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This paper concerns the uplink of multicell multiuser multiple-input multiple-output (MIMO) systems. To tackle the effect of pilot contamination that is generally viewed as a bottleneck in previous work, this paper presents a superimposed pilot (SP)-aided uplink channel estimation scheme and mathematically characterizes the impact that an SP has on the performance of such a very large MIMO system. It is shown that there are two types of interference components that do not vanish, even when the number of antennas $M$ grows to infinity. The first type, which is referred to as cross-contamination, is due to the correlation between the SP and data among different cells. The second type, which is referred to as self-contamination, is due to the dependence between channel estimation and estimation error. Cross-contamination is, in principle, similar to pilot contamination in a conventional pilot-based multicell MIMO system, whereas self-contamination is unique for the SP-aided scheme. Both theoretical and simulation results demonstrate that the SP-aided scheme can effectively reduce the estimation contamination by increasing the data frame size and, in turn, achieve a significant improvement over the spectral efficiency, in comparison with conventional pilot-based methods. [ABSTRACT FROM AUTHOR]

Multicell coordinated beamforming (CB) can mitigate intercell interference (ICI). However, existing work on CB focuses on systems that maximize overall throughput. This paper considers CB for systems with multiple receive antennas and further extends the CB to multiuser and multistream transmission. We consider fairness and pay close attention to cell-edge users. CB that maximizes the harmonic sum of signal-to-interference-plus-noise ratio (SINR) can be derived into a low-complexity algorithm that favors cell-edge users. Two iterative algorithms are developed. From the simulation results, the proposed algorithms can provide a better fifth-percentile user throughput compared with the CB algorithms minimizing mean square error, maximizing uplink SINR, and maximizing weighted sum rate. Furthermore, the computational complexity of the proposed algorithms is significantly lower than that maximizing the minimum SINR of users. [ABSTRACT FROM AUTHOR]

In this paper, we study user selection (US) strategies for a multiple-input–multiple-output (MIMO) cognitive radio (CR) downlink network, where the r-antenna underlay CR secondary users (SUs) coexist with a primary user (PU), and all terminals are equipped with multiple antennas. Two main scenarios are considered: 1) The t-antenna cognitive base station (CBS) has perfect or partial channel state information at the transmitter (CSIT) from the CBS to the PU receiver (RX), and 2) the CBS has absolutely no PU CSIT. For these scenarios, we propose and evaluate multiple SU selection schemes that are applicable to both best-effort PU interference mitigation and hard interference temperature (IT) constraints. The computational complexity of the proposed schemes can be significantly smaller than that of an exhaustive search with negligible performance degradation. For the selection of C SUs out of K, whereas an exhaustive search is on the order of \mathcal{O}(\binom{K}{C}C^4r^3). When t$ and r$ are of the same order, the computational complexity of the proposed scheme can be \binom{K}{C}C^4/K times smaller. Mathematical complexity analysis and numerical simulations are provided to show the advantage of our schemes. [ABSTRACT FROM PUBLISHER]

In this paper, we investigate the problem of spectrum leasing in cognitive radio (CR) networks, while incorporating two advanced physical-layer technologies, i.e., multiple-input multiple-output (MIMO) and distributed interference alignment. We present a cooperative spectrum leasing scheme for primary and secondary users to balance the tension between data transmission and revenue collection/payment. A Stackelberg game is formulated, where the primary user is the leader, and secondary users are followers. With backward induction, we derive the optimal strategies for primary and secondary users that can achieve the unique Stackelberg equilibrium, where no player can gain by a unilaterally changing strategy. We find that spectrum leasing is always beneficial to enhancing the utilities of primary and secondary users. The proposed scheme outperforms a no-spectrum-leasing scheme and a cooperative scheme presented in the literature with considerable gains, which demonstrate the benefits of spectrum leasing and distributed interference alignment and validates the efficacy of the proposed scheme. [ABSTRACT FROM PUBLISHER]

In this paper, a cocktail approach is proposed to delicately integrate the two conventional countermeasures, i.e., the fractional pilot reuse and time-shifted pilots (TSP) schemes, for the pilot contamination problem in the full-duplex massive multiple-input multiple-output system. Specifically, the TSP scheme is applied to duplicate for the inner and edge regions of a cell such that the number of accommodated users can be doubled. To achieve this, the base station should operate in the full-duplex mode; also, the pilot symbols rather than the pilot sequences are used to attain the user diversity gain. The simulation results verify the accuracy of the numerical analysis and the remarkably boosted sum rate for both the downlink and uplink cases. [ABSTRACT FROM AUTHOR]

