Mingchao Yu

A Study of Pilot-Assisted OFDM Channel Estimation Methods With Improvements for DVB-T2

We provide a comparative study of channel estimation methods for pilot-assisted orthogonal frequency-division multiplexing (OFDM) communication systems in time-varying frequency-selective fading channels. We also propose an improved low-complexity least-squares (LS) estimation method based on the domain-transform process, which estimates time-domain channel impulse response (CIR) using the LS estimate of pilot subchannels. Our method is particularly suited to commercial OFDM systems such as the second generation of digital terrestrial television broadcasting systems (DVB-T2) because it has the following properties: 1) It uses only one OFDM symbol; 2) it does not require knowledge of channel statistics; 3) it works for any pilot pattern; and 4) the size of the estimation matrix for obtaining CIR only depends on the number of pilot subcarriers, but not on the size of OFDM symbol. Because of the first three properties, our method is robust to high Doppler frequency shifts, timing synchronization errors, and pilot patterns in commercial systems. Moreover, through computer simulations, we verify that our method provides competitive bit error rate and channel estimation error performance, compared with some well-known methods, which suffer from either a much higher computational load or less robustness to Doppler shifts or timing errors. For irregular pilot patterns, efficient yet simple regularization methods are suggested to solve the ill-conditioned problem of the estimation matrix. An upper bound on the mean squared error of the estimated CIR is also provided.

From Instantly Decodable to Random Linear Network Coded Broadcast

Our primary goal in this paper is to better understand and extend the achievable tradeoffs between the throughput and decoding delay performance of network coded wireless broadcast. To this end, we traverse the performance gap between two linear network coding schemes: random linear network coding (RLNC) and instantly decodable network coding (IDNC). Our approach is to appropriately partition a block of partially received data packets into subgenerations and broadcast them separately using RLNC. Through analyzing the factors that affect the performance of a generic partitioning scheme, we are led to develop a coding framework in which subgenerations are created from IDNC coding sets in an IDNC solution. This coding framework consists of a series of coding schemes, with classic RLNC and IDNC identified as two extreme schemes. We develop two basic partitioning guidelines, including disjoint partitioning and even partitioning. We design various implementations of this coding framework, such as partitioning algorithms and generation scheduling strategies, to further improve its throughput and decoding delay, to manage feedback frequency and coding complexity, or to achieve in-block performance adaption. Their effectiveness is verified through extensive simulations, and their performance is compared with an existing work in the literature.

On deterministic linear network coded broadcast and its relation to matroid theory

Deterministic linear network coding (DLNC) is an important family of network coding techniques for wireless packet broadcast. In this paper, we show that DLNC is strongly related to and can be effectively studied using matroid theory without bridging index coding. We prove the equivalence between the DLNC solution and matrix matroid. We use this equivalence to study the performance limits of DLNC in terms of the number of transmissions and its dependence on the finite field size. Specifically, we derive the sufficient and necessary condition for the existence of perfect DLNC solutions and prove that such solutions may not exist over certain finite fields. We then show that identifying perfect solutions over any finite field is still an open problem in general. To fill this gap, we develop a heuristic algorithm which employs graphic matroids to find perfect DLNC solutions over any finite field. Numerical results show that its performance in terms of minimum number of transmissions is close to the lower bound, and is better than random linear network coding when the field size is not so large.

Time domain synchronization and decoding of P1 symbol in DVB-T2

In this paper we propose a novel timing and frequency synchronization and decoding method for the P1 symbol in DVB-T2 based on the correlation between the received signal and the time domain P1 symbols. This method does not require post-FFT decoding and is insensitive to the frequency-shift offset and continuous-wave (CW) interference. The performance of the proposed method is evaluated via computer simulations, which shows that not only does it achieve good synchronization performance, but also it provides a decoding SNR gain of at least 6dB in AWGN channel and at least 2dB in multipath Rayleigh fading channel compared with the performance reported in the standard guidelines.

