Signal-to-interference-and-noise Research Articles

Optimal Beamformer Design for Millimeter Wave Dual-Functional Radar-Communication Based V2X Systems

Millimeter wave (MmWave) dual-functional radar-communication (DFRC) technology is believed to hold the ability to alleviate spectrum congestion and inter-radar interference in 5G vehicle-to-everything (V2X) systems. The radar target sizes in V2X system may not be ignored in views of the demands of short-range sensing and ultra-narrow beams supported by massive MIMO mmWave beamforming. Under such scenario, a novel single-target-multi-beams (STMB) radar beam alignment scheme is proposed to acquire more accurate information on estimated ranges and velocities by allocating multiple radar beams to a certain target. For instance, the relative velocity direction can be accurately estimated based on STMB scheme by using a weighted linear estimation methods. Then, the hybrid analog-digital beamforming under STMB scheme is formulated and optimized by maximizing transmission rate subject to radar signal-to-interference-and-noise (SINR) constraints, where a radar beam cancellation algorithm is proposed to adjust adaptively the radar beam number pointing to a certain target, which can guarantee strict radar SINR constraint under different transmission power levels. The numerical results verify the effectiveness and reliability of STMB scheme and show that the proposed beamformer outperforms the benchmark in both spectral efficiency and minimum radar SINR.

Maximization of multicast periodic traffic throughput in multi-hop wireless networks with broadcast transmissions

Although a number of different medium access control (MAC) schemes are adopted for wireless multi-hop networks, time division multiple access (TDMA) approaches based on a periodic frame of time slots are the most common when very high efficiency is needed in terms of use of radio and energy resources. Efficient resource usage is typically based on parallel compatible transmissions from multiple nodes that guarantee interference control at the receivers. Optimization of transmission scheduling in multi-hop packet delivery from sources to destinations for a set of traffic relations can be achieved by minimizing the frame length where all necessary transmissions are organized in compatible sets and assigned to the time slots of the frame. When properly designed, the resulting TDMA scheme guarantees the delivery of packets for each traffic relation at a rate of up to one packet per frame duration regardless of the number of the packet transmissions (hops) necessary from source to destination, and thus it is particularly suitable for periodic traffic.While similar traffic maximization problems have been studied quite extensively for the case of unicast traffic, its multicast generalization (where each packet should be delivered from the source node to possibly multiple destination nodes) has not been elaborated so far. In this paper we present such a (non-trivial) generalization, namely a mathematical programming model based on the extension of the compatible set concept where the signal-to-noise and interference (SINR) ratio is guaranteed above a threshold at multiple receivers. We first propose an algorithm for solving the problem that generates compatible sets and schedules the frame by splitting the (predefined) multicast routing trees into one-hop transmissions. The high computational efficiency of the algorithm is proven through numerical results on large networks. Next, we enrich the model by adding multicast tree optimization, illustrating its efficiency numerically as well. Finally, we present possible extensions that consider packets of different lengths (requiring multiple slots for transmission), multiple modulation and coding schemes (MCS) requiring different SINR thresholds at the receivers, and packet delay minimization.

Multi-Channel Resource Allocation Toward Ergodic Rate Maximization for Underlay Device-to-Device Communications

In underlay device-to-device (D2D) communications, a D2D pair reuses the cellular spectrum causing interference to regular cellular users. Maximizing the performance of underlay D2D communications requires joint consideration for the achieved D2D rate and the interference to cellular users. In this paper, we consider the D2D power allocation optimization over multiple resource blocks (RBs), aimed at maximizing either the ergodic D2D rate or the ergodic sum rate of D2D and cellular users, under the long-term sum-power constraint of the D2D users and per-RB probabilistic signal-to-interference-and-noise (SINR) requirements for all cellular users. We formulate stochastic optimization problems for D2D power allocation over time. The proposed optimization framework is applicable to both uplink and downlink cellular spectrum sharing. To solve the proposed stochastic optimization problems, we first convexify the problems by introducing a family of convex constraints as a replacement for the non-convex probabilistic SINR constraints. We then present two dynamic power allocation algorithms: a Lagrange dual-based algorithm that is optimal but with a high computational complexity and a low-complexity heuristic algorithm based on dynamic time averaging. Through simulation, we show that the performance gap between the optimal and heuristic algorithms is small, and the effective long-term stochastic D2D power optimization over the shared RBs can lead to substantial gains in the ergodic D2D rate and the ergodic sum rate.

