Jamming in some cases observed at its transmitting side could be modeled as a constant amplitude but random phase signal:J(t)= AJ · ejϕ(t). Such situation may happen in single-tone or multi-tone jammed frequency hopping systems, in cellular mobile systems under co-channel interference, etc. In order to appropriately handle this kind of jamming through channel coding technologies, a jamming model based log-likelihood ratio (LLR) initialization method is proposed to replace their conventional AWGN model based LLR initialization method. Accordingly, the optimal LLR initialization formula is derived based on the analysis of the probability density function of jammed signals. Then, the approximation of optimal LLR initialization as well as its robust variant are further provided, hence the complexity is significantly reduced and only the signal-to-noise ratio (SNR) and signal-to-jamming ratio (SJR) are required as thea prioriknowledge. The proposed LLR initialization method is tested in a Polar Code (PC) coded Orthogonal Frequency Division Multi-plexing (OFDM) system, where both the AWGN and the Rayleigh fading channel models are considered. The obtained simulation results demonstrate that the proposed method outperforms the conventional Gaussian model based one and other existed robust initialization methods.

Grant-free (GF) low-density signature orthogonal frequency division multiplexing (LDS-OFDM) is one of the most generic grant-free non-orthogonal multiple access (GF-NOMA) schemes. This paper proposes a two-stage active user detection (AUD) consisting of the initial AUD stage and the false alarm correction stage. In the initial AUD stage, an initial active user set is efficiently estimated by the conventional cover decoder, which may still contain a few false alarms. Hence, a false alarm correction stage is further invoked, which consists of two cooperative and iterative detection components, namely, message passing algorithm (MPA) based data decoder and belief propagation (BP) based false alarm corrector. Based on users’ signature spreading sequences in the initial active user set, a tanner graph with potential redundant-edges is constructed, on which MPA is executed for data decoding. In turn, with the aid of decoded data symbols, the remaining false alarms in the initial active user set are further removed by the false alarm corrector. Hence, the tanner graph could evolve iteratively. Furthermore, the false alarm performance of the initial AUD stage is theoretically analyzed. Based on this analysis, the LDS matrix used in GF LDS-OFDM is optimized. Finally, the complexity of our proposal is also provided.

This article investigates the covert performance of an unmanned aerial vehicle (UAV) jammer-assisted cognitive radio (CR) network. In particular, the covert transmission of secondary users can be effectively protected by UAV jamming against the eavesdropping. For practical consideration, the UAV is assumed to only know certain partial channel distribution information (CDI), whereas not to know the detection threshold of an eavesdropper. For this sake, we propose a model-driven generative adversarial network (MD-GAN)-assisted optimization framework, consisting of a generator and a discriminator, where the unknown channel information and the detection threshold are learned weights. Then, a GAN-based joint trajectory and power optimization (GAN-JTP) algorithm is developed to train the MD-GAN optimization framework for covert communication, which results in the joint solution of the UAV’s trajectory and transmits power to maximize the covert rate and the probability of detection errors. Our simulation results show that the proposed GAN-JTP with a rapid convergence speed can attain near-optimal solutions of the UAV’s trajectory and transmit power for the covert communication.

Benefiting from the powerful cyclic redundancy check aided successive cancellation list (CA-SCL) decoder, the polar codes have achieved competitive performances with respect to LDCP codes. However, its short codeword performance needs to be further improved for supporting reliable short package transmissions typically in massive machine-type communications (mMTC). In this paper, the short polar coding problem is tackled by developing a bit-flipping aided CA-SCL detection method. First, we reveal that error distribution of SCL decoding strongly relates to the row weights of generator matrix. Accordingly, we determine the flipping indices according to both their row weights and their polarized bit-channel reliabilities. The simulation results show that our row weight based successive cancellation list flipping (RWB-SCL-Flipping) decoding achieves around 0.3 dB gain compared with its counterpart in [1] while transmitting short codewords over AWGN channels.

