An asynchronous$\mathrm{K}_{\mathrm{a}}$-active-user unsourced multiple access channel (AUMAC) is a key model for uncoordinated massive access in future networks. We focus on a scenario where each transmission is subject to the maximal delay constraint ($\mathbf{D}_{\mathbf{m}}$), yet the precise delay of each user is unknown at the receiver. The combined effects of asynchronicity and uncertain delays require analysis over all possible delay-codeword combinations, making the complexity of the analysis grow with$\mathbf{D}_{\mathbf{m}}$and$\mathrm{K}_{\mathrm{a}}$exponentially. To overcome the complexity, we employ a wrap-decoder for the AUMAC and derive a uniform upper bound on the per-user probability of error (PUPE). Numerical results illuminate the trade-off between energy per bit and the number of active users under various delay constraints. Furthermore, in our considered AUMAC, decoding without explicit delay information is shown to achieve nearly the same energy efficiency as decoding with perfect delay knowledge.

Secret keys play a critical role in secure data transmission, and an efficient secret key generation scheme will enhance the secure transmission rate. However, the secret key is a scarce resource for classical encryption schemes like the Rivest-Shamir-Adleman (RSA) cryptosystem and its counterpart in quantum applications, and we should extract it from all possible random sources to maximize the key rate. In this paper, we investigate the achievable rate of the secret key generation (SKG)-channel-model based on an actual measured multi-mode fiber (MMF) channel, where there is an additional public discussion channel between the legitimate parties, which the adversary can perfectly overhear. In particular, we measure the fiber transmission matrix by digital holography. Based on the real measurements, we show that for 55-mode MMF, we can achieve a positive secret key rate at 51.3 bit/channel use with mode-dependent loss (MDL) at 1 dB and transmit power at 20 dBm. This demonstrates the feasibility of SKG in MMF.

This work considers an asynchronous$\mathrm{K}_{\mathrm{a}}$-active-user unsourced multiple access channel (AUMAC) with the worst-case asynchronicity. The transmitted messages must be decoded within$n$channel uses, while some codewords are not completely received due to asynchronicities. We consider a constraint of the largest allowed delay of the transmission. The AUMAC lacks the permutation-invariant property of the synchronous UMAC since different permutations of the same codewords with a fixed asynchronicity are distinguishable. Hence, the analyses require calculating all$2^{\mathrm{K}_{\mathrm{a}}}-1$combinations of erroneously decoded messages. Moreover, transmitters cannot adapt the corresponding codebooks according to asynchronicity due to a lack of information on asynchronicities. To overcome this challenge, a uniform bound of the per-user probability of error (PUPE) is derived by investigating the worst-case of the asynchronous patterns with the delay constraint. Numerical results show the trade-off between the energy-per-bit and the number of active users for different delay constraints. In addition, although the asynchronous transmission reduces interference, the required energy-per-bit increases as the receiver decodes with incompletely received codewords, compared to the synchronous case.

Future wireless access networks aim to simultaneously support a large number of devices with heterogeneous service requirements, including data rates, error rates, and latencies. While achievable rate and capacity results exist for Gaussian broadcast channels in the asymptotic blocklength regime, the characterization of second-order achievable rate regions for heterogeneous blocklength constraints is not available. Therefore, we investigate a two-user Gaussian broadcast channel (GBC) with heterogeneous blocklength constraints, specified according to users’ channel output signal-to-noise ratios (SNRs). We assume that the user with higher output SNR has a shorter blocklength constraint. We show that with sufficiently large output SNR, the stronger user can perform the early decoding (ED) technique to decode and subtract the interference via successive interference cancellation (SIC). To achieve this goal, we derive an explicit lower bound on the necessary number of received symbols for a successful ED, using an independent and identically distributed Gaussian input. The second-order rate region is also derived. Numerical results show that ED can outperform the hybrid non-orthogonal multiple access scheme when the stronger channel is sufficiently better than the weaker one. Under the considered setting, about 7-dB SNR gain can be achieved compared to treating interference as noise. These results show that ED with SIC is a promising technique for future wireless networks.