In multi-user multi-cell multiple-input multiple-output (MIMO) visible light communication (VLC) systems, inter-cell interference (ICI) and inter-user interference (IUI) are the two key factors that could severely degrade the system performance. In this paper, for the first time, a novel joint precoder and equalizer design based on interference alignment is proposed to mitigate both IUI and ICI in multi-user multi-cell MIMO VLC systems under imperfect channel state information (CSI). The proposed approach aims to choose proper precoder and receiving equalizer to minimize the mean square error (MSE) under the unique optical power constraints in VLC. Furthermore, we consider optical channel estimation error in our formulated joint optimization problem when designing the joint precoder and receiving equalizer in multi-user multi-cell MIMO VLC systems. Numerical results show that the proposed design achieves a better performance under different users locations, channel estimation errors, and transmitter/receiver spacing, compared to the existing minimum mean square error (MMSE) and max-rate designs. Especially, when the transmit optical power is 12 W per light emitting diode (LED) lamp, our proposed design achieves a sum rate improvement of up to 18.2% and 28.7% as compared with the MMSE and max-rate designs, respectively. In addition, the proposed design can save about 1.4 and 4.3 W optical power per LED lamp as compared with the MMSE and max-rate designs, respectively, at a target bit error rate (BER) of 10 $^{-3}$. [ABSTRACT FROM AUTHOR]

In this correspondence paper, we design a massive nonorthogonal multiple access (NOMA) scheme with delay provisioning for cellular internet-of-things. In the context of massive access, the severe interuser interference decreases the quality of the received signal, such that it is a nontrivial task to provide a delay provisioning for heterogeneous wireless services. To solve this challenge, we propose a massive NOMA scheme to meet the delay requirements of a large number of users by exploiting the properties of rateless codes. Especially, we present a power allocation algorithm to minimize the power consumption while achieving delay-constrained massive access. Finally, simulation results validate the effectiveness of the proposed scheme. [ABSTRACT FROM AUTHOR]

This paper studies the degrees of freedom (DoF) of two-way $2\times 2\times 2$ MIMO interference networks, a class of two-way four-unicast networks. We first provide upper and lower bounds on the sum DoF of general two-way $2\times 2\times 2$ MIMO interference networks with any number of antennas in each node. We then investigate the special case where all user nodes have $M$ antennas and relay nodes have $N$ antennas, and provide the simplified bounds on the sum DoF. We show that our proposed achievable rate for this special case is higher than the achievable rates recently proposed in. Moreover, for this special case, we obtain the exact DoF $=4M$ when $N \geq 2M$ , and DoF $=4N$ when $M \leq 2N$. [ABSTRACT FROM AUTHOR]

Cellular networks are increasingly densified to deal with the fast growing wireless traffic. Interference mitigation plays a key role for the dense cellular networks. Successive interference cancellation (SIC) and fractional frequency reuse (FFR) are two representative inter-cell interference (ICI) mitigation techniques. In this paper, we study the application of both SIC and FFR for LTE uplink networks, and develop an analytical model to investigate their interactions and impact on network performance. The performance gains with FFR and SIC are related to key system functionalities and variables, such as SIC parameters, FFR bandwidth partition, uplink power control and sector antennas. The ICIs from individual cell sectors are approximated by log-normal random variables, which enables low complexity computation of the aggregate ICI with FFR and SIC. Then, network performance of site throughput and outage probability is computed. The model is fast and has small modeling deviation, which is validated by simulations. Numerical results show that both SIC and FFR can largely improve network performance, but SIC has a stronger impact than FFR. In addition, most of the network performance gains with SIC could be obtained with a small number of SIC stages applied to a few sectors. [ABSTRACT FROM AUTHOR]

Low-complexity linear precoders are known to be close to optimal for massive multiple-input multiple-output (M-MIMO) systems. However, the large number of antennas at the transmitter imposes a high computational burden and high hardware overloads. In line with this, in this paper, we propose a low-complexity antenna selection (AS) scheme that selects the antennas that maximize constructive interference between the users. Our analyses show that the proposed AS algorithm, in combination with a simple matched-filter (MF) precoder at the transmitter, is able to achieve better performances than systems equipped with a more complex channel inversion (CI) precoder and computationally expensive AS techniques. First, we give an analytical definition of constructive and destructive interference, based on the phase of the received signals from phase-shift-keying-modulated transmissions. Then, we introduce the proposed AS algorithm, which identifies the antenna subset with the highest constructive interference, maximizing the power received by the user. In our study, we derive the computational burden of the proposed technique with a rigorous and thorough analysis, and we identify a closed-form expression of the upper bound received power at the user side. In addition, we evaluate in detail the power benefits of the proposed transmission scheme by defining an efficiency metric based on the achieved throughput. The results presented in this paper prove that AS and green radio concepts can be jointly used for power-efficient M-MIMO, as they lead to significant power savings and complexity reductions. [ABSTRACT FROM AUTHOR]