As a potential development direction of future transportation, the vacuum tube ultra-high-speed train (UHST) wireless communication systems have newly different channel characteristics from existing high-speed train (HST) scenarios. In this paper, a three-dimensional non-stationary millimeter wave (mmWave) geometry-based stochastic model (GBSM) is proposed to investigate the channel characteristics of UHST channels in vacuum tube scenarios, taking into account the waveguide effect and the impact of tube wall roughness on channel. Then, based on the proposed model, some important time-variant channel statistical properties are studied and compared with those in existing HST and tunnel channels. The results obtained show that the multipath effect in vacuum tube scenarios will be more obvious than tunnel scenarios but less than existing HST scenarios, which will provide some insights for future research on vacuum tube UHST wireless communications.

In massive communication networks, bursty traffic may cause an unexpected network overload. Traditionally, the access class barring (ACB) based random access (RA) schemes perform well in controlling network overload. However, as the number of contention devices increases, the performance of the ACB-based access control mechanism degrades severely, especially in terms of access success probability and average access delay. In recognition of the fact that existing ACB-based RA scheme does not take the influence of the physical random access channel (PRACH) state on RA performance into consideration, in this paper, we propose a joint RA control scheme involving two access check mechanisms, i.e., ACB check and PRACH channel quality check. As a result, the proposed joint scheme can not only reduce the number of contention de-vices in each RA slot through ACB check but also guarantee the success of preamble (PA) detection by means of PRACH quality check. Simulation results show that the proposed scheme outperforms the other ACB-based RA scheme in terms of access success probability, network load capacity, and the average number of PA transmission at the expense of increased total service time. As a result, compared with other access control mechanisms, the proposed scheme is more suitable for delay-tolerate services.

To the best of our knowledge, Belief Propagation List (BPL) decoding achieves the best error-correction performance within the class of BP based polar code decoding algorithms. It regards different permutations of the polar code factor graph as a range of available "decoding lists" for individually executing the BP algorithm. Then, a minimum Euclidean distance criterion is employed to combine these individual decisions. However, we demonstrated that simply increasing the number of lists involved in the BPL algorithm does not always improve its performance. Instead, we exploit the extrinsic information transfer (EXIT) chart technology to verify the efficiency of a decoding list. Based on this analysis, an efficient list selection scheme is proposed. In the same spirit, in order to mitigate the impact of relatively inferior decoding lists on other selected decoding lists, new decision fusion schemes are also designed. Benefiting from these improvements of BPL algorithm, performance gains are evidenced in our simulation results.

Non-orthogonal multiple access (NOMA) has attracted both academic and industrial interest since it has been considered as one of the promising 5G technologies in order to increase connectivity and spectral efficiency. In this paper, we focus on a downlink NOMA network, where a single base station serves a set of users through multiple subchannels. The goal is to jointly optimize energy efficiency (EE) and fairness among users with respect to the subcarrier and power allocation parameters. To achieve this with acceptable complexity, we propose a novel greedy subcarrier assignment scheme. Due to the fractional form of the EE expression and the existence of interference, the power allocation problem is non-convex. To this end, we first transform this into an equivalent subtractive form, which is then solved by using fractional programming with sequential optimization of the power allocation vectors. Simulation results reveal the effectiveness of the proposed scheme in terms of EE and fairness among users compared to baseline schemes. Finally, the proposed algorithms are of fast convergence, low complexity, and insensitive to the initial values.

Non-orthogonal multiple access (NOMA) has attracted both academic and industrial interest since it has been considered as one of the promising 5G technologies in order to increase connectivity and spectral efficiency. In this paper, we focus on a downlink multicarrier (MC) NOMA network, where a single base station serves a set of users through multiple subchannels. The goal is to jointly optimize energy efficiency (EE) and fairness among users with respect to the subcarrier and power allocation parameters. To achieve this with acceptable complexity, a novel greedy subcarrier assignment scheme based on the worst-user first principle is proposed. Due to the fractional form of the EE expression and the existence of interference, the power allocation problem is non-convex and NP-hard. To this end, we first transform this into an equivalent subtractive form, which is then solved by using fractional programming with sequential optimization of the inter/intra-subchannel power allocation vectors. Simulation results reveal the effectiveness of the proposed scheme in terms of EE and fairness among users compared to baseline schemes. Finally, the proposed algorithms are of fast convergence, low complexity, and insensitive to the initial values.

