A Coordinated Resource Allocation Algorithm for Infrastructure-Based Relay Networks

This paper addresses channel state information (CSI) estimation in a wireless relay network, which consists of a base station (BS), a relay station (RS), and a mobile station (MS). We propose a method for the BS to obtain the instantaneous CSIs of the three links (BS-RS, BS-MS, and RS-MS links) with minimized overhead. The CSI availability plays an important role for the BS to adapt its transmission strategies to the given channel conditions. Our proposed method exploits the fact that the link condition between fixed BS and fixed RS tends to be stable, and the frequent CSI update is not necessary for this link. In order for the BS to obtain the CSI of the distant link (i.e. RS-MS link), RS amplifies a pilot signal received from MS with a pre-defined amplification factor, and forwards it to BS. This enables the BS to obtain the CSI of the RS-MS link based on the received pilot signal and pre-knowledge on the CSI of BS-RS link. We show by computer simulation that our proposed method can reduce the required overhead for CSI estimation with little degradation on the accuracy of the obtained CSI.

Multiple-input multiple-output (MIMO) wireless communication systems in combination with orthogonal frequency division multiple access and space division multiple access are flexible, spectrally efficient and of high capacity. These systems can allocate frequency, time, and space resources adaptively among mobile stations. Optimal resource allocation (RA) for maximizing the sum rate is usually too complex for practical applications, hence suboptimal algorithms are required. The performance of RA algorithms are degraded due to imperfections in channel state information at transmitter (CSIT). Thus, techniques that make the RA algorithm, robust against CSIT errors are favorable. In this paper, two novel suboptimal grouping algorithms are introduced that are shown to achieve better sum rate-complexity and fairness-complexity performances. A novel index is proposed to measure the efficiency of RA algorithms, which takes into account sum rate and complexity simultaneously. Moreover, the effect of erroneous CSIT on sum rate is investigated and it is shown that performance of the proposed RA algorithms with erroneous CSIT are superior to the existing schemes. Finally, fairness performance of the proposed RA algorithms are evaluated, which are shown to be the same if not superior to other existing algorithms.

The problem of resource allocation (RA) in a downlink OFDMA system with minimum user rate requests is examined under the realistic scenario of partial (imperfect) channel state information (CSI) at the base station. The challenge in this setting is the non-zero probability of outage events which may lead to significant performance degradation if algorithms assuming perfect CSI are utilized. In this paper the statistical description of the partial CSI is incorporated for deriving an (optimal) RA algorithm as the solution of an appropriate constrained optimization problem. Simplifications of the algorithm are utilized for significant complexity reduction with the additional property of allowing the system to adapt on-the-fly to time-varying minimum user rate requests.

In this paper, we present a power allocation technique that improves the sum rate and energy efficiency without reducing the minimum data rate of an established resource block allocation technique. To achieve this, the technique is implemented in two stages where the first is for ensuring that the minimum data rate remains unchanged. The second stage is for increasing the sum rate by ensuring that more resource blocks are reused by the femtocells that reduce their power. The algorithm is iterative with changes in transmit power resulting in changes in resource block allocation. It will be shown that at the expense of some delay, the proposed technique can result in significant energy savings while maintaining the minimum data rate when compared to equal power allocation. Further, relative to optimal allocation techniques, the proposed technique results in better fairness.

In this paper, we consider two different models of partial channel state information at the base station transmitter (CSIT) for multiple antenna broadcast channels: 1) the shape feedback model where the normalized channel vector of each user is available at the base station and 2) the limited feedback model where each user quantizes its channel vector according to a rotated codebook that is optimal in the sense of mean squared error and feeds back the codeword index. This paper is focused on characterizing the sum rate performance of both zero-forcing dirty paper coding (ZFDPC) systems and channel inversion (CI) systems under the given two partial CSIT models. Intuitively speaking, a system with shape feedback loses the sum rate gain of adaptive power allocation. However, shape feedback still provides enough channel knowledge for ZFDPC and CI to approach their own optimal throughput in the high signal-to-noise ratio (SNR) regime. As for limited feedback, we derive sum rate bounds for both signaling schemes and link their throughput performance to some basic properties of the quantization codebook. Interestingly, we find that limited feedback employing a fixed codebook leads to a sum rate ceiling for both schemes for asymptotically high SNR.