We investigate the Gaussian broadcast channel with heterogeneous finite blocklength constraints (HB-GBC), which models different latency requirements for different users. To derive an outer bound on the rate region, we introduce a novel way of applying a Sato-type outer bound in the finite blocklength regime, since Sato’s classical outer bound is not directly applicable. To derive the achievable rate region, we present a way to useshell codes, which are second-order optimal for the single-user case, in the HB-GBC. We apply our technique to a hybrid TDMA/NOMA approach as well asearly decoding, which is a technique that performs successive interference cancellation with an incompletely received interference codeword. Our numerical results show that the range of power allocations where early decoding is feasible is significantly enlarged compared to the state-of-the-art, leading to considerably improved rates in the regime where rate fairness between users is the goal. This makes early decoding a promising technique to increase the rates and fairness when strict latency constraints have to be met.

We investigate early decoding in a Gaussian broadcast channel with heterogeneous blocklength constraints when shell codes are used. By shell codes, we refer to non-i.i.d. codes that fulfill the power constraint with equality. Early decoding is a technique where one user can perform successive interference cancellation with an interference codeword that is not yet fully received. By decoding the interfering shell codeword earlier, it loses the shell property, making the statistical error analysis more challenging. We address this by using composite shell codes in combination with change of measure techniques and the Berry-Esseen Theorem for functions. We derive a bound on the minimum number of symbols that is required to successfully early decode the interference and we characterize the rate region when shell codewords are used. Numerical results show a latency reduction that is at least doubled compared to the state of the art as well as a much broader range of feasible input powers, leading to a significantly improved rate region compared to previous results on early decoding.

5G and beyond wireless networks are the upcoming evolution for the current cellular networks to provide the essential requirement of future demands such as high data rate, low energy consumption, and low latency to provide seamless communication for the emerging applications. Heterogeneous cloud radio access network (H-CRAN) is envisioned as a new trend of 5G that uses the advantages of heterogeneous and cloud radio access networks to enhance both spectral and energy efficiency. In this paper, building on the notion of effective capacity (EC), we propose a framework in orthogonal frequency division multiple access (OFDMA)- non-orthogonal multiple access (NOMA) based H-CRAN to meet these demands simultaneously. Our proposed approach is to maximize the effective energy efficiency (EEE) while considering spectrum and power cooperation between a macro base station (MBS) and radio remote heads (RRHs). To solve the formulated problem and to make it more tractable, we transform the original problem into an equivalent subtractive form via Dinkelbach algorithm. Afterward, the combinational framework of distributed stable matching and successive convex algorithm (SCA) is then adopted to obtain the solution of the equivalent problem. Hereby, we propose an efficient resource allocation scheme to maximize energy efficiency while maintaining the delay quality of service (QoS) requirements for all users. The simulation results show that the proposed algorithm can provide a non-trivial trade-off between delay and energy efficiency in OFDMA-NOMA based H-CRAN systems in terms of EC and EEE and the spectrum and power cooperation improves EEE of the proposed network. Moreover, our proposed solution complexity is much lower than the optimal solution and it suffers a very limited gap compared to the optimal method.

Future wireless access networks will simultaneously support a large number of devices with heterogeneous service requirements. These include data rates, error rates, and latencies. While capacity results exist for Gaussian broadcast channels in the asymptotic regime, the characterization of second-order achievable rate region for different blocklength constraints is not available. Therefore, we investigate a two-user Gaussian broadcast channel (GBC) with heterogeneous blocklength constraints, specified according to users’ channel output signal to noise ratios (SNRs) under a maximal input power constraint and an average error probability constraint. We show that with sufficiently large output SNR, the stronger user can invoke the technique named early decoding (ED) to decode the interference. Then the successive interference cancellation (SIC) is performed. We derive the rate region of the considered setting with individual and also sum power constraints and compare with the hybrid non-orthogonal multiple access (HNOMA) scheme. Numerical results show that under sum power constraint, ED has a larger rate region than HNOMA at the region where the weaker user’s rate is sufficiently large, when the gain of the better channel is sufficiently larger than the weaker one. The above observation makes ED with SIC a promising technique for future wireless networks.

