Dr Zilong Liu

Multiple-input multiple-output filterbank multicarrier communication (MIMO-FBMC) is a promising technique to achieve very tight spectrum confinement (thus, higher spectral efficiency) as well as strong robustness against dispersive channels. In this paper, we present a novel training design for MIMO-FBMC system which enables efficient estimate of frequency-selective channels (associated to multiple transmit antennas) with only one non-zero FBMC symbol. Our key idea is to design real-valued orthogonal training sequences (in the frequency domain) which displaying zero-correlation zone properties in the time-domain. Compared to our earlier proposed training scheme requiring at least two non-zero FBMC symbols (separated by several zero guard symbols), the proposed scheme features ultra-low training overhead yet achieves channel estimation performance comparable to our earlier proposed complex training sequence decomposition(CTSD). Our simulations validate that the proposed method is an efficient channel estimation approach for practical preamble-based MIMO-FBMC systems.

Evolving from cognitive radio networks (CRNs), the concept has developed into a new paradigm of cloud and big data-based next-generation CRNs due to huge amount of data processing, complicated spectrum resource scheduling, and real-time information exchange. In cloud-based CRNs, control channels are needed for CR nodes to perform certain handshakings for network self-organization, spectrum sensing, network coordination, and flexible data connections. This paper investigates a transmission scheme for control channel (CC) in cloud-based CRNs, which is over several noncontiguous spectral holes. Transform domain communication system (TDCS)-based transmission scheme with spectrally-constrained sequence design is presented for CC. A practical testbed design for TDCS-based CC with multiple National Instruments PXIe devices and six universal software defined radio reconfigurable input/output devices is presented. Details of system design as well as main implementation challenges are described. Bit-error rate of the system is validated through both theoretical analysis and simulation results under realistic channel conditions.

We investigate spectrally-constrained sequences (SCSs), which are applicable to the communication and radar systems operating over non-contiguous carriers or frequency slots. Typical examples of such systems are overlay cognitive radio or cognitive radar networks. First, we derive the periodic- and aperiodic-correlation lower bounds for single-channel SCSs and multi-channel SCSs by convex optimization in the frequency domain. Each of these bounds reduces to a Welch bound when the number of forbidden carriers is set to zero. We then propose systematic constructions of optimal unimodular single-channel SCSs with the aid of cyclic difference sets and the theory of maximal-length shift register sequences.

With increasing demand of wireless radio spectrum, fixed spectrum assignment policy leads to spectrum scarcity worldwide. However, most portion of spectrum is inefficiently used, which urges the development of dynamic spectrum access techniques [1]. The concept of cognitive radio (CR) is proposed as a possible solution to solve the spectral congestion problem. It provides the capability to utilize spectrum bands more efficiently in an opportunistic manner without much interruptions to primary users [2]?[4]. In the cognitive radio networks (CRNs), sensors are used to detect the presence of licensed users and find spectrum holes for dynamic spectrum access. Traditional spectrum sensing is usually carried out by CR nodes. This procedure requires complex computation and sufficient storage space to download software packages.

In this paper, a novel unified power allocation (PA) framework is proposed for receive (pre-coding aided) spatial modulation (RSM). We find that the PA matrix design can be formulated as a non-convex quadratically constrained quadratic program (QCQP) problem, whose solution is generally intractable. To tackle this problem, we propose a pair of solvers having different trade-offs in terms of biterror- rate (BER) and complexity. Specifically, we first propose a successive convex approximation (SCA) method, to convert the non-convex QCQP problem under consideration into a series of linear convex subproblems, where the latter can be easily solved by the classic polynomial-time based optimization method, i.e., the interior point method. To further reduce the computational complexity, we propose an augmented Lagrangian multiplier (ALM) method, which transforms the challenging non-convex constrained PA optimization problem into its unconstrained counterpart, which can be efficiently solved by an iterative manner. Our simulation results show that both the proposed SCA and ALM methods are capable of substantially improving the system error performance compared with conventional RSM system without PA as well as conventional PA-aided RSM schemes.

This letter is focused on increasing the zero correlation zone (ZCZ) of even-length binary Z-complementary pairs (EB-ZCPs). Till date, the maximum ZCZ ratio (i.e., ZCZ width over the sequence length) for systematically constructed EB-ZCPs is 2/3. In this letter, we give a construction of EB-ZCPs with lengths 2 ^±+2 10 ^² 26 ^{³ + 2} (where ±, ², and ³ are nonnegative integers) and ZCZ widths 3 × 2 ^± 10 ^² 26 ^³ + 1, thus achieving asymptotic ZCZ ratio of 3/4. The proposed EB-ZCPs are constructed via proper insertion of concatenated odd-length binary ZCPs. The ZCZ width is proved by exploiting several newly identified intrinsic structure properties of binary Golay complementary pairs, obtained from Turyn's method. The proposed EB-ZCPs have aperiodic autocorrelation sums (AACS) magnitude of 4 outside the ZCZ region (except for the last time-shift taking AACS value of zero).