IEEE 802.16j is an amendment to the IEEE 802.16 broadband wireless access standard to enable the operation of multihop relay stations (RSs). It aims to enhance the coverage, per user throughput of IEEE 802.16e. Comparing with a base station (BS), RS does not need a wireline backhaul and has much lower hardware complexity. Moreover, using RSs can significantly reduce the deployment cost of the system. Unfortunately, there are some tradeoffs in the case of multi-hop RSs. Subscriber stations (SSs), located in a long distance, are suffered from the bottleneck of multi-hop, throughput degradation, and increasing of end-to-end delay. This paper proposes a network coding-based relay scheme for multi-hop relay networks, called NC-BR. It allows RSs to combine two wireless backhaul transmissions into one using the network coding technique. This paper also proposes an improved OFDMA frame structure design for the multi-hop relay network. This technique provides higher utilization for the relay zone by reorganizing the RSs transmission sequence. The analysis and simulation results confirm that the proposed scheme can enhance the throughput gain up to 140% and reduce the end-to-end delay by up to 83%. The simulation results also show that the proposed scheme can reduce the jitter by up to 58%.

Coordinated Beamforming (CB) is an effective technique to maximize weighted sum rate (WSR) targeting at on-demand network capacity. However, the channel state information (CSI) of the base stations (BSs) far away can’t be measured accurately, which will lead to the invalidation of the traditional WSR-maximization beamformer design and eventually result in capacity decrease. This letter proposes a tractable user-centric CSI model and a robust CB design to maximize WSR with partially accurate CSI. Specifically, the CSI model of the coordinated BSs is built for each user, where the inaccurate CSI of BSs far away from this user is modeled according to its static statistic characteristic. To derive a robust beamformer, deterministic equivalent method is adopted to obtain an approximate closed-form expression of the ergodic sum rate. Moreover, the performance of the robust CB design with different model parameters is considered to provide guidance for practical network deployment. Simulation results show that the proposed robust CB design has 30% capacity gain through careful interference management compared with traditional beamforming.

A multi-user network code assisted HARQ system with cooperative relay is proposed. Uplink (UL) transmission with multiple mobile-stations (MSs) cooperating with a relay-station (RS) using HARQ is considered. The RS is assumed to he able to successfully monitor and decode the packets transmitted from the MSs to the base-station (BS). The BS partitions the incorrectly decoded packets into groups based on their MS-to-BS channel conditions and feedback this partition to the RS along with the acknowledgement (ACK) or negative acknowledgement (NACK). The RS employs, for each group inside the partition, a network-coded HARQ scheme using packets in that group for subsequent retransmissions. We proposed a dynamic and adaptive partitioning method based on the channel state information at the BS and the corresponding HARQ retransmission schemes. Also, we derived the corresponding low-complexity joint demodulation and decoding structure for this multi-user HARQ scheme. We found via simulations that our proposed scheme can improve the system throughput by around 15% when compared with the simple relay assisted chase combining HARQ system.

Introduction It is envisioned that the capacity demand in fifth generation (5G) wireless networks will increase by 1000 times before the year 2020, and this huge demand will be fueled by high-definition video and content streaming applications, which not only consume immense wireless bandwidth but also have stringent real-time quality of service (QoS) requirements. Small-cell dense wireless networks are regarded as a key candidate 5G technology to meet such aggressive demand. By dense deployment of small-cell base stations (BSs), the network becomes closer to mobile users, and thus the spectral efficiency per unit area can be significantly improved. Moreover, relay stations (RSs) without wired backhaul can also be deployed to enhance the coverage area and provide signal-to-noise ratio (SNR) gain. While there are many potential opportunities associated with dense wireless networks, the potential spectrum efficiency gain they can provide is significantly limited by increasingly severe interference due to the densification of BSs. There are several common schemes to mitigate interference. In the strong-interference case, channel orthogonalization, such as frequency division multiple access (FDMA) or time division multiple access (TDMA), is used to avoid interference [1], and advanced schemes, such as interference alignment (IA) [2, 3] and interference coordination [4, 5], have been proposed to increase the spectral efficiency of interference channels by jointly mitigating the interference using shared channel state information (CSI). However, these approaches may lead to inefficient use of channel resources because the transmitters do not share payload information and therefore are not fully cooperative. To improve the spectrum efficiency further, coordinated multipoint (CoMP) transmission has been proposed as one of the most important core technologies for Long Term Evolution-Advanced (LTE-A) and future 5G wireless networks [6]. By sharing both CSI and payload data among the BSs concerned, CoMP transmission can transform the wireless network from an unfavorable interference topology to a favorable broadcast topology, where the interference can be mitigated much more efficiently. However, the conventional CoMP scheme is quite costly because it requires a high-capacity backhaul for payload exchange between the BSs, and this poses a huge challenge for practical applications of CoMP, especially for small-cell dense wireless networks.