In this work, we investigate a two-user Gaussian broadcast channel (GBC) with heterogeneous blocklength constraints, specified according to users' channel output signal to noise ratios (SNRs). Unlike traditional GBC where two users have the same blocklength constraints, here the user with higher output SNR may have a shorter blocklength constraint. Then it is unclear whether this user can decode the interference to perform successive interference cancellation (SIC) or not. We argue that with sufficient large output SNR, this user can invoke the technique named as the early decoding to decode the interference. Then SIC can proceed. We derive an explicit lower bound on the necessary blocklength for successful early decoding, using an independent and identically distributed Gaussian input, given a maximal input power constraint and an average error probability constraint. A huge SNR gain can be achieved over treating interference as noise when SIC is applied with the aid of early decoding.

With emerging wireless technologies like 6G, many new applications like autonomous systems evolve which have strict demands on the reliability and latency of data communications. In the scenario of the commonly investigated independent slow fading links, the zero-outage capacity (ZOC) is zero and retransmissions are therefore inevitable. In this work, we show that a positive ZOC can be achieved under the same setting of slow fading with constant transmit power and without perfect channel state information at the transmitter, if the joint distribution of the channel gains follows certain structures. This allows reliable reception without any outages, thus not requiring retransmissions. Based on a systematic copula approach, we show that there exists a set of dependency structures for which positive ZOCs can be achieved for both maximum ratio combining (MRC) and selection combining (SC). We characterize the maximum ZOC within a finite number of bits. The results are evaluated explicitly for the special cases of Rayleigh fading and Nakagami-$m$fading in order to quantify the ZOCs for common fading models.

In this paper, fast fading Gaussian multiuser channels are considered. If the channel state information (CSI) is perfectly known to the transmitter, capacities have been derived for many cases in which the channels satisfy certain information-theoretic orders such as degradedness, or strong/very strong interference. We study the case when only the statistics of the CSI are known at the transmitter, which is an open problem in general. The main contributions of this paper are the following: First, we derive a sufficient condition to construct equivalent (having the same capacity region as the original channel) degraded Gaussian broadcast channels, which is based on the marginal distributions of the channel gains. To achieve this goal, we leverage three schemes: coupling, maximal coupling, and copulas, in addition to the same marginal property. The underlying idea of all schemes is to obtain an equivalent channel by changing the joint distribution in such a way that it satisfies a certain information-theoretic order while ensuring that the marginal distributions of the channels to different users are not changed. The construction of this equivalent multiuser channel allows us to directly apply existing capacity results. We then further derive the capacity regions of Gaussian interference channels with strong and very strong interferences, and also the secrecy capacity of Gaussian wiretap channels, while in all cases, the transmitters know only the statistics of the channels. Several practical examples such as Rayleigh fading and Nakagami-m fading illustrate the applicability of the derived results.

In industrial machine type communications, an increasing number of wireless devices communicate under reliability, latency, and confidentiality constraints, simultaneously. From information theory, it is known that wiretap codes can asymptotically achieve reliability (vanishing block error rate (BLER) at the legitimate receiver Bob) while also achieving secrecy (vanishing information leakage (IL) to an eavesdropper Eve). However, under finite block length, there exists a tradeoff between the BLER at Bob and the IL at Eve. In this work, we propose a flexible wiretap code design for degraded Gaussian wiretap channels under finite block length, which can change the operating point on the Pareto boundary of the tradeoff between BLER and IL given specific code parameters. To attain this goal, we formulate a multi-objective programming problem, which takes the BLER at Bob and the IL at Eve into account. During training, we approximate the BLER by the mean square error and the IL by schemes based on Jensen's inequality and the Taylor expansion and then solve the optimization problem by neural network autoencoders. Simulation results show that the proposed scheme can find codes outperforming polar wiretap codes (PWC) with respect to both BLER and IL simultaneously. We show that the codes found by the autoencoders could be implemented with real modulation schemes with only small losses in performance.

