In this paper, we used the data set of domain names Global Top 1M provided by Alexa to analyze the effectiveness of Fallback in ECN. For the same test server, we first negotiate a connection with Not-ECN-Capable, and then negotiate a connection with ECN-Capable, if the sender does not receive the response to ECN-Capable negotiation from the receiver by the end of retransmission timeout, it will enter the Fallback state, and switch to negotiating a connection with Not-ECN-Capable. By extracting the header fields of the TCP/IP packets, we confirmed that in most regions, connectivity will be slightly improved after Fallback is enabled and Fallback has a positive effect on the total time of the whole access process. Meanwhile, we provided the updated information about the characteristics related to ECN with Fallback in different regions by considering the geographical region distribution of all targeted servers.

TCP Friendly Rate Control (TFRC) has been widely used in the Internet multimedia streaming applications. However, performance of traditional TFRC algorithm degrades significantly when deployed over wireless networks. Although numerous TFRC variants have been proposed to improve the performance of TFRC over wireless networks, designing a TFRC algorithm with graceful performance both in throughput and fairness still remains a great challenge. In this paper, a novel TFRC algorithm, named TFRC-FIT, is proposed to improve the performance of TFRC over wireless environments. In the proposed approach, the behavior of multiple TFRC flows is simulated in single connection, while the number of simulated flows is adjusted by the network queuing delay. Through this mechanism, TFRC-FIT can fully utilize the capacity of wireless networks, while maintaining good fairness and TCP friendliness. Both theoretical analysis and extensive experiments over hardware network emulator, Planetlab test bed as well as commercial 3G wireless networks are carried out to characterize and validate the performance of our proposed approach.

Permutation network plays an important role in the reconfigurable QC-LDPC decoder for most modern wireless communication systems with multiple code rates and various code lengths. This paper presents the generic permutation network (GPN) for the reconfigurable QC-LDPC decoder. Compared with conventional permutation networks, this proposal could break through the input number restriction, such as power of 2 and other limited number, and optimize the network for any application in demand. Moreover, the proposed scheme could greatly reduce the latency because of less stages and efficient control signal generating algorithm. In addition, the proposed network processes the nature of high parallelism which could enable several groups of data to be cyclically shifted simultaneously. The synthesis results using the 90 nm technology demonstrate that this architecture can be implemented with the gate count of 18.3k for WiMAX standard at the frequency of 600 MHz and 10.9k for WiFi standard at the frequency of 800 MHz.

Structured quasi-cyclic low-density parity-check (QC-LDPC) codes have been adopted in many wireless communication standards, such as WiMAX, Wi-Fi and WPAN. To completely support the variable code rate (multi-rate) and variable code length (multi-length) implementation for universal applications, the partial-parallel layered LDPC decoder architecture is straightforward and widely used in the decoder design. In this paper, we propose a high parallel LDPC decoder architecture for WiMAX system with dedicated ASIC design. Different from the block by block decoding schedule in most partial-parallel layered architectures, all the messages within each layer are updated simultaneously in the proposed fully-parallel layered decoder architecture. Meanwhile, the message updating is separated into bit-serial style to reduce hardware complexity. A 6-bit implementation is adopted in the decoder chip, since simulations demonstrate that 6-bit quantization is the best trade-off between performance and complexity. Moreover, the two-layer concurrent processing technique is proposed to further increase the parallelism for low code rates. Implementation results show that the decoder chip saves 22.2% storage bits and only takes 2448 clock cycles per iteration for all the code rates defined in WiMAX standard. It occupies 3.36 mm2 in SMIC 65 nm CMOS process, and realizes 1056 Mbps throughput at 1.2 V, 110 MHz and 10 iterations with 115 mW power occupation, which infers a power efficiency of 10.9 pJ/bit/iteration. The power efficiency is improved 63.6% in normalized comparison with the state-of-art WiMAX LDPC decoder.

In this paper, we propose an adaptive Go-Back-N (GBN) ARQ protocol over two parallel channels with slow state transition. This proposed protocol sophisticatedly determines the order of priority of the channel usage for sending packets, by using the channel-state feedback information. We exactly analyze the throughput efficiency of the protocol and obtain its closed-form expression under the assumption that the time-varying channel is modeled by a two-state Markov chain, which is characterized by packet error rate and the decay factor. The analytical results and numerical examples show that, for a given round-trip time, the throughput efficiency depends on both the average packet-error rate and the decay factor. Furthermore, it is shown that the throughput efficiency of the proposed protocol is superior to that of the non-adaptive Go-Back-N protocol using the two channels in a fixed order in the case of slow state transition (i.e. the decay factor is positively large).