For the sake of supporting massive connectivity in the future 5G networks, non-orthogonal multiple access (NOMA) techniques are advocated. As a promising NOMA technique, in recent years sparse code multiple access (SCMA) has attracted substantial attention. However, there is a paucity of studies on the theoretical analysis of its error-freely achievable data rate, especially, in the downlink context. Hence, we derive the cutoff rate of SCMA in downlink broadcast channels, which indicates the lower-bound of a system's error-freely achievable rate. However, we will demonstrate that when considering the conventional categorization of pairwise error events, the accuracy of the cutoff rate rapidly degrades in the low-SNR region owing to the fact that multi-user SCMA systems typically encounter an extremely large constellation size. Alternatively, by invoking Bergmans' concept from 1973 in the categorization of pairwise error events, we obtain a more accurate cutoff rate both in the low- SNR regions and the high-SNR regions. Moreover, we provide insights into the cutoff rate derivation process, which reveals some general guidelines for designing a beneficial codebook, capable of improving SCMA with respect to its original low-density signature-based counterpart.

We propose a simple yet effective norm-based joint transmit and receive antenna selection (NBJTRAS) assisted and two-tier channel estimation (TTCE) aided space-time shift keying (STSK) system, which is capable of significantly outperforming the conventional STSK system, while efficiently utilising available radio frequency (RF) chains. Specifically, the NBJTRAS carries out antenna selection based on the channel estimation (CE) generated using a low-complexity training based least square channel estimator by reusing RF chains. The selected sub-channel matrix is further refined by an efficient semi-blind CE and data detection scheme. Our simulation results show that only a few iterations are sufficient for the TTCE scheme to approach the optimal maximum-likelihood detection performance associated with perfectly channel state information.

A generalized adaptive network coding (GANC) scheme is conceived for a multi-user, multi-relay scenario, where the multiple users transmit independent information streams to a common destination with the aid of multiple relays. The proposed GANC scheme is developed from adaptive network coded cooperation (ANCC), which aims for a high flexibility in order to: 1) allow arbitrary channel coding schemes to serve as the cross-layer network coding regime; 2) provide any arbitrary trade-off between the throughput and reliability by adjusting the ratio of the source nodes and the cooperating relay nodes. Furthermore, we incorporate the proposed GANC scheme in a novel successive relaying aided network (SRAN) in order to recover the typical 50% half-duplex relaying-induced throughput loss. However, in support of the coherent detection, in addition to carrying out all the relaying functions, the relays have to estimate the Source-to-Relay channels, which imposes a substantial extra energy consumption and bit rate reduction owing to the inclusion of pilots. Hence noncoherent detection is employed for eliminating the power-hungry channel estimation. Finally, we intrinsically amalgamate our GANC scheme with the joint network-channel coding (JNCC) concept into a powerful three-stage concatenated architecture relying on iterative detection, which is specifically designed for the destination node (DN). The proposed scheme is also capable of adapting to rapidly time-varying network topologies, while relying on energy-efficient detection.

Conventional single-relay aided two-phase cooperative networks employing coherent detection algorithms incur a significant 50% throughput loss. Furthermore, it is unrealistic to expect that in addition to the task of relaying, the relay-station would dedicate further precious resources to the estimation of the source-relay channel in support of coherent detection. In order to circumvent these problems, we propose decode-and-forward (DF) based successive relaying employing noncoherent detection schemes. A crucial challenge in this context is that of suppressing the successive relaying induced interference, despite dispensing with any channel state information (CSI). We overcome this challenge by introducing a novel adaptive Newton algorithm based multiple-symbol differential interference suppression (MS-DIS) scheme. Correspondingly, a three-stage concatenated transceiver architecture is devised. We demonstrate that our proposed system is capable of near-error-free transmissions at low signal-to-noise ratios.