For conventional multiple-input and multiple-output (MIMO) selective decode-and-forward (S-DF) relaying network, without global channel knowledge, base station (BS) normally allocates its transmission power for the channel links between itself and its served users. In this case, if the received signal power at relay station (RS) is larger enough, RS will help BS decode and forward the messages. However, such strategy may lose system optimality if BS has the location information of RS. Motivated by this, in this paper, a RS-oriented BS power allocation algorithm for MIMO S-DF relaying is proposed to enhance the system performance. Specifically, BS firstly allocates its transmission power to help as much as data streams to be correctly decoded at RS. Then, if there is still some power left, BS will allocate the residual power for its direct channel links to the users to further increase the system performance. Computer simulations are carried out to examine the proposed scheme in terms of sumrate and bit-error-rate. It is shown that the proposed scheme outperforms the conventional schemes, especially when the RS is placed in the middle of BS and the users.

The objective of this paper is to study the performance of a multicell vector perturbation (MVP) precoding technique under practical situations in a network multiple-input multiple-output (MIMO) scheme employing joint transmission. The conventional perturbation strategy that minimizes the total power is considered, and the power at each base station (BS) is properly scaled to enforce per-BS power constraints. In our scenario, we consider multiple-antenna users and use block diagonalization (BD) as the linear front-end precoder for VP. The sum rate for the MVP in the case of uniformly distributed input and an asymptotic upper bound on the sum rate at high signal-to-noise ratios (SNRs) are derived. In addition, using the asymptotic upper bound on the individual user rates, we propose a proportionally fair (PF) user scheduling algorithm of lower complexity and better performance compared with the benchmark fair semiorthogonal user selection (SUS) algorithm. As opposed to the PF-SUS, the proposed PF scheduling algorithm requires no predefined correlation threshold. Furthermore, we study the impact of backhaul delay on the performance of both VP and BD by deriving bounds on the sum rate. The numerical results show that MVP in the case of perfect channel state information (CSI) outperforms multicell BD. In the presence of a backhaul delay, the performance of MVP significantly degrades, but the upper bound on the sum rate for MVP is still higher than for multicell BD.

Network MIMO is a technology being developed towards lifting the interference limits on wireless network through collaborative transmissions from multiple base stations. However its great potential is shadowed by the stringent requirement of high speed/capacity backbones facilitating information exchange, including data, control signals, and channel state information amongst the base stations. In this paper, we propose a user-selective collaboration scheme to mitigate the backbone requirement by reducing the information exchange required. We define a certain threshold for users in each base station and only those users exceeding the threshold will be served by multiple base stations collaboratively. The other users will be served by a single base station as in a conventional non-collaborative transmission. The threshold is determined in such a way that the users with collaborative transmissions enjoy maximized sum rates whereas the others without collaborative transmissions sacrifice only marginal potential collaboration gain in terms of achievable maximized sum rates. As the amount of information to be exchanged will be a square function of the number of users served by the collaborative base stations, the user-selective scheme can reduce the backhaul overhead significantly.

Considering a multi-cell OFDM downlink network, a basic problem is to perform resource allocation to maximize the spectral efficiency (SE). In this paper, we divide it into a user scheduling subproblem and a power allocation subprolem, and then adopt a resource allocation algorithm based on imperfect channel state information (CSI). Universal frequency reuse is considered, and the cochannel interference is dealt with via the cooperation of multiple base stations (BSs) sharing CSI but not user data. Since the wireless communication environment may change rapidly and need real-time computation, we then propose a deep neural network (DNN) approach to approximate the resource allocation algorithm, which greatly reduces the computation time and is capable of ”on-the-fly” adaptation to a time-varying environment. Simulation results verify the effectiveness of the DNN implementation, especially when the number of cells and subcarriers is large.

Ergodic mutual information of OFDMA-based Selection-Decode-and-Forward cooperative relay networks with imperfect CSI

The amendment of 802.16e has been released lately by IEEE 802.16 Relay Task Group j. For the sake of improving throughput and extension of cell coverage, relay stations (RSs) are deployed in the network. Intuitively, the base station (BS) selects a path for a target subscriber station (SS) according to Signal to Interference plus Noise Ratio (SINR) or the available bandwidth. However, it will lead to inefficient resource utilization and low system capacity since some RSs may have high traffic load whereas others may have redundant bandwidth. To tackle this problem, we propose a traffic-aware routing algorithm. By taking into account both resource utilization and load balance, our proposed scheme ensures that paths with heavy traffic load and long hop distance will not be selected while establishing the route. Simulations results demonstrate that, with the proposed traffic-aware routing algorithm, users are able to transmit more packets over the same period. And, not only the latency is limited in a reasonable range but also the throughput and the packet delivery ratio are enhanced.