In high-speed packet networks, protocol processing overhead time becomes remarkable in determining the system performance. In this paper, we present a new Selective-Repeat ARQ scheme (called Block SR-ARQ sheme), in which a packet is transmitted or retransmitted in the same way as basic SR-ARQ scheme, but a single acknowledgement packet is used to acknowledge a block of packets. The maximum number of packets acknowledged by an acknowledgement packet is defined as block size. We analyze the system throughput and the average packet delay over the system, and the accuracy of approximately analyzed results is validated by simulation. Furthermore, we show that there exists an optimal block size which obtains both the maximum throughput and the minimum average packet delay.

In spectrum-sharing systems where the secondary user (SU) opportunistically accesses the primary user (PU)'s licensed channel, the SU should satisfy both the transmit power constraint of the SU transmitter and the received power constraint at the PU receiver. This letter studies the ergodic capacity of spectrum-sharing systems in fading channels. The ergodic capacity expression along with the optimal power allocation scheme is derived considering both the average transmit and received power constraints. The capacity function in terms of the two power constraints is found to be divided into transmit power limited region, received power limited region and dual limited region. Numerical results in Rayleigh fading channels are presented to verify our analysis.

In this paper, we introduce an LDPC decoder design for decoding a length-672 multi-rate code adopted in IEEE 802.15.3c standard. The proposed decoder features high performances in both data rate and power efficiency. A macro-layer level fully parallel layered decoding architecture is proposed to support the throughput requirement in the standard. For the proposed decoder, it takes only 4 clock cycles to process one decoding iteration. While parallelism increases, the chip routing congestion problem becomes more severe because a more complicated interconnection network is needed for message passing during the decoding process. This problem is nicely solved by our proposed efficient message permutation scheme utilizing exploited parity check matrix features. The proposed message permutation network features high compatibility and zero-logic-gate VLSI implementation, which contribute to the remarkable improvements in both area utilization ratio and total gate count. Meanwhile, frame-level pipeline decoding is applied in the design to shorten the critical path. To verify the above techniques, the proposed decoder is implemented on a chip fabricated using Fujitsu 65 nm 1P12L LVT CMOS process. The chip occupies a core area of 1.30 mm2 with area utilization ratio 86.3%. According to the measurement results, working at 1.2 V, 400 MHz and 10 iterations the proposed decoder delivers a 6.72 Gb/s data throughput and dissipates a power of 537.6 mW, resulting in an energy efficiency 8.0 pJ/bit/iteration. Moreover, a decoder of the same architecture but with no pipeline stage for low-profile application is also implemented and evaluated at post-layout level.

Given the limited channel capacity in wireless LANs, it is important to achieve high throughput and good fairness through medium access control (MAC) schemes. Although many schemes have been proposed to enhance throughput or fairness of the original IEEE 802.11 standard, they either fail to consider both throughput and fairness, or to do so with complicated algorithms. In this paper, we propose a new MAC scheme that dynamically optimizes each active node's backoff process. The key idea is to enable each node to adjust its Contention Window (CW) to approach the optimal one that will maximize the throughput. Meanwhile, when the network enters into steady state in saturated case, i.e., under heavy traffic load, all the nodes will maintain approximately identical CWs, which guarantees fair share of the channel among all nodes. A distinguishing feature of this scheme is the use of an index called average channel idle interval for optimizing the backoff process without estimating the number of active nodes in networks. We show through theoretical analysis that the average channel ideal interval can represent current network traffic load and indicate the optimal CW. Moreover, since it can be obtained through direct measurement, our scheme eliminates the need for complicated estimation of the number of active nodes as required in previous schemes, which makes our schemes simpler and more reliable when network traffic changes frequently. Through simulation comparison with previous schemes, we show that our scheme can greatly improve the throughput no matter the network is in saturated or non-saturated case, while maintaining good fairness.

