In 5G mobile communication system design and standard specification, a system-level simulator is an indispensable element of research & development (R&D). Due to various usage scenarios, 5G systems require the development of different simulators that deal with individual evaluation scenarios and environments. To minimize the time and effort required for the implementation, we have designed and implemented 5G K-SimSys, which is a system-level simulator with modular & flexible structure, facilitating its reuse thorough open-source code sharing. This paper describes the 5G ultra-reliable low latency communication (URLLC) specification in 3GPP and its system-level evaluation to illustrate that 5G K-SimSys can provide reconfiguration between various usage scenarios.

Massive MIMO is a key feature for improving spectral efficiency in 5G system. Since massive MIMO has been standardized in 3GPP Re1-13 (LTE-Advanced Pro), a next generation of massive MIMO standard is now available in Rel-15, a.k.a New Radio (NR), for 5G, which is aiming at further improving the average spectral efficiency with more antenna elements over the higher frequency band. In particular, beam-based air interface for above 6GHz band involves with various antenna configurations and feedback schemes, requiring a more complex testbed for system-level performance evaluation. In this paper, we examine the multi-antenna technologies in 3GPP NR specification, so as to develop its system-level model in 5G K-SimSys, which has been designed and implemented to provide an open platform and testbed for evaluating the system-level performance for 5G system. Its actual implementation is detailed along with the overall platform architecture for modular and flexible design. Then, its actual performance is demonstrated for one of the precoding matrices in the NR specification as an example.

Unlike the general concept of eliminating or avoiding inter-user interference in the downlink multi-user multiple-input single-output (MISO) system, the data-aided precoding scheme attempts to exploit the constructive interference at symbol level. Positive interference can be constructed to enhance the received signal gain by predicting the phase and magnitude of the inter-user interference. In this paper, we formulate a constructive interference optimization problem that minimizes a sum of minimum mean square error (MMSE) for all users, while ensuring the minimum required constructive interference gain with a fixed total power constraint. As opposed to the existing scheme, such as constructive zero-forcing precoding or minimum power precoding subject to strict phase conservation for phase-shift keying (PSK), our proposed scheme exploits a full range of relaxation for the constructive interference region, while ensuring the link performance by minimizing the sum of mean-square error (MSE) for all users. In fact, the relaxed requirements lead to more degrees of freedom for improving the cumulative constructive interference gain (CCIG) under the varying channel conditions. Furthermore, our MMSE-based optimization approach allows for a semi-closed-form optimal solution to the data-aided precoding scheme, providing a more CCIG without incurring unacceptable complexity than other state-of-the-art schemes.

The compressive sensing-based random access may get impacted largely by other cell interference (OCI), which may shatter the sparsity of the received signal model unless the signature space assignment among interfering cells is carefully handled. In this paper, we investigate the performance of multi-sequence spreading-based random access (MSRA) scheme under multi-cell environment. In particular, a grant-free random access scenario is considered to indicate its particular attributes that fundamentally affect the cellular performance. We also give the performance of MSRA in comparison with sparse code multiple access (SCMA). We show that if a proper signature assignment is undertaken, the OCI in MSRA and other CS-based schemes can be modeled as a dispersed noise which does not critically undermine the underlying sparsity.

For the frequency division duplexing-based large-scale multiple-input multiple-output (MIMO) systems, we consider a multi-user MIMO (MU-MIMO) non-orthogonal multiple access (NOMA) scheme, referred to as beam division-NOMA (BD-NOMA), which is featured by a long-term feedback-based user grouping and clustering, along with a short-term feedback-based BD-NOMA scheduling. The performance of BD-NOMA is not warranted in practice because near users are severely interfered by strong signals for the far users of other beams, and furthermore, the long-term feedback-based user grouping and clustering might result in short-term inter-beam interference. We consider the short-term feedback-based joint optimization problem of user selection and power allocation for NOMA in each beam and system-wide power allocation for MU-MIMO, dealing with both intra-beam and inter-beam interference at the same time. We formulate a joint optimization problem for a large-scale MIMO system with the multiple channel quality indicators-based short-term feedback. In our analysis, we reformulate the original problem into an equivalent one that can be solved iteratively with the weighted minimum mean square error-based algorithm. Then, the performance analysis is presented to conclude that the proposed optimization is essential for enabling BD-NOMA to outperform beam division multiple access, especially when inter-beam interference becomes critical.

As compared to asynchronous contention-based random access, synchronous & distributed link scheduling for OFDM system turns to be a viable solution to improve the system throughput for device-to-device (D2D) communication. In particular, a spatial spectral efficiency can be improved by scheduling the concurrent D2D links as many as the individual signal-to-interference ratio (SIR) requirement is satisfied. In this paper, we propose an adaptive yielding mechanism that can further improve the spatial spectral efficiency by allowing for more concurrent D2D links whenever more interference can be accepted, e.g., when the instantaneous bandwidth efficiency requirement is less than the current link capacity. Even if the system throughput varies with the link density, it has been shown that the average system throughput can be significantly improved by the proposed yielding mechanism.