With an increasing number of wireless devices, the risk of being eavesdropped increases as well. From information theory, it is well known that wiretap codes can asymptotically achieve vanishing decoding error probability at the legitimate receiver while also achieving vanishing leakage to eavesdroppers. However, under finite blocklength, there exists a tradeoff among different parameters of the transmission. In this work, we propose a flexible wiretap code design for Gaussian wiretap channels under finite blocklength by neural network autoencoders. We show that the proposed scheme has higher flexibility in terms of the error rate and leakage tradeoff, compared to the traditional codes.

We investigate the application of copulas for characterizing channel orders, e.g., degradedness or strong/very strong interference, of Gaussian multiuser channels with statistical channel state information at the transmitter (CSIT). When there is solely statistical CSIT, identifying such channel orders is much more involved and, thus, the capacity remains unknown in general. We use the maximum copula to construct equivalent channels by modifying the joint distributions such that these newly constructed channels possess certain channel orders. We also derive sufficient conditions to attain these equivalent channels. We further discuss the meaning of achieving the maximum copula with respect to the concordance between the fading channels. We illustrate the theoretical results by numerical simulations, which visualize the joint probability distributions.

In this paper, ergodic capacities of fading Gaussian multi-user channels with only statistical channel state information at the transmitter are considered. The main contributions are twofold: First, we introduce a framework to classify random fading channels solely based on their joint distributions, such that we can construct equivalent channels in order to directly make use of existing capacity results. To attain this goal, we leverage three schemes: maximal coupling, coupling, and copulas in addition to the usual stochastic order with the same marginal property. Second, we apply the developed framework to Gaussian broadcast channels, Gaussian interference channels, and Gaussian wiretap channels to obtain novel capacity (region) results.

This work develops a beamforming framework for energy efficiency optimization in MIMO multi-user systems with confidentiality constraints. Two channel models are considered, namely, a broadcast channel with confidential messages (corresponding to single-cell downlink) and an interference channel with confidential messages (corresponding to multi-cell downlink), in which multiple messages are transmitted, and it must be ensured that only the intended receiver is able to perform data decoding, thus treating non-intended receivers as potential eavesdroppers. In this multi-user scenario, the new metric global secrecy energy efficiency is introduced and optimized. Moreover, the coupling among the secrecy energy efficiencies of different users is analyzed by providing an efficient way of computing the system secrecy energy efficiency Pareto boundary. Both contributions are achieved by developing an optimization framework which suitably combines fractional programming theory and sequential optimization theory. The proposed framework is provably convergent, enjoys affordable complexity, and fulfills first-order optimality properties. Finally, the closed form conditions are provided to support smart user selection algorithms for downlink transmission.

Energy-efficient resource allocation in multiple-antenna wiretap channels is investigated, subject to maximum power and minimum secrecy capacity/rate constraints. Two energy-efficient metrics are optimized, namely the secrecy energy efficiency, defined as the ratio between the system secrecy capacity and the consumed power, and the secret-key energy efficiency, defined as the ratio between the system secret-key capacity and the consumed power. If the legitimate receiver and the eavesdropper have a single antenna, and the transmitter has multiple antennas, the global solution can be expressed by a simple formula that requires negligible complexity to be computed. Instead, if all nodes have multiple-antennas, provably convergent and computationally-friendly iterative algorithms are provided, which are able to determine the global maximum of the secret-key energy efficiency and candidate solutions of the secrecy energy efficiency maximization problem. Numerical results assess the performance of the proposed methods.