In orthogonal frequency-division multiplex access (OFDMA) uplink, the carrier-frequency offsets (CFOs) between the multiple transmitters and the receiver introduce inter-carrier interference (ICI) and severely degrade the performance. In this paper, based on the perfect estimation of each user's CFO, we propose two low-complexity iterative algorithms to cancel ICI due to CFOs, which are denoted as the basic algorithm and the improved algorithm with decision-feedback equalization (DFE), respectively. For the basic one, two theorems are proposed that yield a sufficient condition for the convergence of iterations. Moreover, the interference-power-evolution (IPE) charts are proposed to evaluate the convergence behavior of this interference cancellation algorithm. Motivated by the IPE chart, the procedure of DFE is introduced into the iterations, which is the basic idea of the improved algorithm. For this improved algorithm, the error-propagation effect are analyzed and suppressed by an efficient stopping criterion. From IPE charts and simulation results, it can be easily observed that the basic algorithm has the same capability of ICI cancellation as the linear optimal minimum mean square error (MMSE) method, but offers lower complexity, while the improved algorithm with DFE outperforms the MMSE method in terms of the bit-error rate (BER) performance.

This paper addresses the problem of joint transceiver design for Tomlinson-Harashima Precoding (THP) in the multiuser multiple-input-multiple-output (MIMO) downlink under both perfect and imperfect channel state information at the transmitter (CSIT). For the case of perfect CSIT, we differ from the previous work by performing stream-wise (both inter-user and intra-user) interference pre-cancelation at the transmitter. A minimum total mean square error (MT-MSE) criterion is used to formulate our optimization problem. By some convex analysis of the problem, we obtain the necessary conditions for the optimal solution. An iterative algorithm is proposed to handle this problem and its convergence is proved. Then we extend our designed algorithm to the robust version by minimizing the conditional expectation of the T-MSE under imperfect CSIT. Simulation results are given to verify the efficacy of our proposed schemes and to show their superiorities over existing MMSE-based THP schemes.

ECN, as a decisive approach for TCP congestion control, has been proposed for many years. However, its deployment on the Internet is much slower than expected. In this paper, we investigate the state of the deployment of ECN (Explicit Congestion Notification) on the Internet from a different viewpoint. We use the data set of web domains published by Alexa as the hosts to be tested. We negotiate an ECN-Capable and a Not ECN-Capable connections with each host and collect all packets belonging to the connections. By analyzing the header fields of the TCP/IP packets, we dig out the deployment rate, connectivity, variation of round-trip time and time to live between the Not ECN-Capable and ECN-Capable connections as well as the rate of IPv6-Capable web servers. Especially, it is clear that the connectivity is different from the domains (regions on the Internet). We hope that the findings acquired from this study would incentivize ISPs and administrators to enable ECN in their network systems.

In this letter, we propose a partial minimum mean-squared error (MMSE) with successive interference cancellation (PMMSESIC) method in frequency domain to mitigate ICI caused by channel variation. Each detection, the proposed method detects the symbol with the largest received signal-to-interference-plus-noise ratio (SINR) among all the undetected symbols, using an MMSE detector that considers only the interference of several neithborhood subcarriers. Analysis and simulations show that it outperforms the MMSE method at relatively high Eb/N0 and its performance is close to the MMSE with successive detection (MMSESD) method in relatively low Doppler frequency region.

In this paper a multi-channel MAC protocol with dynamic channel allocation (MMAC-DCA) in CDMA Ad Hoc networks is proposed. Under MMAC-DCA, the service sub-channels are dynamically allocated by the RTS/CTS dialogue on the common sub-channel, only when a node has a packet to transmit. In addition, a Markov mode is presented to analyze the performance of MMAC-DCA.

Convolutional Neural Networks (CNNs) and Transformers have achieved remarkable performance in detection and classification tasks. Nevertheless, their feature extraction cannot consider both local and global information, so the detection and classification performance can be further improved. In addition, more and more deep learning networks are designed as more and more complex, and the amount of computation and storage space required is also significantly increased. This paper proposes a combination of CNN and transformer, and designs a local feature enhancement module and global context modeling module to enhance the cascade network. While the local feature enhancement module increases the range of feature extraction, the global context modeling is used to capture the feature maps' global information. To decrease the model complexity, a shared sublayer is designed to realize the sharing of weight parameters between the adjacent convolutional layers or cross convolutional layers, thereby reducing the number of convolutional weight parameters. Moreover, to effectively improve the detection performance of neural networks without increasing network parameters, the optimal transport assignment approach is proposed to resolve the problem of label assignment. The classification loss and regression loss are the summations of the cost between the demander and supplier. The experiment results demonstrate that the proposed Combination of CNN and Transformer with Shared Sublayer (CCTSS) performs better than the state-of-the-art methods in various datasets and applications.

