This study proposes an low density party check (LDPC)-coded multi-relay cooperation with receive multi-antenna in the destination over a Rayleigh-fading channel, where maximal ratio combining and belief propagation algorithm (BP)-based joint iterative decoding based on the introduced multi-layer Tanner graph are effectively designed to detect and decode the corrupted received sequence at the destination. The overall code rate from the destination is derived mathematically in relation to all the constituent LDPC codes employed by source and multiple relays. Theoretical analysis and numerical simulation show that the proposed approach can well combine diversity and coding gains, which consequently result in significant advantage over the conventional cooperations under the same conditions.

In orthogonal frequency division multiple access-based systems where channel frequency response (CFR) estimation has to be carried out using only the user-specific (localised) pilots within a small time frequency block, the accuracy of the estimates suffer because of the limited number of pilots and imperfect knowledge of the channel statistics. A biased estimator is proposed for the estimation of CFR over the time frequency block. Hypothesis tests are designed to ascertain the time and frequency selectivity of the CFR within the region of interest, and the outcome of these tests are used to determine a vector shrinkage target for the biased estimator. Simulation results indicate that the performance of the proposed estimator is comparable to that of the optimal minimum mean square error estimator, even though it does not have any knowledge of the channel statistics.

Inter-cell interference (ICI) is a serious problem in multi-cell orthogonal frequency division multiple access systems and should be mitigated by a smart radio resource management scheme. The authors present here a novel downlink adaptive resource allocation (RA) algorithm based on ICI measurement to achieve both multi-user diversity gain and the cancellation of ICI. The proposed algorithm is performed in two steps: first, interference management by user grouping into different clusters and second, subchannel allocation in order to maximise the total throughput of the network. It does not need any priori frequency planning and no precise signal-to-interference plus noise ratio information is required for subchannel allocation. In both steps of the algorithm, the authors propose a graphic framework and use Hungarian method to solve subproblems. Simulation results indicate that the authors algorithm mitigates the ICI successfully and can improve the total throughput of network by 10–15% compared with existing adaptive RA schemes.

Daily life applications of machine-to-machine (M2M) communication are constantly increasing. Typically, M2M communication systems comprise numerous small, cheap and autonomous devices that communicate with each other while monitoring environmental conditions. After their deployment, however, remote entity management of a node is still needed for firmware or software updates required for bug fixes, functional changes or other maintenance. Therefore implementing remote entity management for M2M service capability in third generation partnership project machine-type-communication is a major challenge. Previous works have attempted to reduce traffic by updating only the software changes in the M2M device. However, the device must still reboot after a software update. Rebooting the device is costly since the previous runtime states are lost. The devices expend time and bandwidth when synchronising with other nodes and when rebuilding the routing table. Hence, the dynamic software update model (DSUM) proposed in this study is designed to enable remote entity management for M2M. A dynamic software update programming model and a prototype implementation for M2M service capability are also presented. By allowing M2M service capabilities to update the software without rebooting the node, the DSUM preserves precious runtime states. The tests in this study showed that software updating required only 88 clock cycles. This framework not only enables dynamic replacement of remote entity management functionalities at runtime, it also reduces power consumption by avoiding the need to rebuild the network topology for devices in an M2M communication network.

3G and beyond wideband code division multiple access networks use orthogonal variable spreading factor (OVSF) codes to handle multimedia traffic. OVSF codes suffer from the limitation of code blocking, which leads to new call blocking. Scattered vacant codes in the OVSF code tree are the main cause of code blocking. This study proposes compact single code and multicode assignment schemes to reduce code blocking. The vacant codes used for incoming calls are the ones surrounded by a minimum number of consecutive vacant codes. Furthermore, finding consecutive vacant codes at the leaves of the tree is sufficient to find the consecutive vacant codes for all other layers. Handling non-quantised rates with a single code assignment produces wastage of code capacity, which is avoided with the use of a multicode assignment. Multicode usage facility along with the use of vacant codes from the minimum consecutive vacant code groups results in minimum code blocking. Two categories of the multicode assignment schemes are considered: the first one uses the least number of codes and is suitable for rake limited OVSF system, and the second scheme uses maximum number of codes to reduce code blocking significantly.