The capacity regions of Gaussian broadcast channels depends on the knowledge of channel state information (CSI). When there is only statistical CSI at the transmitter and full CSI at the receiver, the ergodic capacity region is unknown in general. In this paper we investigate the relation between the degradedness and stochastic orders among channels from the transmitter to different receivers. We derive criteria to identify the degradedness for single and multiple-antenna cases when the channels belong to the usual stochastic order or the increasing convex order. Examples illustrate the usage of the derived criteria. We also show a case in which the channel enhancement technique can be applied even when there is only statistical CSIT.

We consider a heterogeneous network (HetNet) in which multiple small cell base stations (SBSs) aim to offload a quantity of macro cell user equipments (MUEs) to reduce the energy consumption of the network while guaranteeing the QoS requirements of all UEs. We design an ascending-bid auction mechanism to achieve this goal. Unique and closed form solutions for the demand and supply quantities of offloading MUEs are derived. When the MBS has knowledge about the utilities and strategies of the SBSs, the proposed auction can be formulated as a Stackelberg game where the clinching bid price is obtained in closed form. Numerical results verify the theoretical analysis for different scenarios and show that the proposed auction clinches fast at the unique clinching price, thereby resulting in a win-win solution that improves the energy consumption of the HetNet.

This paper studies sub-classes of two-user fast fading Gaussian interference channels (GIC) with ergodic strong/very strong interference, for which channel state information (CSI) is only available at the receivers. Under this setting, the ergodic capacity region is open. In this work we derive a sufficient condition for ergodic strong/very strong GIC to achieve the ergodic capacity regions by stochastic ordering with same marginal property. We also illustrate examples to show the usage scenarios of the derived conditions.

This work proposes a jamming-resistant frequency hopping (FH) system that utilizes local channel observations for secret key generation (SKG). FH is a spread spectrum technique used in both military and consumer wireless applications to avoid jamming attacks, but requires pre-shared secret keys among communicating terminals, say Alice and Bob, to ensure that the same FH sequence is used at both sides. In our scheme, Alice and Bob utilize local observations of the channel between them as the source of common randomness to generate the shared secret key. By gathering multiple time slots into a frame, the sequence of channels observed in each frame can be used to determine the FH sequence in the next frame. In this case, the key generation rate must be high enough to identify the FH sequence in the next frame and, thus, to sustain the operation over time. However, by further considering the data transmission, an interesting tradeoff exists between the power allocated for SKG and channel estimation in the training phase and that for communication in the data transmission phase. Given the number of FH channels and the number of channels that the adversary can jam at once, we derive the minimum pilot signal power required for sustainability and also determine the optimal power allocation between pilot and data signals that maximizes the ergodic rate between the two users. Simulations are provided to demonstrate the effectiveness of the proposed scheme.

In this paper, we investigate the ergodic secrecy capacity of the fast fading Gaussian wiretap channel when only the statistics of the channel state information are known at the transmitter. We derive conditions for the existence of degradedness and a positive ergodic secrecy capacity under the usual stochastic order, the convex order, and the increasing convex order between the legitimate and eavesdropper channels. For more general orders, we prove the secrecy capacity of layered erasure wiretap channels and propose a layered signaling for the achievable scheme, and we derive an upper bound on the capacity for fast fading Gaussian wiretap channels. Finally, the numerical results show that under Nakagami-m fast fading channels, the proposed layered signaling outperforms the Gaussian codebook in several cases. In particular, in certain cases, the Gaussian codebook can achieve only a zero secrecy rate, whereas the proposed scheme achieves positive secrecy rates. Therefore, the connectivity of wireless networks can be significantly improved by the proposed scheme.