On the Ergodic Achievable Rates of Spectrum Sharing Networks with Finite Backlogged Primary Users and an Interference Indicator Signal

Spectrum sharing networks are communication setups in which unlicensed secondary users (SUs) are permitted to work within the spectrum resources of licensed primary users (PUs). This paper aims to study the ergodic achievable rates of spectrum sharing networks with finite backlogged primary user and an interference indicator signal. Here, in contrast to the standard interference-avoiding schemes, the secondary user activity is not restricted within the primary user inactive periods. Considering both fading and nonfading channels, the unlicensed user ergodic achievable rate is obtained for different unlicensed user transmission power and licensed user received interference power or signal-to-interference-and-noise (SINR) constraints. In the case of fading channels, the results are obtained for both short- and long-term primary user quality-of-service requirements. Further, the results are generalized to the case of multiple interfering users. In terms of unlicensed user ergodic achievable rate, analytical results indicate that while the standard interference-avoiding approach is the optimal transmission scheme at low secondary user or high primary user transmission powers, higher rates can be achieved via simultaneous transmission at high secondary user SINRs. Moreover, numerical results show that, using an interference indicator signal, there is considerable potential for data transmission of unlicensed users under different licensed users quality-of-service requirements.

Therapeutic impact of the stent visualization enhancement technique (StentBoost ®) in percutaneus coronary intervention

Although a number of different medium access control (MAC) schemes are adopted for wireless multi-hop networks, time division multiple access (TDMA) approaches based on a periodic frame of time slots are the most common when very high efficiency is needed in terms of use of radio and energy resources. Efficient resource usage is typically based on parallel compatible transmissions from multiple nodes that guarantee interference control at the receivers. Optimization of transmission scheduling in multi-hop packet delivery from sources to destinations for a set of traffic relations can be achieved by minimizing the frame length where all necessary transmissions are organized in compatible sets and assigned to the time slots of the frame. When properly designed, the resulting TDMA scheme guarantees the delivery of packets for each traffic relation at a rate of up to one packet per frame duration regardless of the number of the packet transmissions (hops) necessary from source to destination, and thus it is particularly suitable for periodic traffic.While similar traffic maximization problems have been studied quite extensively for the case of unicast traffic, its multicast generalization (where each packet should be delivered from the source node to possibly multiple destination nodes) has not been elaborated so far. In this paper we present such a (non-trivial) generalization, namely a mathematical programming model based on the extension of the compatible set concept where the signal-to-noise and interference (SINR) ratio is guaranteed above a threshold at multiple receivers. We first propose an algorithm for solving the problem that generates compatible sets and schedules the frame by splitting the (predefined) multicast routing trees into one-hop transmissions. The high computational efficiency of the algorithm is proven through numerical results on large networks. Next, we enrich the model by adding multicast tree optimization, illustrating its efficiency numerically as well. Finally, we present possible extensions that consider packets of different lengths (requiring multiple slots for transmission), multiple modulation and coding schemes (MCS) requiring different SINR thresholds at the receivers, and packet delay minimization.

Distributed Cooperative Multicell Beamforming Based on a Viewpoint of Layered Channel

In this paper, a distributed cooperative multicell beamforming algorithm is proposed, and a detail analysis and solving method for instantaneous and statistical channel state information (CSI) are presented. Firstly, an improved distributed iterative beamforming algorithm is proposed for the multiple-input single-output interference channel (MISO IC) scenario which chooses virtual signal-to-interference-and-noise (SINR) as decision criterion to initialize and then iteratively solves the constrained optimization problem of maximizing the virtual SINR for a given level of generated interference to other users. Then, the algorithm is generalized to the multicell date sharing scenario with a heuristics power allocation scheme based on a viewpoint of the layered channel. Finally, the performance is illustrated through numerical simulations.