In this paper, we use the block orthogonal matching pursuit (BOMP) algorithm to recover block sparse signals x from measurements y = Ax + v, where v is an ?2-bounded noise vector (i.e., kvk2 d ë for some constant ë). We investigate some sufficient conditions based on the block restricted isometry property (block-RIP) for exact (when v = 0) and stable (when v , 0) recovery of block sparse signals x. First, on the one hand, we show that if A satisfies the block-RIP with ´K+1 < 1/?K + 1, then every block K-sparse signal x can be exactly or stably recovered by BOMP in K iterations. On the other hand, we show that, for any K e 1 and 1/?K + 1 d ´ < 1, there exists a matrix A satisfying the block-RIP with ´K+1 = ´ and a block K-sparse signal x such that BOMP may fail to recover x in K iterations. Then, we study some sufficient conditions for recovering block ±-strongly-decaying K-sparse signals. We show that if A satisfies the block-RIP with ´K+1 < ?2/2, then every ±-strongly-decaying block K-sparse signal can be exactly or stably recovered by BOMP in K iterations under some conditions on ±. Our newly found sufficient condition on the block-RIP of A is less restrictive than that for ?1 minimization for this special class of sparse signals. Furthermore, for any K e 1, ± > 1 and ?2/2 d ´ < 1, the recovery of x may fail in K iterations for a sensingmatrix A which satisfies the block-RIP with ´K+1 = ´. Finally, we study some sufficient conditions for partial recovery of block sparse signals. Specifically, if A satisfies the block-RIP with ´K+1 < ?2/2, then BOMP is guaranteed to recover some blocks of x if these blocks satisfy a sufficient condition. We further show that this condition is also sharp.

This paper is focused on a vehicle-to-vehicle (V2V) communication system operating at a road intersection, where the communication links can be either line-of-sight (LOS) or non-line-of-sight (NLOS). We present a semi-empirical analysis of the packet delivery ratio of dedicated short-range communication (DSRC) safety messages for both LOS and NLOS scenarios using a commercial transceiver. In a NLOS scenario in which the reception of a safety message may be heavily blocked by concrete buildings, direct communication between the on-board units (OBUs) of vehicles through the IEEE 802.11p standard tends to be unreliable. On the basis of the semi-empirical result of safety message delivery at an intersection, we propose two relaying mechanisms (namely, simple relaying and network-coded relaying) via a road-side unit (RSU) to improve the delivery ratio of safety messages. Specifically, we designed RSU algorithms to optimize the number of relaying messages so as to maximize the message delivery ratio of the entire system in the presence of data packet collisions. Numerical results show that our proposed relaying schemes lead to a significant increase in safety message delivery rates.

Single-channel blind source separation (SCBSS) of uncoordinated, non-spread, co-frequency interfering signals with non-zero carrier frequency offset and timing offset, and without training sequence for channel estimation, is a challenging task. Iterative SCBSS of coded signals leads to good performance but is computationally expensive as it involves the turbo processing of multi-user per-survivor processing and soft-input soft-output channel decoding. In this letter, we propose a low-complexity SCBSS (LC-SCBSS) scheme, which reduces the computational complexity of the conventional iterative SCBSS by using interference-cancellation from the second iteration onward, and adaptive channel truncation for certain users. Simulation results show that the proposed LC-SCBSS reduces the computational complexity by more than 99%, with only a marginal degradation in performance.

Complementary sets of sequences (CSS) and complete complementary codes (CCC) have found numerous applications in wireless communications and radar sensing owing to their perfect aperiodic correlation properties. In this paper, we first present a new algorithm for generating polyphase CSS and CCC based on paraunitary (PU) matrices which uses equivalent forms of unimodular unitary matrices. Then, we propose a multiplier-free implementation of this generator based on multiplexers and read-only memories (ROMs). Our proposed algorithm generalizes the previous PU generator for complementary pairs by Budiain and Spasojevi?. Some previous algorithms for CSS and CCC can also be derived from our CCC generator as special cases. In addition, we give the enumeration formula and show that the number of generated sequences is significantly higher compared to previous works.

In this paper, we present a novel sequence design for efficient channel estimation in multiple input multiple output filterbank multicarrier (MIMO-FBMC) system with offset QAM modulation. Our proposed sequences, transmitted over one FBMC/OQAM symbol, are real-valued in the frequency domain and display zero-correlation zone properties in the time-domain. The latter property enables optimal channel estimation for a least-square estimator in frequency-selective fading channels. To further improve the system performance, we mitigate the data interference by an iterative feedback loop between channel estimation and FBMC demodulation. Simulation results validate that our proposed real-valued orthogonal sequences and the iterative channel estimation and demodulation scheme provide a practical solution for enhanced performance in preamble-based MIMO-FBMC systems.