This paper studies the spectrum sharing framework for motivating the hybrid access in the two-tier macro-femtocell networks. The power allocation of each user equipment (UE) is subject to its quality-of-service (QoS) requirement as a function of the signal-to-interference plus noise ratio (SINR). The macro base station (MBS) offloads the macro UEs (MUEs) to the femto access points (FAPs) in order to improve the energy efficiency of the entire system since certain MUEs are closer to the FAP(s) than to the MBS. When multiple femtocells exist in the network, auction mechanism is appropriate to establish the hybrid access. Each FAP bids for serving extra MUEs while the MBS acts as the auctioneer. In order to reduce the overhead of the information exchange, we assume that the FAPs decide their bids independently of each other by maximizing their own utilities. After receiving the bids, the MBS searches the winner FAP(s) and optimizes the number of offloaded MUEs. The compensation fee based on the bid is paid by the MBS to the winner FAP(s) for serving the additional MUEs. Numerical results show that the lowest bidder wins the auction. The proposed auction for motivating the hybrid access in the two-tier macro-femtocell network results in a win-win solution since both utilities of the MBS and FAPs are maximized.

Cooperative multi-cell MIMO techniques are well known for their outstanding capability to mitigate inter-cell interference by allowing user data to be jointly processed by several interfering base stations for the improvement of the system performance. This paper proposes an iterative algorithm that designs the precoding matrix for cooperative multi-cell MIMO downlink communications. As the demand for higher throughput and higher system resilience is envisioned for future wireless communication systems, the proposed algorithm takes the potential outage into consideration when channel state information is only partially available at the transmitter side. The aim is to maximize the sum user throughput considering outage with subject to power limitation at each base station. The joint optimization of the precoding matrix and the assigned transmission rate is solved via a 2-step alternating algorithm. The performance of the proposed method is evaluated by Monte Carlo simulations and compared with existing methods. Simulation results show that our proposed algorithm achieves performance gain than other referenced methods over the entire compared SNR region. Performance of all methods are also compared and analyzed when inter-cluster interference is present.

In this paper we consider the secure transmission with multiple-input, single-output, single-antenna eavesdropper (MISOSE) in fast fading channels where the transmitter knows perfect legitimate channel state information but only the statistics of the eavesdropper's channel. For the MISOSE channels, the artificial noise assisted beamforming proposed by Goel and Negi is a promising technique, where the artificial noise is imposed on the null space of the legitimate channel to disrupt the eavesdropper's reception. Here we propose a generalized artificial noise scheme which allows the injection of the artificial noise to the legitimate channel. Although the generalized artificial noise may cause the leakage of artificial noise at the legitimate receiver, the secrecy rate can still be improved since the covariance matrix of it is more flexible than the heuristic one selected by Goel and Negi. To fully characterize the proposed scheme, we investigate the optimization of its secrecy rate. We first derive the conditions under which the beamformers of the message bearing signal and the generalized artificial noise being the same is optimal. Based on this choice, the complicated secrecy rate optimization problem over the covariance matrices of the message-bearing signal and the generalized artificial noise can be reduced to a much simpler power allocation problem. We also develop an efficient algorithm to solve this non-convex power allocation problem. Numerical results show that our generalized artificial noise scheme outperforms Goel and Negi's heuristic selection, especially in the near eavesdropper settings. In particular, with the aid of the proposed scheme, the regime with non-zero secrecy rate is enlarged, which can significantly improve the connectivity of the network.

We consider the secure transmission in ergodic fast Rayleigh fading multiple-input single-output single-antenna-eavesdropper (MISOSE) wiretap channels. We assume that the statistics of both the legitimate and eavesdropper channels are the only available channel state information at the transmitter (CSIT). By introducing a new secrecy capacity upper bound, we prove that the secrecy capacity is achieved by the Gaussian input without prefixing. To attain this result, we form another MISOSE channel for upper-bounding by relaxing the equivocation constraint, and tighten the bound by carefully selecting correlations between the legitimate and eavesdropper channel gains. The resulting upper bound is tighter than the others in the literature which are based on modifying the correlation between the noises at the legitimate receiver and eavesdropper. Next, we fully characterize the secrecy capacity by showing that the optimal channel input covariance matrix is a scaled identity matrix. The key to solve such a stochastic optimization problem is by exploiting the completely monotone property of the secrecy capacity. Finally, we prove that with only statistical CSIT of both channels, the capacity will neither scale with signal-to-noise ratio (SNR) nor the number of antenna. Our numerical results also match these observations and further confirm that having the legitimate CSIT (realizations) is very beneficial to increase the secrecy capacity.