We consider a communication system in which a transmitter is connected to a receiver through parallel channels, and the Go-Back-N ARQ scheme is used to handle transmission errors. A packet error on one channel results in retransmission of packets assigned to other channels under the Go-Back-N ARQ scheme. Therefore, the channel-grouping (a grouped-channel is used to transmit the same packet at a time), would affect the throughput performance. We analyze the throughput performance, and give a tree-algorithm to efficiently search for the optimal channel-grouping which makes the throughput to become maximum. Numerical results show that the throughput is largely improved by using the optimal channel-grouping.

Recently, the throughput performances of ARQ's have been analyzed over a Markov error channel. It has been shown that given a round-trip-delay, the throughput of the Stop-and-Wait ARQ is dependent only on the overall average packet-error probability. In this paper, we exactly analyze the Stop-and-Wait ARQ scheme under the condition that the channel is slotted and packet errors occur according to a two-state Markov chain which is characterized by the decay factor. The distribution of packet delay time and the channel usage factor are obtained. From the analytical results and numerical examples, it is shown that for a given round-trip-delay, the average packet delay time and the channel utilization factor depend on both the overall average packet-error probability and the decay factor characterizing the two-state Markov chain. Furthermore, the decay factor gives different influence on the average delay time and the channel usage factor depending on whether the round-trip-delay is even slots or not.

This paper studies the performance of a dialogue communication system which consists of two stations over a half-duplex line. When a station seizes the right to send its packets, it can consecutively transmits k packets. We analyze the transmission time of a message and the throughput performances of Stop-and-Wait, Go-back-N and Selective-Repeat protocols for the half-duplex line transmission system. Based on the analytical and numerical results, we clarify the influences of the switching and the thinking times, which exist in half-duplex line system, on the throughput performance, and give the optimal k which makes the throughput to become maximum. It is observed that the throughput performances are greatly influenced not only by the switching and thinking times but also by the average message length.

Since the structured quasi-cyclic low-density parity-check (QC-LDPC) codes for most modern wireless communication systems include multiple code rates, various block lengths, and the corresponding different sizes of submatrices in parity check matrix (PCM), the reconfigurable LDPC decoder is desirable and the permutation network is needed to accommodate any input number (IN) and shift number (SN) for cyclic shift. In this paper, we propose a novel permutation network architecture for the reconfigurable QC-LDPC decoders based on Banyan network. We prove that Banyan network has the nonblocking property for cyclic shift when the IN is power of 2, and give the control signal generating algorithm. Through introducing the bypass network, we put forward the nonblocking scheme for any IN and SN. In addition, we present the hardware design of the control signal generator, which can greatly reduce the hardware complexity and latency. The synthesis results using the TSMC 0.18 µm library demonstrate that the proposed permutation network can be implemented with the area of 0.546 mm2 and the frequency of 292 MHz.

Multi-agent based simulation has been widely used in behavior finance, and several single-processed simulation platforms with Agent-Based Modeling (ABM) have been proposed. However, traditional simulations of stock markets on single processed computers are limited by the computing capability since financial researchers need larger and larger number of agents and more and more rounds to evolve agents' intelligence and get more efficient data. This paper introduces a distributed multi-agent simulation platform, named PSSPAM, for stock market simulation focusing on large scale of parallel agents, communication system and simulation scheduling. A logical architecture for distributed artificial stock market simulation is proposed, containing four loosely coupled modules: agent module, market module, communication system and user interface. With the customizable trading strategies inside, agents are deployed to multiple computing nodes. Agents exchange messages with each other and with the market based on a customizable network topology through a uniform communication system. With a large number of agent threads, the round scheduling strategy is used during the simulation, and a worker pool is applied in the market module. Financial researchers can design their own financial models and run the simulation through the user interface, without caring about the complexity of parallelization and related problems. Two groups of experiments are conducted, one with internal communication between agents and the other without communication between agents, to verify PSSPAM to be compatible with the data from Euronext-NYSE. And the platform shows fair scalability and performance under different parallelism configurations.