Z-complementary code set (ZCCS), an extension of perfect CCs, refers to a set of 2-D matrices having zero correlation zone properties. ZCCS can be used in various multi-channel systems to support, for example, quasi-synchronous interference-free multicarrier code-division multiple access communication and optimal channel estimation in multiple-input multiple-output systems. Traditional constructions of ZCCS heavily rely on a series of sequence operations which may not be feasible for rapid hardware generation particularly for long ZCCSs. In this paper, we propose a direct construction of ZCCS using the second-order Reed?Muller codes with efficient graphical representation. Our proposed construction, valid for any number of isolated vertices present in the graph, is capable of generating optimal ZCCS meeting the set size upper bound.

This paper presents a family of training preambles for offset QAM (OQAM) based filter-bank multi-carrier (FBMC) modulations with low peak-to-average power ratio (PAPR) property. We propose to use binary Golay sequences as FBMC preambles and analyze the maximum PAPR for different numbers of zero guard symbols. For both the PHYDYAS and Hermite prototype filters with overlapping factor of 4, as an illustration of the proposed preambles, we show that a preamble PAPR less than 3 dB can be achieved with probability of one, when three or more zero guard symbols are inserted in the vicinity of each preamble.

As a special case of sparse code multiple access (SCMA), low-density signatures based code-division multiple access (LDS-CDMA) was widely believed to have worse error rate performance compared to SCMA. With the aid of Eisenstein numbers, we present a novel class of LDS which can achieve error rate performances comparable to that of SCMA in Rayleigh fading channels and better performances in Gaussian channels. This is achieved by designing power-imbalanced LDS such that variation of user powers can be seen both in every chip window and the entire sequence window. As LDS-CDMA is more flexible in terms of its backwards compatibility, our proposed LDS are a promising sequence candidate for dynamic machine-type networks serving a wide range of communication devices.

The 5th generation (5G) mobile networks and beyond need to support massive machine-type communications (MTC) devices with limited available radio resources. In this paper, we study the power-domain non-orthogonal multiple access (NOMA) technology to support energy-efficient massive MTC networks, where MTC devices exchange information using sporadic and low-rate short packets. We investigate the subchannel allocation and power control policy to maximize the achievable effective energy efficiency (EE) for uplink NOMA-based massive MTC networks, taking into account of short-packet communication characteristics. We model the subchannel allocation problem as a multi-agent Markov decision process and propose an efficient Q-learning algorithm to solve it. Furthermore, we obtain the optimal transmission power policy by approximating the achievable effective rate of uplink NOMA-based short packet communications. Compared with the existing OFDMA scheme, simulations validate that the proposed scheme can improve the achievable effective EE of massive MTC networks with 5.93%.

The concept of massive spatial modulation (SM) assisted vertical bell labs space-time (V-BLAST) (SM-VBLAST) system [1] is proposed, where SM symbols (instead of conventional constellation symbols) are mapped onto the VBLAST structure. We show that the proposed SM-VBLAST is a promising massive multiple input multiple output (MIMO) candidate owing to its high throughput and low number of radio frequency (RF) chains used at the transmitter. For the generalized massive SM-VBLAST systems, we first derive both the upper bounds of the average bit error probability (ABEP) and the lower bounds of the ergodic capacity. Then, we develop an efficient error correction mechanism (ECM) assisted compressive sensing (CS) detector whose performance tends to achieve that of the maximum likelihood (ML) detector. Our simulations indicate that the proposed ECM-CS detector is suitable both for massive SM-MIMO based point-to-point and for uplink communications at the cost of a slightly higher complexity than that of the compressive sampling matching pursuit (CoSaMP) based detector in the high SNR region.

Targeting to provide reliable short-packet communications with tens of bits in machine-type networks, we investigate a novel sparse code multiple access (SCMA) scheme called delayed bit-interleaved coded SCMA (DBIC-SCMA). At the transmitter side, a delay module is introduced between each channel encoder and SCMA mapper such that data bits from different channel codewords can be mapped to an identical SCMA codeword. We present the main components and principles for the transmitter of DBIC-SCMA, followed by a pre-decoding assisted receiver design which exploits systematic and rate-adaptive properties of certain channel codes. Our simulation results show that the proposed DBIC-SCMA leads to significant improvements in error rate performance over the classical BIC-SCMA scheme.

Vehicular networks, an enabling technology for Intelligent Transportation System (ITS), smart cities, and autonomous driving, can deliver numerous on-board data services, e.g., road-safety, easy navigation, traffic efficiency, comfort driving, infotainment, etc. Providing satisfactory quality of service (QoS) in vehicular networks, however, is a challenging task due to a number of limiting factors such as hostile wireless channels (e.g., high mobility or asynchronous transmissions), increasingly fragmented and congested spectrum, hardware imperfections, and explosive growth of vehicular communication devices. Therefore, it is highly desirable to allocate and utilize the available wireless network resources in an ultra-efficient manner. In this paper, we present a comprehensive survey on resource allocation (RA) schemes for a range of vehicular network technologies including dedicated short range communications (DSRC) and cellular based vehicular networks. We discuss the challenges and opportunities for resource allocations in modern vehicular networks and outline a number of promising future research directions.