Turbo codes and LDPC (Low-Density Parity-Check) codes are two of the most powerful error correction codes that can approach Shannon limit in many communication systems. But there are little architecture presented to support both LDPC and Turbo codes, especially by the means of ASIC. This paper have implemented a common architecture that can decode LDPC and Turbo codes, and it is capable of supporting the WiMAX, WiFi, 3GPP-LTE standard on the same hardware. In this paper, we will carefully describe how to share memory and logic devices in different operation mode. The chip is design in a 130 nm CMOS technology, and the maximum clock frequency can reach up to 160 MHz. The maximum throughput is about 104 Mbps@5.5 iteration for Turbo codes and 136 Mbps@10iteration for LDPC codes. Comparing to other existing structure, the design speed, area have significant advantage.

With simultaneous multi-user transmissions, spatial division multiple access (SDMA) provides substantial throughput gain over the single user transmission. However, its implementation in WLANs with contention-based IEEE 802.11 MAC remains challenging. Problems such as coordinating and synchronizing the multiple users need to be solved in a distributed way. In this paper, we propose a distributed MAC protocol for WLANs with SDMA support. A dual-mode CTS responding mechanism is designed to accomplish the channel estimation and user synchronization required for SDMA. We analytically study the throughput performance of the proposed MAC, and dynamic parameter adjustment is designed to enhance the protocol efficiency. In addition, the proposed MAC protocol does not rely on specific physical layer realizations, and can work on legacy IEEE 802.11 equipment with slight software updates. Simulation results show that the proposed MAC outperforms IEEE 802.11 significantly, and that the dynamic parameter adjustment can effectively track the load variation in the network.

In this letter, we propose a novel precoding scheme for base station (BS) cooperation in downlink cellular networks that allow overlapped clusters. The proposed precoding scheme is designed to mitigate the overlapping-BS interference by maximizing the so-called clustered virtual signal-to-interference-plus-noise ratio (CVSINR). Simulations show that with the proposed scheme, overlapped clustering provides substantial throughput gain over the traditional non-overlapped clustering methods, and user fairness is also improved.

In this work, we consider a remote estimation system where a remote controller estimates the status of heterogeneous sensing devices with the information delivered over wireless channels. Status of heterogeneous devices changes at different speeds. With limited wireless resources, estimating as accurately as possible requires careful design of status update schemes. Status update schemes can be divided into two classes: centralized and decentralized. In centralized schemes, a central scheduler coordinates devices to avoid potential collisions. However, in decentralized schemes where each device updates on its own, update decisions can be made by using the current status which is unavailable in centralized schemes. The relation between these two schemes under the heterogeneous devices case is unclear, and thus we study these two schemes in terms of the mean square error (MSE) of the estimation. For centralized schemes, since the scheduler does not have the current status of each device, we study policies where the scheduling decisions are based on age of information (AoI), which measures the staleness of the status information held in the controller. The optimal scheduling policy is provided, along with the corresponding MSE. For decentralized schemes, we consider deviation-based policies with which only devices with estimation deviations larger than prescribed thresholds may update, and the others stay idle. We derive an approximation of the minimum MSE under the deviation-based policies and show that it is e/3 of the minimum MSE under the AoI-based policies. Simulation results further show that the actual minimum MSEs of these two policies are even closer than that shown by the approximation, which indicates that the cost of collision in the deviation-based policy cancels out the gain from exploiting status deviations.

Base station (BS) cooperation is a promising technique to suppress co-channel interference for cellular networks. However, practical limitations constrain the scale of cooperation, thus the network is divided into small disjoint BS cooperation groups, namely clusters. A decentralized scheme for BS cluster formation is proposed based on efficient BS negotiations, of which the feedback overhead per user is nearly irrelevant to the network size, and the number of iteration rounds scales very slowly with the network size. Simulations show that our decentralized scheme provides significant sum-rate gain over static clustering and performs almost the same as the existing centralized approach. The proposed scheme is well suited for large-scale cellular networks due to its low overhead and complexity.

A leakage-aware Coordinated Scheduling/Coordinated Beamforming (CS/CB) scheme for heterogeneous networks with layered limited feedback is proposed. In particular, all pico cells cooperatively select an optimal beamforming vector for the macro cell within a CoMP cluster so as to minimizing leakage power from the macro cell. Simulations show that the proposed scheme outperforms the conventional non-CoMP scheme with perfect channel state information at teansmitter (CSIT). Furthermore, the feedback amount and scheduler complexity is decreased greatly.

The energy consumption of the information and communication technology (ICT) industry, which has become a serious problem, is mostly due to the network infrastructure rather than the mobile terminals. In this paper, we focus on reducing the energy consumption of base stations (BSs) by adjusting their working modes (active or sleep). Specifically, the objective is to minimize the energy consumption while satisfying quality of service (QoS, e.g., blocking probability) requirement and, at the same time, avoiding frequent mode switching to reduce signaling and delay overhead. The problem is modeled as a dynamic programming (DP) problem, which is NP-hard in general. Based on cooperation among neighboring BSs, a low-complexity algorithm is proposed to reduce the size of state space as well as that of action space. Simulations demonstrate that, with the proposed algorithm, the active BS pattern well meets the time variation and the non-uniform spatial distribution of system traffic. Moreover, the tradeoff between the energy saving from BS sleeping and the cost of switching is well balanced by the proposed scheme.

The traffic load of cellular networks varies in both time and spatial domains, causing many base stations (BS) to be under-utilized. Assisted by cell zooming, dynamic BS sleep control is considered as an effective way to improve energy efficiency during low traffic hours. Therefore, how densely the BSs should be deployed with cell zooming and BS sleeping is an important issue. In this paper, we explore the energy-optimal cellular network planning problem with dynamic BS sleeping and cell zooming for the cases in which traffic is uniformly distributed in space but time-varying. To guarantee the quality of multi-class services, an approximation method based on Erlang formula is proposed. Extensive simulations under our predefined scenarios show that about half of energy consumption can be saved through dynamic BS sleeping and power control. Surprisingly, the energy-optimal BS density we obtained is larger than the one without considering BS sleeping. In other words, deploying more BSs may help to save energy if dynamic BS sleeping is executed.

Based on Turbo-Decoding Message-Passing (TDMP) and Normalized Min-Sum (NMS) algorithm, an area efficient LDPC decoder that supports both structured and unstructured LDPC codes is proposed in this paper. We introduce a solution to solve the memory access conflict problem caused by TDMP algorithm. We also arrange the main timing schedule carefully to handle the operations of our solution while avoiding much additional hardware consumption. To reduce the memory bits needed, the extrinsic message storing strategy is also optimized. Besides the extrinsic message recover and the accumulate operation are merged together. To verify our architecture, a LDPC decoder that supports both China Multimedia Mobile Broadcasting (CMMB) and Digital Terrestrial/ Television Multimedia Broadcasting (DTMB) standards is developed using SMIC 0.13 µm standard CMOS process. The core area is 4.75 mm2 and the maximum operating clock frequency is 200 MHz. The estimated power consumption is 48.4 mW at 25 MHz for CMMB and 130.9 mW at 50 MHz for DTMB with 5 iterations and 1.2 V supply.