This paper considers a two-cell uplink cochannel multiple-input–multiple-output (MIMO) network with users sequentially arriving at the network. We study the problem of sequential base-station (BS) selection for the users, with the selection criterion based on the degrees of freedom (DoFs) available for the new arriving user. We find that different sequential BS selections affect individual and network performance in terms of the individual and network sum DoF, as well as the number of admissible users in the network. We propose a method to build the tree structure for sequential BS selection, which carries trellis information for individual and system-wide selections. The properties of the tree are analytically studied. It turns out that by adopting an interference coordination strategy based on the concept of interference alignment (IA), better individual and network performance can be achieved. Simulation compares the proposed DoF-based BS selection and traditional BS selection schemes and highlights the advantages of the proposed scheme. [ABSTRACT FROM PUBLISHER]

We investigate the performance of multiuser multiple-input-single-output (MU-MISO) downlink in the presence of the mutual coupling effect at the transmitter. Contrary to traditional approaches that aim at eliminating this effect, in this paper we propose a joint analog–digital (AD) beamforming scheme that exploits this effect to further improve the system performance. A jointly optimal AD beamformer is first obtained by iteratively maximizing the minimum received signal-to-interference-plus-noise ratio in the digital domain, followed by an optimization on the load impedance of each antenna element in the analog domain. We further introduce a decoupled low-complexity approach, with which existing closed-form beamforming schemes can also be efficiently applied. For the consideration of hardware imperfections in practice, we study the case where the analog load values are quantized, and propose a sequential search scheme based on greedy algorithm to efficiently obtain the desired quantized load values. Moreover, we also investigate the imperfect channel state information (CSI) scenarios, where we prove the optimality for closed-form beamformers, and further propose the robust schemes for two typical CSI error models. Simulation results show that with the proposed schemes the mutual coupling effect can be exploited to further improve the performance for both perfect CSI and imperfect CSI. [ABSTRACT FROM PUBLISHER]

In this paper, a low-complexity detection scheme is proposed for an underdetermined multiple-input–multiple-output (UD-MIMO) wireless communication system that employs $N$ transmit antennas and M < N$ receive antennas. The proposed scheme combines a simplified parallel interference cancelation (S-PIC) with the block decision feedback equalization (BDFE) algorithm. To account for the extra (N - M)$-dimension in the transmitted signal, the UD-MIMO system is partitioned into two subsystems: one with (N - M)$ transmit antennas and the other one with M sequences in the first subsystem, with $Q$ being the constellation size, the proposed scheme explores only a small number of candidate sequences in the first subsystem; thus, it achieves significant complexity reduction. Two new candidate sequence selection methods are proposed. In the first iteration, the candidate sequences used for PIC are selected by exploring the statistical properties of the received signals. In the second iteration and beyond, the set containing the candidate sequences is constructed by utilizing the soft information generated from the previous iteration. The proposed scheme provides a balanced tradeoff between computational complexity and bit error rate (BER) performance. [ABSTRACT FROM PUBLISHER]

Interrelay interference (IRI) is known to limit the performance of virtual full-duplex (VFD) relaying schemes. Available interference cancelation schemes are unable to simultaneously improve the diversity and maintain the multiplexing gain of VFD relaying schemes in multiple antennas scenarios. In this paper, we propose a technique to improve the reliability of multiantenna VFD relaying scheme, while maintaining the multiplexing gain in the presence of IRI. In the proposed scheme, the source and interrelay channels are concatenated and their signals are jointly decoded at the relay. A superposition of the decoded messages is forwarded to the destination. To reduce the effect of IRI on the receiving relay, two suboptimal relay transmit antenna selection schemes, namely, random antenna selection and maximum capacity antenna selection, are investigated. The system capacity and outage probability bounds of the proposed scheme are derived in closed form. The diversity and multiplexing tradeoff is also characterized. The analytical and numerical results show that the proposed scheme can achieve full diversity and maintain the multiplexing gain of the full-duplex relaying scheme. Also, the proposed scheme can outperform conventional VFD relaying scheme in terms of reliability even in the presence of IRI. [ABSTRACT FROM PUBLISHER]

Due to the unique physical-layer characteristics associated with multiple-input multiple-output (MIMO) and cognitive radio (CR), the network performance is tightly coupled with mechanisms at the physical, link, network, and transport layers. In this paper, we consider an energy-efficient cross-layer optimization problem in multihop MIMO CR networks (CRNs) and provide a new formulation to balance the weighted network utility and the weighted power consumption of secondary users (SUs), with the minimum transmission rate constraint of primary users (PUs) and the SU power consumption constraint. However, this formulation is highly challenging due to the nonconvexity of the PU rate constraint. We propose a solution that features a linearization-based alternative optimization method and a heuristic primal recovery method. We further develop a distributed algorithm to jointly optimize the covariance matrix of the transmitted signal vector at each SU node, bandwidth allocation at each SU link, rate control at each session source, and multihop/multipath routing. Extensive simulation results demonstrate that the performance of the proposed distributed algorithm is very close to that of the centralized algorithm, and the proposed formulation provides an efficient way to save power consumption significantly, while achieving the network utility very close to that achieved with full power consumption. [ABSTRACT FROM PUBLISHER]