In this paper we consider secure transmission for the multiple-input, multiple-output, single-antenna-eavesdropper systems with perfect information of the main channel and only the statistics of the eavesdropper's channel state information known at the transmitter. We adopt the celebrated artificial-noise (AN) assisted beamforming, which was studied by Goel and Negi with the limitation that the AN must be allocated in the null space of the main channel. By removing this limitation, we study the rate optimization problems over the covariance matrices of the signal and the AN. After exploring the structure of the optimal solutions, we show that the original optimization problem can be simplified as a much simpler power allocation problem. Our results show that to improve the rate performance, one may allocate the power of the AN in the directions of the right singular vectors of the main channel. Thus Goel and Negi's AN selection is strictly sub-optimal. Moreover, our simulations show that when the main channel has no null space, the rate performance of our optimized signaling outperforms that of Goel and Negi's significantly.

In this work, we consider an interference-mitigation based cognitive radio system where a secondary transmitter is to communicate with its corresponding receiver without affecting the communication between a primary transmitter-receiver pair. In this case, the secondary transmitter must satisfy a coexistence constraint which requires that no rate degradation occurs at the primary user (PU), even when the latter utilizes only a single-user decoder. To achieve a non-zero rate of the secondary user (SU) under this constraint, Jovicic and Viswanath previously proposed a scheme (referred to as the JV scheme) that utilizes relaying by the secondary transmitter to overcome the interference caused by the simultaneous transmission of the SU's message. In this case, the interference caused by the signals corresponding to PU's message at the secondary receiver (from both the direct and the relay links) is mitigated by employing dirty paper coding (DPC) at the secondary transmitter. However, the interference caused by the SU's message at the primary receiver is not eliminated in this case and, thus, will limit the power (and, hence, the rate) that can be used by the secondary transmitter to transmit its own message. In our work, the use of clean relaying by the secondary transmitter and/or receiver (i.e., relaying without simultaneous transmission of SU's own message) is proposed to improve the quality of the relayed signal and, thereby, increases the rate achievable by the SU. Two improved transmission schemes are proposed: (i) clean relaying by secondary transmitter (CT) and (ii) clean relaying by secondary transmitter and receiver (CTR). The CT scheme utilizes DPC to mitigate interference at the secondary receiver whereas the CTR scheme utilizes coding for multiple access channels with common messages to enable decoding of both PU's and SU's messages at the secondary receiver. The CT scheme can be viewed as a generalization of the JV scheme and, therefore, performs at least as well as the latter. The CTR scheme, on the other hand, is shown to outperform the CT scheme in terms of the multiplexing gain achievable under full channel state information at the transmitter (CSIT) and in terms of the rate achievable with statistical CSIT. Numerical simulations are provided to illustrate these advantages.

We consider secure transmission in fading channels with only the statistics of the eavesdropper's channel state information known at the transmitter. We optimize the celebrated artificial-noise (AN) assisted beamforming, which was studied by Goel and Negi using heuristically selected AN and beamforming directions. We find that Goel and Negi's AN selection is strictly sub-optimal. On the contrary, one may inject AN to the beam direction of the message to improve the secrecy rate performance. We prove that for a multiple-input, single-output, single-antenna-eavesdropper system, the optimal transmission scheme is a beamformer which is aligned to the direction of the legitimate channel. We then prove that, for the part of the AN in the null space of the legitimate channel, uniform power allocation is optimal. We also provide the necessary condition for the proposed AN selection to be optimal. Simulation results show that our AN selection outperforms Goel and Negi's, especially when the legitimate user's channel quality is poor. In particular, when AN assisted beamforming is applied, the region with non-zero secrecy rate is enlarged, which can significantly improve the connectivity of secure networks.