Collaborative spectrum sensing has attracted significant research attention in the last few years and is widely accepted as a viable approach to improve spectrum sensing reliability. Fusing data from multiple opportunistic users (OUs) in order to produce reliable sensing results implies a reliance on the OU to provide correct information. In the presence of malfunctioning or selfish users, performance of collaborative spectrum sensing deteriorates significantly. In this study, the authors propose mechanisms for the detection and suppression of such deleterious OUs (DOUs) for hard and soft decision fusion. More specifically, a credibility-based mechanism for hard decision fusion using a hard decision combining beta reputation (HDC-BR) system is introduced. The authors proposed method does not require knowledge of the total number of deleterious users in advance. In HDC-BR, the fusion centre assigns and updates weights to each user's decisions based on an individual user credibility score, which is calculated using the BR system. The presence of DOUs in soft decision-based collaborative spectrum sensing has even more adverse effects on system performance. The authors also propose a scheme for the case of soft decision fusion to detect and eliminate falsified user observations at the fusion centre using a modified Grubbs test; they refer to it as soft-decision combining-modified Grubbs (SDC-MG). They compare the performance of the proposed methods with malicious user detection schemes proposed in the literature as well as with the case where no DOU suppression scheme is implemented, and conclude that SDC-MG performs much better than HDC-BR in a low signal-to-noise ratio regime.

In this study, different pulse modulation parameters, such as symbol error rate (SER), power loss and bandwidth were investigated to highlight the most suitable parameter for narrowband interference cancellation in ultra-wide-band (UWB) Rake receivers. Thus, the performance of transmitter pulse was evaluated at the UWB Rake receiver. Finally, comparison of various filter bank receivers in terms of number of filters and SER was achieved by using a new accurate indoor UWB IEEE model channel with different propagation scenarios.

With the growing importance of error correction in different communication systems, using an efficient and easily implementable code is always appreciated. One of the most important codes is the low-density parity-check (LDPC) code. Two main iterative decoding algorithms are usually used, namely the sum-product (SP) algorithm (also referred to as belief propagation) and the min–sum (MS). The SP algorithm is more accurate but suffers from very high complexity. On the other hand, the MS algorithm has a much lower complexity at the expense of some performance degradation. To handle this performance degradation, many algorithms were presented in the literature as improvements for the MS, like the scaled MS and the offset MS. However, all those improved algorithms are more complex than the traditional MS. In this study, an efficient and low complexity LDPC decoding algorithm, called selective max–min (SMM), is proposed. The SMM performance is closer to SP than to MS as long as the average number of ones per column in the parity check matrix is around or less than 4 (which is the case for most of the communication systems using LDPC). On the other hand, the SMM exhibits only a minor complexity increase over traditional MS making it suitable for practical implementation.

The shared-medium nature and complex wireless environment of wireless sensor networks (WSNs) poses fundamental challenges to the design of effective transmission scheduling algorithms that are optimised with respect to superframe length and reliability. In this study, the authors propose an adaptive and reliable transmission scheduling algorithm for WSNs based on low-cost estimation of channel states. The authors establish a hierarchical scheduling framework on global centralised timeslot scheduling and local distributed channel scheduling. On the one hand, global centralised timeslot scheduling aims to guarantee global optimality of resource allocation, during which a mathematical reliability model is built to avoid resource waste by the stationary allocation method and improve the reliability of packet transmission. On the other hand, local distributed channel scheduling shares the responsibility of resource allocation. During channel scheduling, the channel model is constructed by the dynamic programming method and takes both probing cost and channel quality into consideration, which alleviates the uncertain and time-varying interference and overcomes the blindness of traditional methods. In contrast with previous works that do not consider link reliability and channel probing cost and often assume two channel states, the scheduling algorithm performs reliably for an arbitrary number of channels and arbitrary number of channel states. Extensive simulations and experiments under a variety of network environments have been conducted to validate our theoretical claims.

Two-path successive relaying (TPSR) is an effective way to reduce the multiplex loss induced by the half-duplex operation of the relay node in a conventional relay network. One crucial issue in TPSR network is that the listening relay always suffers inevitable inter-relay interference (IRI), which degrades detection performance at the destination. In this study, a concatenated channel-and-network coding approach is proposed to solve the problem. In particular, a highly flexible channel code, namely, rateless code, is employed at the source to provide resilience to the residual IRI and reduce the retransmissions, which might break the system steady state of successive relaying. Then recognising the special interference structure, physical-layer network coding is incorporated into the forwarding scheme of the relay nodes to exploit network diversity and improve system efficiency. By extrinsic information transfer analysis, the minimum number of required code symbols for successful data recovery are calculated, and degree distribution of the rateless code is optimised.