Interference alignment (IA) is a promising transmission technology enabling, essentially, the maximum achievable degrees of freedom (DOF) in $K$-user multiple-input–multiple-output (MIMO) interference channels. The ideal DOF of IA systems have been obtained using independent MIMO channels, which is, usually rarely observed in reality, particularly in indoor environments. Therefore, the data sum rate and symbol error-rate of IA are dramatically degraded in real-world scenarios since the correlation between MIMO channels decreases the signal-to-noise ratio (SNR) of the received signal after alignment. For this reason, an acceptable sum rate of IA in real MIMO-orthogonal frequency-division multiplexing (MIMO-OFDM) interference channels was obtained in the literature by modifying the distance between network nodes and the separation between the antennas within each node to minimize the spatial correlation. In this paper, we propose to apply transmit antenna selection to MIMO-OFDM IA systems either through bulk or per-subcarrier selection, aiming at improving the sum-rate and/or error-rate performance under real-world channel circumstances, while keeping the minimum spatial antenna separation of 0.5 wavelengths within each node. Two selection criteria are considered: maximum sum rate (Max-SR) and minimum error rate (Min-ER). To avoid subcarrier imbalance across the antennas of each user, which is caused by per-subcarrier selection, a constrained per-subcarrier antenna selection is operated. Furthermore, a suboptimal antenna selection algorithm is proposed to reduce the computational complexity of the optimal algorithm. An experimental validation of MIMO-OFDM IA with antenna selection in an indoor wireless network scenario is presented. The experimental results are compared with deterministic channels that are synthesized using hybrid electromagnetic (EM) ray-tracing models. Our performance evaluation shows that the practical feasibility of MIMO-OFDM IA systems is significantly increased by antenna selection in real-world scenarios. [ABSTRACT FROM AUTHOR]

Multiuser orthogonal frequency-division multiplexing (OFDM) and multiple-output multiple-output (MIMO) have been widely adopted to enhance the system throughput and combat the detrimental effects of wireless channels. Interference alignment has been proposed to exploit interference to enable concurrent transmissions of multiple signals. In this paper, we investigate how to combine these techniques to further enhance the system throughput. We first reveal the unique characteristics and challenges brought about by using interference alignment in diagonal channels. We then derive a performance bound for the multiuser (MIMO) OFDM interference alignment system under practical constraints and show how to achieve this bound with a decomposition approach. The superior performance of the proposed scheme is validated with simulations. [ABSTRACT FROM PUBLISHER]

In this paper, we consider unicast/multicast multicell cooperative transmission with interference among users/user groups. In this context, we derive the optimal minimum variance distortionless response (MVDR)-based successive minimum variance beamforming (SMVB) scheme that achieves a superior sum-rate performance compared with the block diagonalization scheme. Subsequently, we derive an optimal joint power allocation and broadcast beamforming scheme for multicell cooperative broadcast transmission for a pooled power constraint at the base stations. This scheme is extended to include per base station power constraints by formulating it as a relaxed semi-definite program (SDP). We also consider the multicell cooperative uplink scenario and derive a successive multiuser (MU) uplink beamforming (SMUB) scheme that maximizes the signal-to-interference-plus-noise ratio (SINR) of each user. Next, we consider imperfect channel state information (CSI) and derive a robust beamforming scheme for the downlink, based on minimizing the worst-case interference by formulating it as a second-order cone program. It is demonstrated that the corresponding robust beamformer for the uplink transmission can be derived by employing the multidimensional covariance fitting approach. Simulation results are presented to demonstrate the superior sum-rate performance of the proposed multicell transmission schemes. The performance is also compared with several bounds for cooperative multicell scenarios. [ABSTRACT FROM AUTHOR]

Edge caching is emerging as the most promising solution to reduce the content retrieval delay and relieve the huge burden on the backhaul links in the ultra-dense networks by proactive caching popular contents in the small base station (SBS). However, constraint cache resource of individual SBSs significantly throttles the performance of edge caching. In this paper, we propose a device-to-device (D2D) assisted cooperative edge caching (DCEC) policy for millimeter (mmWave) dense networks, which cooperatively utilizes the cache resource of users and SBSs in proximity. In the proposed DCEC policy, a content can be cached in either users’ devices or SBSs according to the content popularity, and a user can retrieve the requested content from neighboring users via D2D links or the neighboring SBSs via cellular links to efficiently exploit the cache diversity. Unlike existing cooperative caching policies in the lower frequency bands that require complex interference management techniques to suppress interference, we take advantage of directional antenna in mmWave systems to ensure high transmission rate whereas mitigating interference footprint. Taking the practical directional antenna model and the network density into consideration, we derive closed-form expressions of the backhaul offloading performance and content retrieval delay based on the stochastic information of network topology. In addition, analytical results indicate that, with the increase of the network density, the content retrieval delay via D2D links increases significantly while that via cellular links increases slightly. Comprehensive simulations validate our theoretical analysis and demonstrate that the proposed policy can achieve higher performance in offloading the backhaul traffic and reducing the content retrieval delay compared with the state-of-the-art most popular caching policy. [ABSTRACT FROM AUTHOR]