On minimizing the average packet decoding delay in wireless network coded broadcast

We consider a setting in which a sender wishes to broadcast a block of K data packets to a set of wireless receivers, where each of the receivers already has a subset of the data packets available to it (e.g., from prior transmissions) and wants to obtain the rest of the packets in the block. Our goal is to find a linear network coding scheme that yields the minimum average packet decoding delay (APDD), i.e., the average time it takes for a receiver to decode a data packet. Our contributions can be summarized as follows. First, we prove that this problem is NP-hard by presenting a reduction from the hypergraph coloring problem. Next, we show that the random linear network coding (RLNC) technique provides an approximate solution to this problem with approximation ratio of 2 with high probability. Next, we present a methodology for designing specialized approximation algorithms for this problem that outperform RLNC solutions while maintaining the same throughput. In a special case of practical interest in which each receiver wants a small number of packets, our solution can achieve an approximation ratio of 4-2/K 3. Finally, we conduct an experimental study that demonstrates the advantages of the presented methodology.

Performance characterization and transmission schemes for instantly decodable network coding in wireless broadcast

We consider broadcasting a block of packets to multiple wireless receivers under random packet erasures using instantly decodable network coding (IDNC). The sender first broadcasts each packet uncoded once, then generates coded packets according to receivers’ feedback about their missing packets. We focus on strict IDNC (S-IDNC), where each coded packet includes at most one missing packet of every receiver. But, we will also study its relation with generalized IDNC (G-IDNC), where this condition is relaxed. We characterize two fundamental performance limits of S-IDNC: (1) the number of transmissions to complete the broadcast, which measures throughput and (2) average packet decoding delay, which measures how fast each packet is decoded at each receiver on average. We derive a closed-form expression for the expected minimum number of transmissions in terms of the number of packets and receivers and the erasure probability. We prove that it is NP-hard to minimize the average packet decoding delay of S-IDNC. We also prove that the graph models of S- and G-IDNC share the same chromatic number. Next, we design efficient S-IDNC transmission schemes and coding algorithms with full/intermittent receiver feedback. We present simulation results to corroborate the developed theory and compare our schemes with existing ones.

Rapprochement between instantly decodable and random linear network coding

In this paper, a new network coding model is proposed to unify instantly decodable network coding (IDNC) and random linear network coding (RLNC), which have been considered to be incompatible in the literature. This model is based on a novel definition of generation, which is built upon optimal IDNC solutions. Under this model, IDNC and RLNC are only two extreme cases with specific generation sizes. Throughput and delay properties of this model, measured by block completion time and packet decoding delay, respectively, are studied, which fill the gap between IDNC and RLNC and thus provide a good understanding on the throughput-delay tradeoff of network coding. An efficient adaptive scheme is then designed, which allows in-block switch among IDNC and different levels of RLNC, so that the systems throughput and delay can be fine-tuned to meet the real-time requirements of the application. Extensive simulations are performed to demonstrate how the proposed generation size interacts with the number of receivers and the channel quality to affect the overall system performance.

Feedback-Assisted Random Linear Network Coding in Wireless Broadcast

The paper focuses on the reliable delivery of a stream of packets from a sender to a set of receivers over a lossy broadcast channel with limited receiver feedback. To facilitate efficient data transfer, the packets are grouped into generations. For each generation, we employ a two- phase coding scheme that transmits uncoded packets in the first phase and coded packets in the second phase. We assume that the packet reception status of receivers after the first phase is known through feedback. To enable tunable tradeoff between throughput, computational load, and packet decoding delay, we partition each generation into sub-generations, such that each coded packet is a linear combination of packets that belong to the same sub- generation. We focus on the optimal sub-generation partitioning problem which limits the number of transmissions required to deliver all packets that belong to each sub-generation. We show that this problem is NP- complete and present a heuristic algorithm for its solution. Our simulation results indicate that the proposed algorithm outperforms existing alternative solutions.