Linear-assignment Gel'fand-Pinsker coding (LA-GPC) is a coding technique for channels with interference known only at the transmitter, where the known interference is treated as side-information (SI). As a special case of the LA-GPC, dirty paper coding has been shown to be able to achieve the optimal interference-free rate for SI channels with perfect channel state information at the transmitter (CSIT). In the cases where only the channel distribution information at the transmitter (CDIT) is available, LA-GPC also has good (sometimes optimal) performance in a variety of fast and slow fading SI channels. In this letter, we design filters in the nested lattice based coding to make it achieve the same rate performance as the LA-GPC in multiple-input multiple-output (MIMO) channels. Compared with the random Gaussian codebooks used in previous works, our resultant coding schemes have algebraic structures and can be implemented in practical systems. Simulations in slow-fading channels are provided, and near interference-free error performance is obtained. The proposed coding schemes can serve as the fundamental building blocks to achieve the promised rate performance of MIMO Gaussian broadcast channels with CDIT or perfect CSIT.

In this paper, we aim to maximize the weighted sum rate of Orthogonal Frequency Division Multiplexing (OFDM) relaying systems. In the considered system we jointly optimize subcarrier pairing in two consecutive time slots and power allocation on each subcarrier in each time slot. In addition, the destination combines the signals from the source and the relay pertaining to the same message in each two time slots. This is motivated by the lack of discussion in the literature on joint optimization with destination combining. It is assumed that the channel state information is known to the source. Decode-and-forward and half-duplex strategies are considered when the relay is used. Both total and individual power constraints for the source and the relay are investigated. Based on the optimization results, algorithms to achieve feasible solutions are also proposed. Simulation results show that the proposed algorithms almost achieve the optimal weighted sum rate, and outperform the existing methods in various channel conditions.

In this paper, we present the design of cognitive radio in the Rician channel with partial channel state information at the transmitter (CSIT). We replace the dirty paper coding (DPC) used in the cognitive radio with full CSIT by the linear assignment Gel'fand-Pinsker coding (LA-GPC) which can achieve better error performance when there is only partial CSIT. Based on the achievable rate derived from the LA-GPC, two optimization problems under the fast and slow fading channels are formulated. We derive semi-analytical solutions to find the relaying ratios and precoding coefficients. We also show that the parameters derived by the proposed methods converge to the optimal full CSIT solutions in the asymptotic cases. This result verifies the correctness of the proposed methods asymptotically. Moreover, a new coding scheme is proposed to implement the LA-GPC in practice. Simulation results show that the proposed semi-analytical solutions perform close to the optimal solutions found by brute-force search, and outperform the systems based on naive DPC. Simulation results also show that the proposed practical coding scheme can effectively approach the theoretical rate performance.

Cognitive radio (CR) has been proposed as an efficient method to reuse the licensed spectrum. It recognizes the primary (licensed) users' signals and adapts its own to minimize the interference it generates. When perfect channel state information is known at the transmitters, the capacity of CR system can be achieved by utilizing the dirty paper coding (DPC). In this paper, we consider the performance of the CR system under both fast and slow fading channels with only channel statistics known at the transmitters. Due to the limited channel state information, the original DPC fails and is replaced by the so-called linear-assignment Gel'fand-Pinsker coding. By carefully designing the parameters based on this preceding, this system has significant rate gains over naively treating primary users' signals as interference for fast and slow fading scenarios.

In this paper, we improve the peak to average power ratio (PAPR) reduction scheme for multicarrier systems proposed by Collings and Clarkson by applying dirty paper coding with peak power constraint. We compare the bit error rate (BER) performance among conventional orthogonal frequency division multiplexing (OFDM), Collings and Clarkson’s method, and our proposed scheme with bit loading. From simulation we find that when channel coding is considered, Collings and Clarkson’s method is the worst independent of the number of bits loaded. The proposed method performs the best when the number of bits is large and hence is suitable for high speed transmission.