as a preferable choice for flash memory systems. To further improve the efficiency of the decoder, the convergence speed and the error-rate performance are the key performance indicators for LDPC-coded NAND flash memory. In this study, a threshold-voltage-drift-aware scheduling for belief propagation (BP) decoding of LDPC-coded NAND flash memory is introduced to improve the convergence speed and the error-rate performance. The basic idea of the proposed scheduling is to find an appropriate updated order of variable nodes according to their corresponding locations of threshold voltages. Since the proposed scheduling updates less reliable variable nodes with higher priority, it can improve the efficiency of BP decoding. Simulation results show that the proposed scheduling not only significantly improves the convergence speed, but also obtains better error-rate performance than the conventional serial scheduling.

In a K-user single input-single output interference channel, it is proved that the upper bound for multiplexing gain (MG) is . Based on interference alignment technique, Cadambe and Jafar introduced a scheme known as Original Interference Alignment (IA). This scheme is improved by Choi–Jafar–Chung (CJC) in which for reduced channel extension, higher MG is achievable. These designs requirean infinite number of channel extension to achieve the upper bound. In this study, as a common generalisation of Original IA and CJC, the authors focus on designing new precoding matrices. With the same conditions as in Original IA and CJC, by changing the values of defined variables (t and s), different cases could be generated so that different MGs with different channel extensions become possible. Broadly speaking, setting appropriate values to the assigned variables, the proposed scheme yields the same results as Original IA and CJC schemes. For all other values of t and s parameters better results than Original IA are obtained but for some special t and s parameters better results than CJC scheme are achieved. Thus, it is possible to simultaneously achieve a higher MG with lower channel extension (i.e. the reduction of computational complexity) in comparison with previously designed schemes.