In this paper, we develop beamforming (BF) schemes to minimize the total transmitted power of both uplink (UL) and downlink (DL) in two-tier network with in-band wireless backhaul (WB) while the target rates of user equipment (UE) are satisfied under the backhaul constraints. We propose a centralized BF scheme with an alternate update algorithm optimizing the BF matrices and power allocation vectors. Then the UL-DL feasible target rate region of the proposed scheme is analyzed, which can be enlarged in both UL and DL by increasing the number of antennas of small cell base stations (SBSs). Simulation results show that the proposed in-band WB system for two-tier network can save the power consumption by 33.5% and 82.1% compared with the out-of-band WB system and conventional one-tier network, respectively, at the UE target rates of 80 Mb/s in DL and 40 Mb/s in UL. In addition, we propose a distributed BF scheme to locally optimize the variables at each SBS, which can achieve above 90% of the feasible target rate region of the centralized scheme without the instantaneous information exchange. [ABSTRACT FROM AUTHOR]

Recently, heterogeneous network (HetNet) has been introduced as an appropriate strategy to cope with the explosive growth of wireless traffic. To address the issue of severe interference in the HetNet, we can consider interference alignment (IA), which achieves the maximum degrees of freedom (DOFs) in multiple-input–multiple-output (MIMO) interference channels (ICs). However, an anticipated performance of the MIMO IA is difficult to be clarified, particularly with different numbers of antennas across the nodes when designing an appropriate system. In this paper, we thus study antenna configurations for the three-user MIMO IA with respect to the intended data stream tuple, i.e., DOF. For simple analysis, we consider two-tier network with two types of data stream numbers in a system. First, the dimension of the subspace occupied by interference is derived by aligning the interference in the signal space of the MIMO IA. After this, the suitable numbers of antennas are computed depending on the transmitted data stream numbers. Our obtained results provide an insight on how the performance of the MIMO IA is affected as the system configurations change. Furthermore, we discuss how to maximize the performance of such systems when the available numbers of antennas are finite. The actual simulations with an iterative IA confirm the validity of our derived results. [ABSTRACT FROM PUBLISHER]

In this paper, we propose a new three-user network information flow model, referred to as the triangular multiple-input–multiple-output (MIMO) relay (TMR) channel, which consists of three users and three relays equipped with nU and nR antennas, respectively. Each user sends two independent messages to the other two users via the adjacent relays in two time slots, which are referred to as the multiple-access and broadcast stages. We derive a novel simultaneous signal and interference alignment for the proposed TMR channel in a scenario where there are fewer antennas at each relay than at each user (nR < nU ) . An optimized pseudo-inverse scheme based on an efficient gradient projection algorithm is proposed to solve the simultaneous alignment problem. By deriving a gradient over weighted sum-rate maximization and applying a gradient descent method, the optimal beamforming vectors are obtained to maximize the effective signal-to-noise ratios. Furthermore, to obtain rapid convergence speed and reduce computational complexity, we introduce a quasi-Newton method, which is referred to as the Broyden–Fletcher–Goldfarb–Shanno algorithm, by approximating the Hessian matrix of a pure Newton method. The convergence of the proposed gradient algorithm is guaranteed by proposing a line search algorithm. Finally, a performance evaluation shows that the proposed scheme offers a higher sum rate, produces a better outage probability, and achieves a higher multiplexing gain than the existing schemes. [ABSTRACT FROM PUBLISHER]

For massive multiuser multiple input multiple output (MIMO) (MU-MIMO) systems, pilot contamination (PC) and data interference (DI) are two main factors that affect the accuracy of the superimposed pilot (SP) based channel estimation, provided that the channel coherence time is less than the total number of users. In this paper, to tackle the effect of the PC, we propose a block-diagonal Grassmannian line packing (GLP) approach, in which the specific sequences for different cells are first designed based on the GLP, and then are block-diagonally extended to form the SP matrices for the users in different cells. To also alleviate the effect of DI on the channel estimation, with the designed SP matrices, an iterative channel estimation (ICE) method based on Tikhonov regularization is presented. The impact that the proposed ICE method has on the signal-to-interference-plus-noise ratio with matched filtering receiver is theoretically analyzed. Moreover, the optimal power allocation factor to the SP by maximizing the spectral efficiency (SE) of the target cell is also derived. Numerical results show that the proposed ICE method with the designed SP matrices effectively mitigates the effects of the PC and DI, and hence, improves the accuracy of channel estimation and further the SE of the massive MU-MIMO systems. [ABSTRACT FROM AUTHOR]