An amplify-and-forward (AF) based successive relaying aided network (SRAN) is designed for a multi-user spread-spectrum scenario conceived for noncoherent (NC) detection in order to convert the typical 50% half-duplex relaying-induced throughput loss to a potential user-load reduction of the CDMA system, where the NC detector allows us to avoid the extra power consumption imposed by channel estimation. With the same “green agenda” in mind, we limit the extra complexity imposed on the relay node (RN) by invoking the AF, rather than the more complex decode-and-forward protocol. We theoretically characterize the proposed AF based SRAN in the context of the DS-CDMA uplink by evaluating its noncoherent Discrete-input Continuous-output Memoryless Channel (DCMC) capacity. We demonstrate that the cooperative DS-CDMA uplink achieves a higher capacity gain with respect to its conventional direct transmission based counterpart, when the system has to support a high number of DS-CDMA users.

Conventional single-relay aided two-phase cooperative networks employing coherent detection algorithms incur a significant 50% throughput loss. Furthermore, it is unrealistic to expect that in addition to the task of relaying, the relay-station would dedicate further precious resources to the estimation of the source-to-relay channel in support of coherent detection, which would consume extra energy expended in power-hungry channel estimation. In order to circumvent these problems, we propose successive relaying employing noncoherent detection schemes. A crucial challenge in this context is that of suppressing the successive relaying induced interference, despite dispensing with any channel state information (CSI). We overcome this challenge by introducing a novel adaptive Newton algorithm based multiple-symbol differential interference suppression (MS-DIS) scheme. We demonstrate that our system is capable of near-error-free transmissions at low signal-to-noise ratios.

The conventional single-relay aided two-phase cooperative network employing a so-called soft-input soft-output multiple-symbol differential sphere detection (SISO-MSDSD) and operating in a distributed turbo decoding mode incurs a high complexity and imposes a 50% half-duplex relaying induced throughput loss. In this paper, we combat both of these critical problems. We commence by evaluating the Discrete-input Continuous-output Memoryless Channel (DCMC) capacity of the Decode-and-Forward (DF) based successive relaying aided networks (SRAN) as our theoretical benchmark. Then a relay-aided SISO-MSDSD is designed, which is then incorporated in the DF based SRAN. As our novel contribution, we demonstrate that the proposed transceiver is capable of significantly reducing the system's complexity, whilst recovering the 50% half-duplex relaying induced throughput loss. The system is capable of performing within 2.9 dB from the corresponding noncoherent DCMC capacity.

The employment of wireless mesh networking in real- life scenarios has attracted substantial research interest in recent years and in this context VoIP has become a ubiquitous application. However, it has been demonstrated that VoIP transmissions over a multihop network may still remain inadequate in terms of their high packet-loss ratio and network- induced delays. To alleviate these limitations, we propose a novel distributed MAC-layer cooperation protocol, which is based on the decode-and-forward regime, whilst relying on the lowest possible control packet overhead. Furthermore, we employ several improvements across the protocol stack, including an improved PHY-layer, based on three- stage turbo-style differential detection, packet aggregation in the MAC-layer, as well as on adjusting the retransmission limit of each packet in order to reduce the delay imposed when employing cooperation. We characterize our improved system in a Wireless Mesh Network (WMN) scenario using the OMNeT++ network simulator and compare it to an 802.11g-based benchmarker. As a benefit of these techniques, we have observed up to 10-fold reduction in the energy consumption per bit, despite increasing the number of simultaneous calls supported by up to 9, when the number of hops between the sources and destination is 6.

The conventional amplify-and-forward cooperative system is capable of achieving a superior performance with the aid of Multiple-Symbol Differential Sphere Detection (MSDSD), when compared to conventional differential detection (CDD) for transmission over time-selective channels. However, the conventional broadcast/cooperative twin-phase based relaying protocol encounters a 50% throughput loss imposed by half-duplex relaying. For combating this problem, in this paper, we create a MSDSD aided successive relaying based cooperative DS-CDMA system. We demonstrate that given the target BER of 10-4, a diversity gain of up to 10 dB is achieved over the benchmark schemes employed without a throughput loss.