With progressive image or scalable video encoders, as more bits are received, the source can be reconstructed with progressively better quality. These progressive codes have gradual differences of importance in their bitstreams, which necessitates multiple levels of unequal error protection (UEP). One practical method of achieving UEP is based on a constellation of nonuniformly spaced signal points, or hierarchical constellations. However, hierarchical modulation can achieve only a limited number of UEP levels for a given constellation size. Though hierarchical modulation has been intensively studied for digital broadcasting or multimedia transmission, most work has considered only two layered source coding, and methods of achieving a large number of UEP levels for progressive transmission have rarely been studied. In this paper, we propose a multilevel UEP system using multiplexed hierarchical quadrature amplitude modulation (QAM). We show that multiple levels of UEP are achieved by the proposed multiplexing method. When the BER is dominated by the minimum Euclidian distance, we derive an optimal multiplexing approach which minimizes both the average and peak powers. We next propose an asymmetric hierarchical QAM which reduces the peak-to-average power ratio (PAPR) of the proposed UEP system without any performance loss. Numerical results show that the performance of progressive transmission over Rayleigh fading channels is significantly enhanced by the proposed methods.

This paper proposes a contention-based fair coexistence mechanism among heterogeneous networks that have different transmission power and/or coverage. First, we show that the existing carrier sensing multiple access (CSMA) mechanism, that is a prevailing contention-based protocol, results in significant unfairness in channel access when heterogeneous networks coexist; a system with lower transmission power hardly occupies the shared channel due to interference from a system with higher transmission power. We analyze the causes of unfairness in terms of (i) the asymmetry of carrier sensing and (ii) the blindness of binary exponential backoff mechanism and the link adaptation mechanism, and we derive an analytical model of per-system throughput to investigate the effects of these causes. To resolve this problem, we propose a fair coexistence CSMA protocol consisting of access etiquette and interference-aware backoff. The former adaptively controls the contention window size so that the high-power system allows transmission opportunities to the low-power system in a fair and efficient manner. The latter differentiates between the response to transmission failure caused by collision and the response to failure caused by interference. The simulation results confirm that the proposed scheme effectively mitigates the unfairness of channel sharing while attaining high spectral efficiency.

We propose superposition multiple-input multiple-output (MIMO) coding for the transmission of unequally important sources in a point-to-multipoint system. First, a tradeoff between Alamouti code and spatial multiplexing (V-BLAST) is analyzed in terms of the average bit error rate (BER), where the maximum data rates of both MIMO schemes are set to be equal. The results show that for a given target bit error rate, Alamouti code is preferable for a low data rate, and spatial multiplexing is preferable for a high data rate. For layered sources such as scalable video, the more important component typically has lower data rate than does the less important component. Based on these, we construct a superposition MIMO scheme where two different MIMO techniques are hierarchically combined such that important data is Alamouti coded, less important data is spatially multiplexed, and then two unequally important data symbols are superposed.

Average throughput maximization has commonly been used as an alternative to image or video average distortion minimization. However, as the throughput-distortion curve is non-linear, throughput maximization can be very different from distortion minimization if the variance of the throughput is large. Under high channel quality variability, the variance of the throughput will be high. Multiple description coding with unequal error protection is a promising technique for the transmission of progressive images when there exists a high variability of the channel conditions. In this paper, we consider both the variance and the average of the throughput when deciding the constellation size for adaptive modulation in an OFDM system used for transmitting progressively-coded images with multiple description coding. Simulation results show that in an adaptive modulated image transmission system, taking into account both moments of the throughput achieves better performance than a system considering average throughput alone.

Progressive image and scalable video have gradual differences of importance in their bitstreams, which can benefit from multiple levels of unequal error protection (UEP). Though hierarchical modulation has been intensively studied as an UEP approach for digital broadcasting and multimedia transmission, methods of achieving a large number of UEP levels have rarely been studied. In this paper, we propose a multilevel UEP system using multiplexed hierarchical quadrature amplitude modulation (QAM) for progressive transmission over mobile radio channels. We suggest a specific way of multiplexing, and prove that multiple levels of UEP are achieved by the suggested method. When the BER is dominated by the minimum Euclidian distance, we derive an optimal multiplexing approach which minimizes both the average and peak powers. An asymmetric hierarchical QAM which reduces the peak-to-average power ratio (PAPR) without performance loss is also proposed. Numerical results show that the performance of progressive transmission over Rayleigh fading channels is significantly enhanced by the proposed UEP systems.