A major challenge in designing a spectral co-existence between radar and communication systems is how to simultaneously provide efficient utilization of the shared spectrum while maintaining a reliable performance for both systems. Due to its flexibility in using linear independent waveforms and superiority in terms of target detection and estimation, the collocated multiple-input-multiple-output (MIMO) radars provide a paramount capability in realizing spectrum sharing with communication systems. In this paper, we consider the use of joint transmit and receive beamformers for both the MIMO radar and MIMO communication systems. Specifically, we design a two-tier alternating optimization spectrum sharing framework that is based on interference alignment (IA) approach. The effectiveness of spectrum sharing between radar and communication systems is guaranteed by mitigating the mutual interference signals in the shared spectral band. Subsequently, motivated by the excellent performance provided by IA in different wireless network scenarios, we propose a spectrum sharing framework that consists of a main iterative algorithm with two subalgorithms included within its operation. The first subalgorithm is used to maximize the signal-to-interference-plus-noise ratio of the radar system, whereas the second one is utilized to maximize the average sum-rate of the communication system. The main iterative algorithm is proposed to jointly optimize the transmit and receive beamforming filters of both systems by performing alternating optimization between the two subalgorithms. The convergences of the proposed algorithm and its subalgorithms are numerically verified. Simulation results are provided to confirm the superiority of the proposed framework for both systems. [ABSTRACT FROM AUTHOR]

In this paper, we investigate the transmitter cooperation based topological interference management (TIM) scheme for MIMO Interference Channels (IC), where there is no channel state information beyond only the topology information at transmitters and receivers to cancel the interference. Specifically, for two different scenarios, i.e., there exists a Hamiltonian cycle or a perfect matching in the alignment-feasible graph, we propose different transmitter cooperation based TIM schemes by jointly designing the precoding and decoding matrices and present one theorem to characterize the achievable degrees of freedom (DoF) of the proposed TIM schemes. Moreover, the numeric results show that the DoF of the proposed scheme can be significantly higher than that by the TIM scheme without transmitter cooperation. [ABSTRACT FROM AUTHOR]

In this paper, we study a network information flow problem for cellular multiuser two-way relay networks (MU-TWRNs) where uplink and downlink messages are exchanged through a multiantenna relay node using two-way relaying. Both single- and two-cell scenarios are investigated. In particular, for the two-cell scenario, we consider two schemes with and without base station (BS) cooperation, respectively. By comparing the degrees-of-freedom (DOF) upper bounds obtained via cut-set theory, we derive the feasibility conditions to achieve the optimal DOF for all the schemes. These DOF bounds are shown to be achieved by suitably applying some physical-layer signaling techniques, such as physical-layer network coding, signal alignment, block diagonalization, and the newly proposed successive interference nulling. By comparing one-way relaying in terms of the normalized DOF, we observe that the proposed two-way-relaying-based scheme can double the performance with symmetric antenna configurations; however, the gain is reduced under unbalanced antenna configurations. [ABSTRACT FROM PUBLISHER]

In this paper, we investigate the resource allocation problem in two-tier heterogenous networks (HetNets) with massive MIMO, where two frequency bands, cellular frequency band and millimeter wave frequency band, are used for wireless backhaul links. To coordinate the interference among small cells (SCs), SCs are grouped into multiple SC clusters (SCCs), where SC users are jointly served by SC base stations (BSs) (SBSs) belonging to the same SCC. To eliminate the multi-user and inter-tier interference, we propose a block diagonalization based precoding scheme at macro-BS and each SCC, where the transmit precoding matrix for users is projected onto the null space of interference channels. Following this, we formulate a power allocation optimization problem to maximize the downlink sum rate of the system subject to per-SCC power and users’ quality of service requirements. Since the formulated problem is nonconvex, we transform it into a convex one by appropriate approximation, and a constrained concave convex procedure based iterative algorithm is proposed to obtain the solution. Furthermore, we prove that the obtained solution converges to the local optimum. Meanwhile, according to the structure of the original formulated problem, we divide it into multiple subproblems and propose an optimal iterative water-filling algorithm. Next, we extend the original problem with per-SBS power constraint, which results in that the precoding of each SCC has to be redesigned. On this basis, we propose an iterative water-filling algorithm to obtain the optimal power allocation and precoding. Numerical results are presented to verify the performance of our proposed algorithms. [ABSTRACT FROM PUBLISHER]

In this paper, we propose an optimal channel training method in the sense of linear minimum mean square error for multiple-input multiple-output amplify-and-forward relay systems in the presence of interference. By using a relay processing matrix, the received interference is cancelled or mitigated. To make the problem tractable, we first derive the optimal structure of the training signal and the relay processing matrix. Then, we propose an optimal channel training method. In order to reduce the complexity, we also propose an asymptotically optimal channel training method. Simulation results demonstrate that the two proposed methods outperform the conventional training signal design methods in terms of both the mean square error and in the bit error rate. [ABSTRACT FROM PUBLISHER]