Near Optimum Power Control and Precoding under Fairness Constraints in Network MIMO Systems

We consider the problem of setting the uplink signal-to-noise-and-interference (SINR) target and allocating transmit powers for mobile stations in multicell spatial multiplexing wireless systems. Our aim is twofold: to evaluate the potential of such mechanisms in network multiple input multiple output (MIMO) systems, and to develop scalable numerical schemes that allow real-time near-optimal resource allocation across multiple sites. We formulate two versions of the SINR target and power allocation problem: one for maximizing the sum rate subject to power constraints, and one for minimizing the total power needed to meet a sum-rate target. To evaluate the potential of our approach, we perform a semianalytical study inMathematicausing the augmented Lagrangian penalty function method. We find that the gain of the joint optimum SINR setting and power allocation may be significant depending on the degree of fairness that we impose. We develop a numerical technique, based on successive convexification, for real-time optimization of SINR targets and transmit powers. We benchmark our procedure against the globally optimal solution and demonstrate consistently strong performance in realistic network MIMO scenarios. Finally, we study the impact of near optimal precoding in a multicell MIMO environment and find that precoding helps to reduce the sum transmit power while meeting a capacity target.

Optimum Practical Design of Distributed and Asynchronous Power Control for Wireless Networks with Shared Bands

The present paper proposes two novel and practical schemes for distributed and asynchronous power control in wireless ad hoc networks, in which users dynamically share several frequency bands as in “cognitive radio” networks. These schemes iteratively adjust transmit powers of individual network transmitters with respect to mutually caused interference in the shared bands. Their most attractive feature is that they find network-wide acceptable trade-offs to diverse signal-to-noise and interference (SINR) requirements and efficiently use techniques of stochastic approximation and time-averaging to guarantee a robust performance in random channels. Advantageously, both proposed algorithms do not assume any particular modulation, coding, QoS measure definition or network architecture, which assures their high applicability in the industry and research. Moreover, the broad definition and non-linear nature of these schemes mathematically generalize and thus encompass as a special case many widely deployed power control schemes such as e.g. those for achieving fixed SINR targets or using game-theoretic utility maximization. Simulations are provided to illustrate our approach and its better performance compared to standard algorithms.

The feasibility of matchings in a wireless network

The problem of determining what links can be simultaneously activated in a wireless network such that a signal-to-interference-and-noise (SINR) constraint is satisfied at all receivers is considered. The term "feasible matching" is introduced to describe a set of (transmitter, receiver) pairs for which there exists some set of transmit powers which can simultaneously meet the SINR requirements at the receivers. Given disjoint equally sized sets of transmitters and receivers, it is shown that when the SINR requirement at the receivers is greater than 1, no more than one feasible matching between the transmitters and the receivers exists. Sufficient conditions are provided under which certain broad classes of matchings in a network are guaranteed to be feasible; for example all matchings involving k or fewer links. The application of these results to ad hoc wireless networks and to scheduling is discussed.

Orthogonal Time–Frequency Signaling Over Doubly Dispersive Channels

This paper develops a general framework for communication over doubly dispersive fading channels via an orthogonal short-time Fourier (STF) basis. The STF basis is generated from a prototype pulse via time-frequency shifts. In general, the orthogonality between basis functions is destroyed at the receiver due to channel dispersion. The starting point of this work is a pulse scale adaptation rule first proposed by Kozek to minimize the interference between the basis functions. We show that the average signal-to-interference-and-noise (SINR) ratio associated with different basis functions is identical and is maximized by the scale adaptation rule. The results in this paper highlight the critical impact of the channel spread factor, the product of multipath and Doppler spreads, on system performance. Smaller spread factors result in lesser interference such that a scale-adapted STF basis serves as an approximate eigenbasis for the channel. A highly effective iterative interference cancellation technique is proposed for mitigating the residual interference for larger spread factors. The approximate eigendecomposition leads to an intuitively appealing block-fading interpretation of the channel in terms of time-frequency coherence subspaces: the channel is highly correlated within each coherence subspace whereas it is approximately independent across different subspaces. The block-fading model also yields an approximate expression for the coherent channel capacity in terms of parallel flat-fading channels. The deviation of the capacity of doubly dispersive channels from that of flat-fading channels is quantified by studying the moments of the channel eigenvalue distribution. In particular, the difference between the moments of doubly dispersive and flat-fading channels is proportional to channel spread factor. The results in this paper indicate that the proposed STF signaling framework is applicable for spread factors as large as 0.01.