Recently, as asynchronous heterogeneous network scenario becoming one of the key features for next generation wireless communications, superior spectrum confinement as well as higher spectral efficiency compared to cyclic prefixed orthogonal frequency division multiplexing (CP-OFDM) has been taken into consideration for future radio access technologies. In this paper, we propose a new quadrature amplitude modulation based filter-bank multi-carrier (QAM-FBMC) system that provides with an inherent spectral efficiency gain against CP-OFDM, which comes from reduction of the redundancies such as cyclic prefix (CP) and guard-band, while keeping the symbol rate same as in CP-less OFDM. We propose a new transceiver structure consisting of at least two different filter-bank bases at both transmitter and receiver sides. Practical algorithms including channel estimation and equalization to mitigate multi-path fading channel without CP are proposed. Various evaluation results show that the proposed system performs comparable to the CP-OFDM system even without CP and guard-band reduction is also available from the well-confined spectrum.

As a promising candidate to replace cyclic prefixed orthogonal frequency division multiplexing (CP-OFDM), a new quadrature amplitude modulation filter-bank multi-carrier (QAM-FBMC) has been proposed for enabling spectral efficiency increase and spectrum confinement while keeping near orthogonality. QAM transmission can combat intrinsic interference of conventional offset-QAM (OQAM)-FBMC, which is main bottleneck in channel estimator and multiple antenna transceiver design. Compared to existing single filter based QAM-FBMC, the new QAM-FBMC has more optimization freedom in multiple prototype filters to increase self signal-to-interference ratio (SIR). In this paper, the possibility of per-tone multiple input multiple output (MIMO) reception in the new QAM-FBMC system is exploited. Our MIMO receiver is constructed with per-tone MIMO equalization in oversampled signal domain and its soft-demapper in symbol domain. Not only the separate log likelihood ratio (LLR) calculation per stream but also joint LLR calculation (i.e., soft maximum likelihood (ML) detection) is implemented with pre-processing. Simulation results show that the per-tone MIMO reception in QAM-FBMC is comparable to that of CP-OFDM.

In this paper we consider a multi-pair two-way relaying network with two types of relays, namely, smart multi-antenna amplify and forward relays and dumb repeaters. The smart relays are able to perform adaptive linear precoding while the dumb repeaters are only able to forward the received signals. Utilizing an interference neutralization scheme, a closed-form transmit strategy can be computed for our scenario. We derive necessary and sufficient conditions for the feasibility of interference neutralization. This provides interesting insights how to choose system parameters like the number of antennas and the number of relays. When the SINR balancing problem is considered, simulation results show that the interference neutralization solution provides a balance between the computational complexity and the performance when compared to optimal transmit strategies.

In a multi‐user wireless network, physical layer security is an important issue, especially when some of the served users are malicious. As these users actively participate in the network, their channel state information can be estimated or feedback, although not perfectly known. With this channel uncertainty, the worst‐case signal leakage to eavesdropping users’ needs to be managed. The authors propose a robust instantaneous relay design that improves the worst‐case secrecy rate performance, and decompose the problem into two sub‐problems: First, the achievable signal leakage or leakage‐to‐noise ratio region is studied. Second, for fixed signal leakage constraints, the achievable secrecy rate region is computed. To approach the non‐convex optimisation problems, the authors propose to iteratively solve for the phases and magnitudes of the equivalent channel matrix, a function of the relay matrix. The numerical simulations illustrate that the proposed alternating optimisation algorithm achieves higher secrecy rates than those in a system without an instantaneous relay.

In heterogeneous dense networks where spectrum is shared, users privacy remains one of the major challenges. When the receivers are not only interested in their own signals but also in eavesdropping other users' signals, the cross talk becomes information leakage.We propose a novel and efficient secrecy rate enhancing relay strategy EFFIN for information leakage neutralization. The relay matrix is chosen such that the effective leakage channel (spectral and spatial) is zero. Thus, it ensures secrecy regardless of receive processing employed at eavesdroppers and does not rely on wiretaps codes to ensure secrecy, unlike other physical layer security techniques such as artificial noise. EFFIN achieves a higher sum secrecy rate over several state-of-the-art baseline methods.

In heterogeneous dense networks where spectrum is shared, users' privacy remains one of the major challenges. On a multi-antenna relay-assisted multi-carrier interference channel, each user shares the spectral and spatial resources with all other users. When the receivers are not only interested in their own signals but also in eavesdropping other users' signals, the cross talk on the spectral and spatial channels becomes information leakage. In this paper, we propose a novel secrecy rate enhancing relay strategy that utilizes both spectral and spatial resources, termed as information leakage neutralization. To this end, the relay matrix is chosen such that the effective channel from the transmitter to the colluding eavesdropper is equal to the negative of the effective channel over the relay to the colluding eavesdropper and thus the information leakage to zero. Interestingly, the optimal relay matrix in general is not block-diagonal which encourages users' encoding over the frequency channels. We proposed two information leakage neutralization strategies, namely efficient information leakage neutralization (EFFIN) and local-optimized information leakage neutralization (LOPTIN). EFFIN provides a simple and efficient design of relay processing matrix and precoding matrices at the transmitters in the scenario of limited power and computational resources. LOPTIN, despite its higher complexity, provides a better sum secrecy rate performance by optimizing the relay processing matrix and the precoding matrices jointly. The proposed methods are shown to improve the sum secrecy rates over several state-of-the-art baseline methods.