Full-duplex (FD) multiple-input multiple-output relaying has been considered an effective scheme to increase the spectral efficiency for wireless communications. As known, the main problem for the FD system is the cancellation of loop interference (LI). In this paper, we propose using the joint source/relay precoding to reduce the influence of LI. Therein, linear precoders are used at the source and relay, while the minimum mean-squared-error receiver is adopted at the destination. The joint precoder design is complicated when spatial multiplexing is exploited for signal transmission. To solve the problem, we propose an iterative method in which the original problem is split into two subproblems. With some matrix properties, we then show that each subproblem can be formulated as a convex optimization. Finally, a closed-form solution can be obtained with the Karush–Kuhn–Tucker conditions. Using a mean-squared-error upper bound, we also propose a low-complexity method to reduce the computational complexity. The proposed precoders have closed-form expressions, which is a great advantage in real-world implementation. Simulation results show that the proposed methods significantly outperform existing ones. [ABSTRACT FROM AUTHOR]

In this paper, we investigate the performance of a dual-hop multiple-input–multiple-output (MIMO) amplify-and-forward (AF) relay network, where the source, relay, and destination are all equipped with multiple antennas. By using maximum ratio transmission (MRT) at the transmitter and maximum ratio combining (MRC) at the receiver, we first obtain the output signal-to-interference-plus-noise ratio (SINR) of the dual-hop AF relay system, considering multiple cochannel interferences (CCIs), as well as noise at the relay. Then, we derive an exact closed-form expression for the outage probability (OP), and the asymptotic result of OP at high SNR, which can be used to calculate the array gain and diversity order. Finally, computer simulations are conducted to validate the performance analysis. Our new analytical expressions not only provide a fast and efficient method to evaluate the system performance but enable us to gain valuable insights into the effects of key parameters on the MIMO AF relaying network performance that benefits from implementing multiple antennas at each of the three nodes as well. [ABSTRACT FROM PUBLISHER]

In this paper, we investigate the interference alignment (IA) for the multiple-input–multiple-output (MIMO) multicell downlink networks in the context of a square channel matrix. We propose a novel joint user grouping and base station (BS) association algorithm. Furthermore, we design the transmit and receive beamforming matrices in closed forms by using a generalized eigenvalue decomposition (GEVD)-based IA scheme, which can exploit the special structure of a square channel matrix against the existing algorithm. Moreover, we provide three theorems to characterize the maximum achievable degrees of freedom (DoF) of the proposed GEVD-based IA scheme. Compared with the existing IA scheme, the proposed GEVD-based IA scheme can reduce the dimension of subspace occupied by the intercell interference (ICI) more efficiently, hence providing achievable DoF higher than or equal to that of the existing IA scheme. [ABSTRACT FROM AUTHOR]

Interference alignment (IA) is widely regarded as a promising interference management technique for wireless networks and its potential is most profound in interference-intensive environments. This motivates us to study IA for multicast communications in multihop MIMO networks, which are rich in interference by nature. We develop a set of linear constraints that can characterize a feasible design space of IA for multicast communications. The set of linear constraints constitutes a simple mathematical model of IA that allows us to conduct cross-layer multicast throughput optimization in multihop MIMO networks, but without getting involved into the onerous signal design at the physical layer. Based on the mathematical model of IA, we formulate a multicast throughput maximization problem and develop an approximation solution that can achieve $(1-\varepsilon)$ -optimality. Simulation results show that the use of IA can significantly increase the multicast throughput in multihop MIMO networks and the throughput gain increases with the volume of multicast traffic and the number of antennas. [ABSTRACT FROM AUTHOR]

We investigate the heterogeneous cellular network (HetNet) where the macrocell base stations (MBSs) are equipped with very large antenna arrays. Since such a combined massive multi-input multi-output (MIMO) and HetNet system operates in the co-channel time-division duplex mode, to mitigate the pilot contamination effect to channel estimation, the number of users that can be served simultaneously is limited by the available pilot resources in the conventional designs. We propose a pilot reuse scheme for massive MIMO–HetNet to increase the user capacity. Specifically, location-aware channel estimation is employed at the MBSs to mitigate the severe pilot contamination introduced by pilot reuse, and we propose a novel pilot assignment algorithm to reduce the interference in HetNets. Simulation results demonstrate that our proposed scheme can support more users and increase both the uplink and the downlink sum-rate capacity, in comparison to the conventional scheme, particularly when the antenna number at the MBSs is sufficiently large. [ABSTRACT FROM AUTHOR]

Interference among frequency modulated continues wave automotive radars can either increase the noise floor, which occurs in the most cases, or generate a ghost target in rare situations. To address the increment of noise floor due to interference, we proposed a low calculation cost method using adaptive noise canceller to increase the signal-to-interference ratio. In a quadrature receiver, the interference in the positive half of frequency spectrum is correlated to that in the negative half of frequency spectrum, whereas the beat frequencies from real targets are always present in the positive frequency. Thus, we estimated the power of the negative frequency as an indication of interference, and fed the positive frequency and negative frequency components into the primary and reference channel of an adaptive noise canceller, respectively. The least mean square algorithm was used to solve for the optimum filter solution. As a result, both the simulation and experiment showed a good interference mitigation performance. [ABSTRACT FROM AUTHOR]