This paper addresses the use of adaptive modulation in progressive image transmission with multiple description coding in conjunction with an Orthogonal Frequency Division Multiplexing (OFDM) system. Specifically, two adaptive systems are considered: variable rate with fixed power, and variable rate with variable power. An algorithm is proposed to allocate power and constellation size at each subchannel by maximizing the throughput. Simulation results confirm that cross-layer optimization with adaptive modulation enhances system performance.

When decision-directed channel estimation is used for QAM-OFDM systems, the optimal shape of the two-dimensional filter depends on the amplitudes of the modulated symbols as well as the channel characteristics such as delay spread. Doppler frequency, and signal-to-noise ratio. While most conventional channel estimation methods did not consider the amplitudes of the modulated symbols because of the large computational complexity, we propose a simple channel estimation method for multi-level-amplitude-modulated systems. The proposed method can effectively reduce the noise variance of the estimates with small-sized filtering and there is a possibility of reducing the implementation cost and producing better results by avoiding unnecessarily large biased term.

In this paper we present a new class of loop optimizing transformations called valid transformations, which are suitable for fine-grain parallelization applications such as high-level synthesis of VLSI designs or compilers for super-scalar or VLIW machines. This class of transformations are different from existing ones in that valid transformations can be illegal. Nevertheless, if a transformation is valid, the transformed loop has a feasible pipeline schedule. We present an example valid transformation called loop expansion which can help produce cost-performance efficient designs and explore a larger design space for a satisfactory design. Several examples are used to demonstrate the efficacy of the proposed technique.

In this paper, we present a global scheduling technique for synthesis applications. The algorithm accepts a specification containing conditional branches and while-loop constructs and schedules it for a given set of resources. The algorithm performs several types of code motions across different basic blocks and trades off cost with performance. Several real-life examples taken from Numerical Recipes in C are used to demonstrate the efficacy of the approach. The results indicate that code-motions are very important for achieving significant speed-ups for synthesis applications.>

In this paper, we present a resource-constrained global scheduling technique for synthesis applications. The algorithm accepts speci cations containing conditional branches and while loops and schedules them for a given set of resources. The algorithm performs several types of code motions across di erent basic blocks and trades o cost with performance. Several real-life examples are used to demonstrate the e cacy of the approach. 1

Presents a new scheduling heuristic RECALS II for high-level synthesis applications. RECALS II accepts a directed acyclic graph and a set of resources and schedules the graph while minimizing the number of clock cycles required to execute it. Experiments show that schedules produced by RECALS II are close to the optimal solutions.>

In this paper we present a new class of loop optimizing transformations called valid transformations. This class of transformations are different from existing ones in that valid transformations can be illegal and can result in incorrect non-pipelined designs. Nevertheless, valid transformations have feasible pipeline schedules which is important for scheduling loops. We present an example valid transformation called loop expansion which can help explore a larger design space and helps in producing cost-performance efficient designs. Several examples are used to demonstrate the efficacy of the proposed transformations.

In this paper we present estimation techniques for loop transformations. These estimation techniques can be used for design space exploration. They can be used to quickly evaluate the cost and performance characteristics of the transformations, thus helping the designer make the decision of applying the transformation or not. The estimates are verified for several transformations and are very close to the actual results.>

A given behavioral specification can be implemented on a large number of register-transfer level designs. Instead of producing several designs and selecting the best one, synthesis systems may use estimation to reduce the design space. In this paper, we present a new technique for computing a lower-bound completion time for non-pipelined resource-constrained scheduling problem. Given a data flow graph, a set of resources, resource delays and a clock cycle, we derive a lower-bound on the completion time of a schedule. Our technique can handle chaining, multi-cycle operations and pipelined modules. The technique is very fast and experimental results show that it is also very tight.>

In this paper we present an optimal and a heuristic approach to solve the binding problem which occurs in high-level synthesis of digital systems. The optimal approach is based on an integer linear programming formulation. Given that such an approach is not practical for large problems, we then derive a heuristic from the ILP formulation which produces very good solutions in order of seconds. The heuristic is based on a network flow model and also considers floorplanning during the design process to minimize the interconnection area.>

A technique for computing a lower bound for nonpipelined resource-constrained scheduling performance is presented. Given a data-flow graph, a set of resources, resource delays, and clock cycle, a lower bound on the performance of a schedule is derived. The technique is fast (typical runtime of 50 ms), and the experimental lower-bounds are within two time steps of the actual schedules produced by a scheduling heuristic. The technique is also constructive and can be incorporated in a branch-and-bound method for solving the scheduling problem. The lower bound can be used to reduce a design search space. The method is applicable to lower-bound estimation in high-level synthesis.>