On a single-input-single-out (SISO) interference channel (IC), conventional non-cooperative strategies encourage players selfishly maximizing their transmit data rates, neglecting the deficit of performance caused by and to other players. In the case of proper complex Gaussian noise, the maximum entropy theorem shows that the best-response strategy is to transmit with proper signals (symmetric complex Gaussian symbols). However, such equilibrium leads to degrees-of-freedom zero due to the saturation of interference. With improper signals (asymmetric complex Gaussian symbols), an extra freedom of optimization is available. In this paper, we study the impact of improper signaling on the 2-user SISO IC. We explore the achievable rate region with non-cooperative strategies by computing a Nash equilibrium of a non-cooperative game with improper signaling. Then, assuming cooperation between players, we study the achievable rate region of improper signals. We propose the usage of improper rank one signals for their simplicity and ease of implementation. Despite their simplicity, rank one signals achieve close to optimal sum rate compared to full rank improper signals. We characterize the Pareto boundary, the outer-boundary of the achievable rate region, of improper rank one signals with a single real-valued parameter; we compute the closed-form solution of the Pareto boundary with the non-zero-forcing strategies, the maximum sum rate point and the max-min fairness solution with zero-forcing strategies. Analysis on the extreme SNR regimes shows that proper signals maximize the wide-band slope of spectral efficiency whereas improper signals optimize the high-SNR power offset.

This paper considers the so-called Multiple-Input Multiple-Output interference channel (MIMO-IC) which has relevance in applications such as multi-cell coordination in cellular networks as well as spectrum sharing in cognitive radio networks among others. We address the design of preceding (i.e. beamforming) vectors at each sender with the aim of striking a compromise between beamforming gain at the intended receiver (Egoism) and the mitigation of interference created towards other receivers (Altruism). Combining egoistic and altruistic beamforming has been shown previously to be instrumental to optimizing the rates in a Multiple-Input-SingleOutput (MISO) interference channel (i.e. where receivers have no interference canceling capability). Here we explore these game-theoretic concepts in the more general context of MIMO channels and use the framework of Bayesian games which allows us to derive (semi-)distributed precoding techniques. We draw parallels with important existing work on the MIMO-IC, including rate-optimizing and interference-alignment precoding techniques, and show how such techniques may be re-interpreted through a common prism based on balancing egoistic and altruistic beamforming. Our analysis and simulations attest the improvements in terms of complexity and performance.

Coordination in a multi-cell/link environment has been attracting a lot of attention in the research community recently. In this paper, we consider the problem of coordinated beamforming where base stations (BS) equipped with multiple antennas attempt to serve a separate user each despite the interference generated by the other bases. We propose a framework for a distributed optimization of the beamformers at each base, where distributed is defined as using "local CSIT" only. We present and compare two distributed approaches (one iterative and another direct approach) which have in common the optimization of the beamformers as a combination of so-called egoistic and altruistic solutions for this problem. We provide the intuitions behind these approaches and some theoretical grounds for optimality in certain cases. Performance is finally illustrated through numerical simulations.

It is well known that cross-layer scheduling which adapts power, rate and user allocation can achieve significant gain on system capacity. However, conventional cross-layer designs all require channel state information at the base station (CSIT) which is difficult to obtain in practice. In this paper, we focus on cross-layer resource optimization based on ACK/NAK feedback flows in orthogonal frequency-division multiplexing (OFDM) systems without explicit CSIT. While the problem can be modeled as Markov decision process (MDP), brute-force approach by policy iteration or value iteration cannot lead to any viable solution. Thus, we derive a simple closed-form solution for the MDP cross-layer problem, which is asymptotically optimal for sufficiently small target packet error rate (PER). The proposed solution also has low complexity and is suitable for real-time implementation. It is also shown to achieve significant performance gain compared with systems that do not utilize the ACK/NAK feedbacks for cross-layer designs or cross-layer systems that utilize very unreliable CSIT for adaptation with mismatch in CSIT error statistics. Asymptotic analysis is also provided to obtain useful design insights.

We consider a cognitive radio scenario in which two (or more) operators providing services in the same area wish to share the same licensed band of spectrum. This scenario differs from the classical cognitive setup with a primary and a secondary operators, as both operators here are instead on an equal footing. The operators face the choice of competition or cooperation in the way they choose their transmission parameters (here beamforming vectors) to communicate with their respective users. We build on interesting recently published work [5] [6] analyzing the gains of cooperation in this context and propose novel techniques for beamforming within this interference channel. The proposed techniques outperform classical non-cooperative game solutions and mimic known cooperative game solutions while introducing a distributed aspect for the algorithm.

Adapting user selection, power allocation and rate allocation, cross layer centralized scheduling can achieve a tremendous gain due to multiuser selection diversity in wireless networks. Yet, conventional cross layer designs all require channel state information at transmitters (CSIT), which is difficult to obtain in practice. In this paper, a closed loop cross layer design with no CSIT in a block fading frequency selective environment is proposed as an extension of flat fading case in (Ka Ming Ho, 2006). The solution to optimal power, rate allocation and user selection involves stochastic programming and thus has high complexity, especially when the channel is highly frequency selective. Instead, we would like to focus on two suboptimal algorithms, namely CP-TX and OP-TX, which are based on ACK/NAK feedbacks from selected mobiles. In practical situations, OP-TX can achieve more than 67 % of the goodput of the optimal algorithm.

In wireless networks with centralized base station, cross layer scheduling to adapt user selection, power allocation and rate allocation can achieve a tremendous gain due to multiuser selection diversity. However, conventional cross layer designs all require channel state information at the base station (CSIT), which is difficult to obtain in practice. In this paper, we propose a closed loop cross layer design with no CSIT. The optimal power, rate allocation and user selection has high complexity as it involves stochastic programming. Instead, we would like to focus on two suboptimal algorithms, namely CP-TX and OP, which are based on ACK/NAK feedbacks from selected mobiles. Under practical circumstances, OP can achieve more than 88% goodput of the optimal algorithm.