We consider the interference alignment (IA) in small cell networks with full-duplex (FD) self-backhauling equipped on each small base station. First, by leveraging the optimization theory and formulating the IA conditions as a 0–1 integer linear programming (ILP) problem, we establish that the optimal solution of the formulated ILP problem is exactly equivalent to that of its associated relaxed linear programming one, then proposing an efficient approach to judge the IA feasibility, even in FD-based small cell networks with more interference signals. Then, given perfect interference elimination, an adaptive power allocation (PA) problem is formulated, followed by an iterative algorithm leveraging first-order approximations, with its convergence assured. Finally, simulations are conducted to reveal the effectiveness of the proposed algorithms, showing that the sum rate of FD-enabled networks can benefit from not only the introduction of FD self-backhauling but also the execution of adaptive PA. [ABSTRACT FROM AUTHOR]

The limited fronthaul capacity imposes a challenge on the uplink of a centralized radio access network (C-RAN). We propose to boost the fronthaul capacity of a massive multiple-input multiple-output (MIMO)-aided C-RAN by globally optimizing the power sharing between channel estimation and data transmission both for the user devices (UDs) and the remote radio units (RRUs). Intuitively, allocating more power to the channel estimation will result in more accurate channel estimates, which increases the achievable throughput. However, increasing the power allocated to the pilot training will reduce the power assigned to data transmission, which reduces the achievable throughput. In order to optimize the powers allocated to the pilot training and to the data transmission of both the UDs and the RRUs, we assign an individual power sharing factor to each of them and derive an asymptotic closed-form expression of the signal-to-interference-plus-noise ratio for the massive MIMO-aided C-RAN consisting of both the UD-to-RRU links and the RRU-to-baseband unit (BBU) links. We then exploit the C-RAN architecture's central computing and control capability for jointly optimizing the UDs’ power sharing factors and the RRUs’ power sharing factors aiming at maximizing the fronthaul capacity. Our simulation results show that the fronthaul capacity is significantly boosted by the proposed global optimization of the power allocation between channel estimation and data transmission both for the UDs and for their host RRUs. As a specific example of 32 receive antennas (RAs) deployed by the RRU and 128 RAs deployed by the BBU, the sum rate of 10 UDs achieved with the optimal power sharing factors improves by 33% compared with the one attained without optimizing power sharing factors. [ABSTRACT FROM AUTHOR]

As a benefit of sophisticated interference cancelation techniques, full-duplex (FD) transceiver design may become feasible, even possibly on the aggressive time-scale of fifth-generation (5G) wireless communication systems. Hence, we further develop the recent bidirectional relaying [i.e., the two-way half-duplex (HD) relaying] aided cooperative network to its more radical counterpart, which entirely consists of FD entities for the sake of adapting to emerging FD communication scenarios. In more detail, the proposed bidirectional relaying-aided FD network operates in a decode-and-forward (DF) style and exploits the advanced network coding (NC) concept. We analyze its achievable error-free data rate, where the effects of both the self-interference (SI) and of the geographic location of the relay node (RN) are evaluated. Furthermore, the potential variations of the networking scenario are also taken into account. Based on this theoretical analysis, the optimum rate allocation scheme maximizing the system's error-free data rate is found. Our results demonstrate that a significant spectral efficiency gain is achieved by the proposed system. [ABSTRACT FROM PUBLISHER]

An interference alignment (IA) transceiver design scheme for multiple-input–multiple-output (MIMO) multicell multiuser wireless communication systems is proposed by minimizing the maximum mean square error (MSE) of the received symbols to improve fairness among users. The formulated Min-Max MSE optimization problem is not jointly convex on the transmit precoders and receive filters and, thus, is very difficult to solve directly. An iterative method is proposed to solve the optimization problem to get a suboptimal solution instead. Considering that if the receive filters are fixed, the Min-Max MSE problem can be reformulated as a second-order cone programming problem, and if the transmit precoders are fixed, the closed-form receive filters minimizing the receive MSE can be easily obtained, and the formulated Min-Max MSE problem is solved by alternatively optimizing the transmit precoders and the receive filters. The convergence of the proposed algorithm is proved, which shows its feasibility. Furthermore, a robust Min-Max MSE algorithm is proposed to counter the channel uncertainty. Simulation results show that the proposed Min-Max MSE algorithm can achieve IA when the antennas are configured to be strong IA proper and when the users in the network are of the same signal-to-noise ratio (SNR). Analysis indicates that the proposed Min-Max IA transceiver design scheme can significantly improve user fairness with a possible cost of sum-rate reduction. Results also show that the proposed robust design algorithm provides better performance when lacking perfect channel state information (CSI). [ABSTRACT FROM AUTHOR]